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Digital Connectivity Reshapes Insurance Communications

Digital connectivity streamlines workflows and strengthens relationships among carriers, agents and policyholders.

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By combining digital tools and advancements with personal interactions, carriers can better engage with agents. Modernizing traditional processes improves links among agents, managing general agents (MGAs), carriers, and policyholders and streamlines workflows, enabling a better experience while saving valuable resources that can be allocated elsewhere, like to customer-facing goals. 

Digital connectivity goes beyond portals by integrating data across different, often disparate, systems. Its reach extends beyond simply modernizing workflows to the potential of reshaping the insurance industry. A recent Ivans report explored these topics and trends, including responses from more than 1,400 agents, carriers, MGAs, and technology providers. The report revealed critical next steps for the future of the insurance ecosystem.

The Evolution of Digital Connectivity

Carriers have traditionally relied on portals, phone calls, or in-person meetings to interact with agents. These methods were functional but often resulted in delays and inefficiencies. There were fewer opportunities for information to be relayed instantly, and agents were managing multiple log-ins and learning different systems for each carrier. These workflow challenges created redundancies and increased the risk of errors.

In the future, agents will no longer navigate disparate portals, duplicating efforts and spending more time than needed on administrative tasks. Instead, they will interact with carriers through a centralized hub, or single, integrated platform linking all stakeholders in one user-friendly place. By shifting to this integrated system, agents will have more time to focus on building relationships and servicing policyholders, while the platform seamlessly reduces friction.

Digital rating and appetite usage increase the number of carriers an agent submits applications to, so carriers see more submissions and write new business they could not previously access, thanks to advancements in digital connectivity. Eliminating manual data entry steps and integrating real-time data and synchronous conversations means carriers can process submissions more quickly and with greater accuracy. Carriers can use this strategy to give agents the right tools to succeed, making it a winning model for everyone. Policyholders also benefit when submissions are accurate and priced properly.

Digital connectivity at its simplest means connecting agents and carriers through digital pipelines to transmit information instantly, a transformative upgrade from sending information through the mail or sharing it via large zip drives. 

While carriers need to adopt digital tools, the opportunity to modernize also brings challenges.

See also: How Everybody Wins in a Digitized Insurance Market

The Challenges and Opportunities of Digital Connectivity

Carriers and agents may want to adopt digital connectivity tools, but their level of readiness varies. Some larger carriers that have already undergone change management and digital transformations can leverage their existing platforms to improve connectivity. Small and mid-sized carriers, however, may struggle with resources and legacy systems as they plan extensive digital projects.

Carriers may resist changing their portal design to one with more digital connectivity because they fear losing customers who have adapted to the current platform or losing the competitive edge they have built through branding and user experience. However, improving digital connectivity offers built-in advantages as the industry moves toward greater integration, creating opportunities for carriers that embrace the shift toward modernization.

Artificial intelligence (AI) continues to revolutionize digital connectivity and tools. It frees time for carriers as it can review and summarize vast amounts of records and data, automate manual tasks like data entry, and provide insights and next steps for underwriters and adjusters. Document management and ingestion is a prime example where underwriters currently spend hours manually reviewing submissions, but AI could streamline the process to give underwriters more time to spend on complex, high-value tasks.

The Trends Driving the Future of Digital Connectivity

Several trends will shape the future of digital connectivity in insurance:

  • Agents will increasingly choose carriers based on digital capabilities. Recent research found that 83% of agents prioritize digital tools when selecting a carrier partner. Those carriers that offer streamlined, tech-forward workflows become the preferred option.
  • Carriers want to explore new technologies to help streamline communications, with 85% of carriers agreeing they would invest in technology to receive more complete commercial submissions and minimize the back-and-forth discussions between underwriters and agents.
  • Real-time data and quoting solutions help agents place business faster, with fewer declinations. Eighty-seven percent of agents surveyed confirmed they would write more business with carriers if they provided real-time appetite and quoting within their agency management systems.
  • AI-powered efficiencies will continue transforming underwriting, claims, and policy administration. Automating routine tasks, enhancing analytics, and predicting risk with AI tools will give agents and carriers time to focus on other strategic initiatives.
  • Connectivity tools designed to match excess and surplus (E&S) market growth are essential. The E&S market is growing, with 48% of agents noting increased placements in the market, which means E&S carriers that embrace digital connectivity can meet this growing demand and stay competitive.
  • Partnerships are key in advancing digital connectivity. By partnering with established vendors and innovative startups, carriers and agents can access customizable platforms that meet their unique needs.

See also: 3 Steps for Insurers to Keep the Human Touch

Digital Connectivity Transforms the Insurance Ecosystem

Carriers and MGAs that adopt digital tools can improve efficiency while reducing costs and strengthening agent relationships. Agents benefit from the faster workflows and advanced data insights this digital connection brings. The future is clear — digital connectivity empowers all insurance stakeholders. It can transform the insurance industry into a more collaborative, streamlined, innovative ecosystem where connections are prioritized and each player can unlock opportunities in a rapidly changing market.


Reid Holzworth

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Reid Holzworth

Reid Holzworth is CEO at Ivans, a network for greater connectivity throughout the insurance lifecycle.

Holzworth was the founder and CEO of TechCanary, which Applied Systems acquired in 2019. TechCanary built insurance solutions on the Salesforce platform to create choice and flexibility for agencies: 

Digital Adoption Platforms Transform Operations

Digital adoption platforms are revolutionizing insurance operations, driving efficiency and transforming employee training.

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Insurers are feeling the pressure to adopt digital strategies or risk falling behind. In fact, a recent study found that more than 50% of insurers believe digital transformation is vital to attracting consumers and improving current policyholder retention rates. The time for change is now. 

Many insurance companies are modernizing their core systems across claims, underwriting and billing, migrating to the cloud, and digitizing distribution channels to meet growing demands. However, the key to successful transformation lies not just in adopting new technologies but in ensuring that employees can seamlessly navigate and leverage them.

Common Digital Adoption Challenges

Legacy systems often lead to data fragmentation and inefficiencies, but the transition to modern, cloud-based platforms can be challenging. This shift requires significant upfront investment and can meet resistance from long-standing employees accustomed to older systems. Still, many insurance leaders believe the limitations of legacy systems have become a major roadblock.

Insurance companies also face the growing skills gap and aging workforce. As these companies adopt new technologies, they must take the time to upskill their existing workforce and make the industry more appealing to younger, tech-savvy professionals. Additionally, entrenched processes and resistance to change within organizations can present challenges and slow the pace of digitization. This is where strong change management becomes essential. Organizations must foster a culture that is open to innovation, where employees at all levels are encouraged to embrace new technologies.

The Benefits of Digital Adoption Platforms

Digital adoption platforms (DAPs) revolutionize how insurers engage with new technologies by providing contextual, in-the-moment support tailored to each user's role and skill level. Instead of relying on generic training materials, DAPs deliver personalized, interactive learning paths that enable employees to learn by doing. For example, a new insurance agent logging into a claims platform for the first time would immediately receive an interactive walkthrough customized to their tasks, ensuring they grasp core functions while completing real work. This hands-on approach reduces learning curves and fosters faster adoption.

DAPs also offer targeted, real-time guidance to help employees overcome common roadblocks without losing momentum. For instance, if an adjuster hesitates while filling out a complex claims form, a contextual tip can instantly clarify the requirements, unblocking progress and ensuring accuracy. By delivering support at the moment it is needed, DAPs empower employees to work more independently, which increases their confidence and reduces dependency on IT and training teams.

DAPs can also provide insurance companies with valuable insights into how their employees interact with digital tools. Analytics capabilities can identify underused features and highlight areas of friction within workflows. With this data, insurers can optimize their systems and tailor and refine their processes to align with their employees' needs. This continuous cycle of feedback and improvement ensures digital platforms remain agile and effective, which not only enhances employee satisfaction but also leads to optimized efficiency and increased return on investment.

Real World Successes

Many insurance companies have already reaped the benefits of digital adoption. Sentry Insurance, for instance, implemented an innovative digital adoption platform across eight key applications. It accelerated staff onboarding and saw a 40% reduction in the time it took to create training content, shaving 30 hours off for each item. As staff became proficient faster, they minimized errors and improved customer interactions. A more intuitive workflow also decreased the number of support tickets raised by agents, boosting operational efficiency and employee engagement. In 12 months, Sentry saved over $950,000, which it allocated to growth-oriented activities.

Looking Ahead

Industry forecasts predict the digital insurance platform market will grow 12% annually through 2029. With DAPs, insurers have the ability to harness real-time data, to predict trends, customize products and offer personalized experiences at every touchpoint. This not only improves customer satisfaction but also strengthens internal processes, driving efficiency and accuracy across the organization.

By implementing a digital adoption platform, insurers can develop innovative solutions that address emerging risks and meet evolving customer needs.

 


Vara Kumar

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Vara Kumar

Vara Kumar is the co-founder and head of R&D and solutions at Whatfix.

Kumar co-founded Whatfix with Khadim Batti in 2014 with the vision of empowering individuals and organizations to work symbiotically with technology to maximize their potential. 

4 Golden Opportunities With AI

From customers and employees to the business and society, a recent study identified four ways AI can make insurance more humane.

Artificial Intelligence

There's a story most of us know about insurance and technology. It goes something like this: a new technology trend emerges—telematics, blockchain, cloud computing, big data, embedded insurance... fill in the blank. The insurance industry latches on. Hype ensues. For a conference cycle or two, this is all we hear about.

Big investments follow, multiyear transformation efforts get underway… and yet, years later, nothing has fundamentally changed. Insurance is still as complex as ever, if not more so. Legacy systems handicap modern user experience (UX) efforts, multiple data sources compete instead of connect, and layers upon layers of infrastructure weigh down any real progress. Meanwhile, insurance products remain largely the same. While some customer experiences marginally improve — just enough to start to feel "modern" (great, I can pay my premium online now!) — others deteriorate (whatever happened to customer service?).

And the industry moves on, chasing the next big idea.

Will AI be any different? The answer to that question is, of course, "it depends." It depends on a lot of factors, not the least of which is the industry's motives for AI adoption. Will insurers approach AI transformation as it has past transformations, through a purely utilitarian lens, focused on operational efficiencies, cost-cutting and risk reduction? Or will it surprise us all and take a more human-centered approach to AI?

We hope to be surprised.

Can AI usher in a new golden age for insurance?

A recent report explores what the future of insurance might look like should the industry pursue AI through a human-centered lens—motivated not just by what AI can do for the business but by what AI can do for its policyholders, employees and all the people involved in the insurance ecosystem.

As customer experience designers know: What's good for policyholders, employees and people is also good business.

The report asks: Can AI usher in a new golden age for insurance? One where policies are easy to understand, affordable and tailored to customer needs? Where employees are fulfilled and empowered, with the resources to excel and flourish? Where businesses are unburdened by legacy technology, gaining streamlined access to data that helps them efficiently write and sell policies relevant to an evolving customer base? And where all of society—not just the privileged few—can access the protection and financial stability they need to thrive?

The opportunity is clear: AI can help insurance become not just smarter or faster or more profitable but also more humane. Who wouldn't want to sign on to that?

Based on decades of work with dozens of top insurers and insights gathered from thousands of policyholders, agents, brokers and employees through research, the study identified some of the biggest challenges plaguing the industry, across the insurance value chain—from customers, employees and businesses, to society at large–with a vision for how AI might elevate these experiences for everyone.

Four golden opportunities for how to use AI to make insurance more humane

1. For customers: Shifting the burden of complexity off the customer.

Insurance is inherently complex—policies are dense with jargon, products are hard to compare, and navigating claims or coverage can feel like an endless maze. This complexity creates a major barrier to delivering a positive, human experience. Customers often feel overwhelmed and frustrated, as though they're dealing with a faceless, impersonal system rather than a service designed to care for them. Despite insurers' efforts to be transparent, the intricacies of risk, coverage and pricing leave many customers feeling alienated and disconnected.

The study explores how the real promise of AI lies in its ability to combine insurance's inherent complexity with a deep understanding of the customer. Generative AI can craft highly personalized, intuitive experiences that make customers feel seen, heard and confident in their coverage—transforming insurance from a transactional process into one that feels human, empathetic and rewarding.

As AI becomes more sophisticated, insurers must navigate the human consequences—ensuring that automation enhances experiences without eroding internal expertise, weakening brand identity or diminishing the value of human interaction.

2. For employees: Alleviating employee burnout.

Insurance claims departments and call centers are critical during high-impact events like storms and natural disasters, but employees—particularly claims adjusters—are often overwhelmed by surges in workload. Long hours, limited resources and a shrinking talent pool exacerbate the problem, leading to burnout, high turnover and slower service for customers.

The report envisions how human-centered AI might offer a smarter way to manage workloads by predicting surges—using real-time data like weather forecasts—and proactively adjusting staffing. Drawing inspiration from models like healthcare's traveling nurses, insurers can integrate highly trained, well-compensated temporary workers to relieve pressure on full-time staff. This approach improves work-life balance, reduces burnout and ensures customers get faster, more empathetic service during critical moments.

While AI can fairly distribute work and manage surges, insurers must ensure it doesn't come at the cost of job stability, team cohesion or human judgment—particularly in complex or unexpected scenarios.

3. For the business: Empowering a new generation of brokers and agents.

As baby boomers retire, they take decades of institutional knowledge with them, leaving behind a generation-sized gap in expertise. This is particularly acute for brokers, claims adjusters and underwriters, whose deep understanding of products, clients and complex decision-making processes is difficult to replace. Traditional mentorship programs and documentation efforts have fallen short, as they often fail to capture the nuances of expertise or fit into employees' already demanding schedules.

The study discusses how AI offers a powerful opportunity to preserve and distribute this expertise if executed with a human-centered focus. By analyzing years of documentation, correspondence and decision-making in real time, AI can transform the tacit knowledge of experienced professionals into actionable guidance for newer employees. For brokers, claims adjusters and underwriters, this means real-time decision support that bridges the knowledge gap while fostering continuous learning.

While AI can scale expertise and streamline onboarding, insurers must ensure it complements—not replaces—human mentorship and critical judgment, which are essential for developing talent and innovation.

4. For society: Making insurance more accessible, affordable and fair.

Rising premiums, driven by climate risks, claims costs and administrative inefficiencies, are making insurance unaffordable for those who need it most. In some regions, premiums have surged by double digits while coverage has narrowed, leaving vulnerable populations exposed. Meanwhile, up to 30% of premium dollars are absorbed by outdated processes and bloated back-office operations, further inflating costs.

The report dives into how AI has the potential to transform insurance into a more transparent, affordable and utility-like service. By leveraging real-time data and automating risk analysis, AI can enable fairer premiums and faster claims processing. Combined with smart contracts, AI could revive peer-to-peer insurance models, making risk-sharing viable, scalable and equitable—particularly for underserved communities.

Still, while AI streamlines processes and lowers costs, it raises important questions: Can it preserve the sense of community and trust peer-to-peer models rely on? And what will happen to the thousands of jobs tied to insurance's administrative backbone as automation takes hold?

A human-centered path toward a new golden age

The insurance industry stands at a crossroads. AI has the potential to do what past technologies could not—transform insurance into a system that works better for everyone. But to get there, insurers must rethink their approach, shifting their focus from efficiency and cost-cutting alone to better supporting people.

The opportunity is clear. AI can help insurers meet the demands of a changing world while delivering experiences that build trust, confidence and connection. The choice now lies with the industry: Will it use AI to perpetuate the status quo, or will it seize this moment to usher in a new golden age—one where technology truly serves people?

The future of insurance is waiting. The question is, will we rise to meet it?

For a deeper exploration of these ideas and actionable strategies for achieving a more human-centered future, download our full report, A New Golden Age for Insurance

 


Emily Smith

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Emily Smith

Emily Smith is the senior manager of communication and marketing at Cake & Arrow, a customer experience agency providing end-to-end digital products and services that help insurance companies redefine customer experience.

The Key to Unlocking Life Insurance Sales

Behavioral science offers solutions to demystify complex life insurance products.

Black Handled Key on Key Hole

Customer acquisition has been a thorn in the side of life insurance providers in the U,S. The number of American adults with life insurance has declined since the 2010s, leaving more consumers uninsured or underinsured and affecting other corners of the financial sector. Although ownership has stabilized post-pandemic, insurance companies aren't protecting enough consumers financially.

Life Insurance Remains Widely Misunderstood

Out of all mainstream insurance products, life insurance is the most underappreciated. It doesn't inspire a sense of urgency like auto insurance, which is mandatory. Life insurance isn't a legal requirement in financial transactions — the opposite of homeowners insurance, which mortgage lenders demand before releasing funds to borrowers.

The public views life insurance more as discretionary and less as essential. The fact that only 37% of adults surveyed in January 2024 — out of the 42% who admitted they need or need more insurance — said they plan to buy a policy within the next 12 months proves this.

The 2024 Insurance Barometer study by LIMRA and Life Happens found that American consumers don't own any life insurance policy at all or don't own more coverage because of three reasons:

  • High cost
  • More important financial priorities
  • Confusion about what to buy and how much

On the bright side, nearly three-fourths of consumers overestimate the actual cost of a basic term life insurance policy, and more than half rely purely on gut instinct. Debunking the myth that life insurance is out of reach and articulating its value as an estate-planning tool can move the needle on sales.

Unfortunately, insurance companies have yet to close this knowledge gap with marketing. The research commissioned by the SOA and RGA and published in August 2024 suggests that life insurance product information could be more straightforward, resulting in miscomprehension among consumers and stagnant sales.

Curiously, low popularity for estate planning in the U.S. coincides with the downward trajectory of life insurance ownership. Financial advisers' significant role in estate plan adoption reinforces the need for product clarity to inspire sales. After all, the adults with access to sound financial advice are four times more likely to have an estate plan.

History Says Simplifying Language Alone Doesn't Work

Life insurance information complexity is old news. Insurers have known this for a long time and attempted to explain the intricacies of this financial product in layperson's terms to no avail. On the contrary, attempts have backfired.

In the mid-2010s, LIMRA tested the traditional "quick and easy" marketing message to entice Americans to buy life insurance. This strategy didn't work as well on life insurance as it normally does on most retail goods. Out of all the marketing messages the researchers used, this one performed the worst.

The trade association did a follow-up study in 2017. LIMRA tried 10 different messages, emphasizing the benefits of buying insurance online. Although some did better than others, none was a runaway winner.

There are two takeaways:

  • Convenience isn't as powerful a motivator as thought.
  • Simple language alone doesn't sell.

Incorporating behavioral science techniques into content simplification efforts may be the key to spurring life insurance ownership.

Behavioral Science: Making Life Insurance Easier to Understand

Explaining the nitty-gritty of life insurance is only half the battle. Convincing the public that a financial product generally viewed as only beneficial after death is the other.

Life insurance providers can reduce misconception throughout the sales journey by acknowledging that humans have limited cognitive resources. Only a few people have the time to exert considerable mental effort to understand and appreciate financial products. Naturally, consumers would concentrate their time, attention and bandwidth on those aligned with their near- and long-term goals.

Rising retirement anxiety is one of the reasons life insurance has been a hard sell of late. In 2024, 79% of Americans believe the country faces a retirement crisis — up from 67% in 2020. Discerning life insurance carriers would view this sentiment as an opportunity to debunk the notion that policyholders can't enjoy the coverage while alive.

More adults may give life insurance products a second look if they're aware of living benefits. Marketing cash value accounts as financial cushions and living benefit riders as means to tap the death benefit during the policyholder's lifetime can generate interest and entice consumers to learn more.

Behavioral science can help reinforce a simplified marketing message while shifting the focus to specific life insurance components that resonate with more consumers. Various techniques can help insurers leverage the human tendency to think fast or slow when making decisions.

Fast thinking refers to routine decision-making, which involves no conscious deliberation, while slow thinking involves deeper logical consideration to judge more complex subjects. Designing customer journeys with this in mind can improve life insurance comprehension and may translate to higher customer acquisition.

Behavioral Science Techniques to Complement Simplification

Simplification is a behavioral science technique. However, timeliness, salience and relevance are just as vital to demystifying life insurance. To aid comprehension, insurers should:

  • Create marketing content in plain language.
  • Present concepts at optimal moments.
  • Ensure that the most essential details visually and auditorily stand out.
  • Provide a quote matching every individual's unique situation.

There are countless ways to combine these behavioral science techniques to educate consumers about insurance online. Websites and emails with thoughtful typography, engaging visuals, FAQ sections and interactive tools are tried-and-true media.

Social media and artificial intelligence (AI) also supercharge information dissemination and content creation. Video consumption accounts for 82% of all internet traffic, so being on TikTok, producing YouTube Shorts, and uploading Reels on Facebook and Instagram are recipes for success.

Moreover, messengers are as crucial as digital channels. Life insurance buyers are judicious, so using a trusted messenger will lend credibility to content.

AI-generated avatars are also becoming more popular, as they help insurance marketing teams balance rapid content production, customization and cost-effectiveness. Considering that 99% of global insurers have invested or are planning to invest in AI, seeing this innovative approach to marketing gain currency in the future shouldn't be surprising.

Still, insurers should think twice about choosing AI over humans when engaging with prospective buyers and paying customers. While bots can soup up marketing engines and customer service portals, they have limitations. AI excels in analyzing mountains of data, identifying patterns and spotting anomalies, but nothing compares to human resourcefulness.

Human subject matter experts can provide practical advice to promote life insurance comprehension and resolve individual concerns in ways available self-help resources can't. In contrast, AI can hallucinate and spread false information, responding to queries with incorrect, biased or fabricated answers.

Allianz — A Success Story

Allianz has adopted customer-centricity through simplicity to achieve its goal of becoming one of the 25 top insurance brands by 2025. The multinational took this route at a time when most insurers embraced hyperpersonalization — an approach emphasizing providing customers with information based on their personal data, risk profiles and past interactions.

This move raised the eyebrows of many pundits, doubting the company's ability to grow while simplifying its products and processes in markets where it had traditionally sold diverse offerings.

But Allianz's decision to double down on simplicity has paid off. In 2024, the company moved up two places to become the 29th-best global and top insurance brand worldwide. Allianz's value ballooned to $23.5 billion, a 13% increase year-over-year.

Careless Execution May Cause Legal Issues

Employing behavioral science to bridge the insurance comprehension gap and boost customer acquisition carelessly may result in regulatory noncompliance. Penalties and settlements can lighten insurers' coffers, and reputational damage can be costlier.

Using behavioral science techniques effectively and legally involves considerable uncertainty and countless tests. Fortunately, dozens of recent case studies demonstrate how not to do it.

In 2015, Geico agreed to pay $6 million to settle with the California Department of Insurance. The case stemmed from the Consumer Federation of California's allegation that the auto insurer's premium quoting system discriminated against consumers based on gender, occupation and education level.

In 2020, then-Massachusetts Attorney General Maura Healy filed a case against UnitedHealth Group entities for allegedly supplemental health insurance as an alternative to primary health insurance, misrepresenting agents as licensed insurance advisers and using emotional manipulation. Healy claimed the defendants deceived more than 15,000 low-income and Medicaid-eligible consumers and violated the state's consumer protection law and a 2009 Superior Court judgment.

In 2024, Sanya Virani sued NLV Financial Corp. and two subsidiaries for allegedly using rosy illustrations to sell indexed universal life policies. The plaintiff's policy yielded a 0% return after one year. Virani argued the insurer used unrealistic back-tested historical performance. She called the product a "fraudulent sham" because she would have to pay hefty surrender fees if she terminated her policy.

Take Care With Customer Acquisition

Insurance information simplification and other behavioral science techniques aren't foolproof, so learning the lessons from others' mistakes is crucial to avoid finding an organization in hot water.


Jack Shaw

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Jack Shaw

Jack Shaw serves as the editor of Modded.

His insights on innovation have been published on Safeopedia, Packaging Digest, Plastics Today and USCCG, among others.

 

Cyber Incidents Top Global Business Risks in 2025

Cyber incidents remain the top global business risk, and climate change surges to its highest-ever ranking in the Allianz Risk Barometer.

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Cyber incidents such as data breaches or ransomware attacks, and IT disruptions, like the CrowdStrike incident, are the biggest worry for companies globally in 2025, according to the Allianz Risk Barometer.

Once again, business interruption is also a main concern for companies of all sizes, ranking No. 2. After another heavy year of natural catastrophes activity in 2024, this peril remains No. 3, while the impact of a super election year, rising geopolitical tensions and the potential for trade wars mean changes in legislation and regulation is a top five risk at No. 4. The biggest riser in this year's Allianz Risk Barometer is climate change, from No. 7 to No. 5, achieving its highest-ever position in 14 years of the survey.

The Allianz Risk Barometer is an annual business risk ranking compiled by Allianz Commercial, together with other Allianz entities. It incorporates the views of 3,778 risk management experts in 106 countries and territories, including CEOs, risk managers, brokers and insurance experts.

Large corporates and mid-size, and smaller businesses all perceive cyber incidents as their No. 1 business risk. However, there are significant differences in the rest of the ranking. Smaller companies are more concerned about more localized and immediate risks, such as regulatory compliance, macroeconomic developments and skill shortages, but there are also signs that some of the risks that have preoccupied larger companies are starting to affect smaller firms, too, with climate change and political risks and violence climbing the ranking.

In the U.S., cyber incidents once again top the list of business risks, followed by natural catastrophes at No. 2, up from the third spot in 2024. Rounding out the top three is business interruption. Changes in legislation and regulation is the biggest riser in the region, advancing to the fourth spot from No. 8 in 2024.

Cyber risks continue to increase with rapid development of technology. 

Cyber incidents (38% of overall responses) rank as the most important risk globally for the fourth year in a row – and by a higher margin than ever (seven percentage points). It is the top peril in 20 countries, including Argentina, France, Germany, India, South Africa, the U.K. and the U.S. More than 60% of respondents identified data breaches as the cyber exposure companies fear most, followed by attacks on critical infrastructure and physical assets, with 57%.

According to Rishi Baviskar, global head of cyber risk consulting at Allianz Commercial, "For many companies, cyber risk, exacerbated by rapid development of artificial intelligence (AI), is the big risk overriding everything else. It is likely to remain a top risk for organizations going forward, given the growing reliance on technology – the CrowdStrike incident in summer 2024 once again underlined how dependent we all are on secure and dependent IT systems."

See also: The Evolving Landscape of Cybersecurity

Business interruption strongly linked with other risks.

Business interruption (BI) has ranked either No. 1 or No. 2 in every Allianz Risk Barometer for the past decade and retains its position at No. 2 in 2025, with 31% of responses. BI is typically a consequence of events like a natural disaster or a cyberattack, which can affect the ability of a business to operate normally.

Several examples from 2024 highlight why companies still see BI as a major threat to their business model. Houthi attacks in the Red Sea led to supply chain disruptions due to rerouting of container ships, while incidents such as the collapse of the Francis Scott Key Bridge in Baltimore also directly affected supply chains. Supply chain disruptions with global effects occur approximately every 1.4 years, and the trend is intensifying, according to analysis from Circular Republic. Those disruptions cause major economic damages, ranging up to 5% to 10% of product costs and additional downtime impacts.

Climate change reaches new high.

2024 is expected to have been the hottest year on record. It has also been a year of terrible natural catastrophes with extreme hurricanes and storms in North America, devastating floods in Europe and Asia and drought in Africa and South America.

After dropping down the ranking during the pandemic years, as companies had to deal with more immediate challenges, climate change moves up two positions into the top five global risks, at No. 5 in 2025, its highest-ever position, while the closely linked peril of natural catastrophes remains at No. 3, with 29%, although more respondents also picked this as a top risk year-over-year. For the fifth time in a row in 2024, insured losses surpassed $100 billion.

See also: Why Is the Cyber Insurance Market So Soft?

Geopolitics and protectionism remain on the radar.

Despite continuing geopolitical and economic uncertainty in the Middle East, Ukraine and Southeast Asia, political risks and violence drop one place to No. 9 year-over-year, albeit with the same share of respondents as 2024 (14%). But it ranks as a more concerning risk for large companies, up to No. 7, while it is also a new entry into the top 10 risks for smaller companies, at No. 10.

The fear of trade wars and protectionism is increasing, and analysis shows that within the last decade export restrictions on critical raw materials increased by a factor of five. Tariffs and protectionism may be top of the list of the new U.S. government, but on the other hand there is also the risk of a "regulatory Wild West," particularly around AI and cryptocurrencies. Meanwhile, sustainability reporting requirements will be high on the agenda in Europe in 2025.

Read the full 2025 Allianz Risk Barometer here.

It’s Time to Change How We Change

In this Future of Risk interview, Amy Radin says the traditional, top-down approach to change management no longer works. In the age of AI, she recommends the approaches revolutionaries use.

amy radin

 

amy radin

Amy Radin is a transformation strategist, a scholar-practitioner at Columbia University and an executive adviser.

As a member of the Fast Company Executive Board and author of the award-winning book, "The Change Maker's Playbook: How to Seek, Seed and Scale Innovation in Any Company," Radin regularly shares insights that help leaders reimagine their approach to organizational change. Her thought leadership draws from both her scholarly work and hands-on experience implementing transformative initiatives in complex business environments.

Previously, she held senior roles at American Express, served as chief digital officer and one of the corporate world’s first chief innovation officers at Citi and was chief marketing officer at AXA (now Equitable) in the U.S. 

Radin holds degrees from Wesleyan University and the Wharton School.


Insurance Thought Leadership

You’ve said that companies need to change the way they change. How do you approach that problem, both generally and in the context of the course you teach at Columbia?

Amy Radin

The whole premise of the course, much of which is drawn from my own lessons learned, is about moving a complex bureaucracy forward and having people accept the idea of change. For a long time, I was an operating executive on the bleeding edge of change, often in conflict or intense discussion with colleagues. In a zero-sum, fixed-resource environment, which is how most big companies operate, doing something new often is perceived as coming at the expense of something else. 

Starting in the early eighties, consulting firms built businesses around what's called change management. The eighties' idea of change management, which is still prevalent, is that change happens from the top down—incremental changes at a predictable pace, often within organizational silos, and in a command-and-control mode. Leaders plan and direct, leveraging their hierarchical authority to get things done. 

However, in today's world, with AI, robotics, advanced data analytics, and the integration of technology to enhance human creativity and problem-solving, that traditional mode of change management is no longer effective. Change will happen in organizations that can rapidly adapt and iterate, promoting engagement and collaboration across silos, and where employees are empowered rather than told what to do. Leaders need to build a culture of empowerment and participation, where the customer comes first, experimentation is promoted, and failure is treated as learning. 

The shift is from hierarchical authority, where leaders plan and direct, to a world where change is driven by the power of networks, and leaders inspire and empower belief in a vision of the future. This is something I've learned from the executives I work with in my course at Columbia and from my own experiences as an operator. Instead of just telling people what to do, which frankly doesn't work, it's about building change leadership skills, mindset, and capabilities to help employees and stakeholders navigate the integration of human-centric technologies, anticipate and pivot quickly as new challenges and opportunities arise, and provide transparent communications and a clear vision. Leveraging networks rather than hierarchical authority is key to winning support and accomplishing change. 

This approach resonates with those leading change because the work is really tough, especially with everything that's happened in the last couple of years with AI and advanced data analytics layered on top of the usual challenges of change. Old methods just don't work anymore.

Insurance Thought Leadership

I was always rather skeptical of the change management stuff, even as a partner at one of those consulting firms, because it seemed a little too packaged.

Amy Radin

You make an interesting point. One of the things I talk about in my class is that one of the worst things you can do when you want to drive transformation is get everybody together and say, "Okay, we're all going to change now." What you're doing is essentially telling the resistors in the room what they need to resist, enabling more resistance while confusing most of the other people. 

One of the books we read in my course is a best-seller called "Cascades." The author, Greg Satell, spent about 15 years in Ukraine. He was there during the Orange Revolution and became really interested in the history of social movements and how they take hold and build steam. He tells the story of how the Orange Revolution started with just a handful of guys in a coffee shop, and how they went from this small group to a couple hundred, to a few thousand, to tens of thousands in the course of a year or so. 

Greg's idea was that the lessons learned from how social movements build momentum could be replicated in the corporate world. Not that we want to promote overthrow, but rather to build momentum and scale change. It's really about starting with a small team, then finding other small teams, helping them, and building networks across all those small teams of believers, uniting them against a common purpose and vision. 

I find it fascinating. When I think back to some of my corporate experiences, it makes so much sense. We did some of that, but more because we stumbled into it by accident, not because we could label it as an effective strategy. 

If you're interested in learning more, you can search for Gene Sharp and “How to Start a Revolution” on YouTube. He worked with resistance movements all over the world to help them apply best practices of resistance. If you cross out the word "resistance" and repackage it as "transformative change" in the corporate world, it becomes very relevant. 

Based on my student evaluations, it seems this approach resonates with people in organizational settings. I've always been a fan of learning from completely different sectors. 

This is about the power of networks and starting really small, uniting people around a common purpose or vision. It's about abandoning the idea that just because you have a big title and a big budget, you're going to get people to pay attention.

Insurance Thought Leadership

I’m betting that the wave of innovation involving AI creates an environment where people are thinking more about change.

Amy Radin

That's hugely important. Too many people are approaching AI as just a way to automate and eliminate jobs. The early data is already showing that the economic value of AI and these technologies, including robotics, is much greater when viewed as tools to augment and expand human creativity. In fact, the economic value of creativity enhancement is triple the value of productivity gains from efficiency and staff reduction. Most people are missing the point by seeing AI purely as an expense reduction tool versus a means of expanding human potential with many other benefits, not just cutting costs.

I'm experiencing this firsthand while taking an online course in generative AI. Yes, it's making me more productive, but more importantly, it's expanding my thinking and capacity to imagine things, driving me toward higher order of thinking and expanded impact for my clients.

If you're approaching this as a CEO or CFO simply asking how to save money using AI and pushing that on the organization, versus thinking about how it's a tool to increase human capacity to perform and engaging employees to begin to experiment, you're missing the boat. If you want to focus on the bigger opportunity -- enhancing human performance -- by definition, you must start engaging your organization and experimenting with small pods of people who are up for doing something different.

Insurance Thought Leadership

Do you have an example from your experience in financial services about how a CEO should approach organizational change?

Amy Radin

First, you truly have to start with deeply listening to your customers and other stakeholders. Everybody says they're customer-centric, but most people aren't. You have to start with understanding who you really want to do business with and deeply listening to understand where they are and what they're looking for right now.

Then you need to identify sparks of interest, activity, or commitment within your organization to pursue solving those customer needs using new technologies. Rather than starting change with a big announcement and program, thinking it's all about communications, seed activity that helps prove what your change path should look like and empower your people to expand from that small group to other parts of the organization. It's much more about driving real collaboration versus telling people what to do.

I just started writing an article this morning on the power of asking the right questions. Rather than going into a room and presenting a new idea only to have it get shot down because everybody thinks they're the expert, what if you promoted a culture where the expert was willing to say, "Wow, that's really interesting. How did you come to that insight?"

I don't know if you can make people be more curious - much of that may be innate or cultivated through childhood. But, you can hire for this attribute. We've become so transactional that just having the conversation matters. Promoting a culture where there's actual curiosity, conversation, questioning, learning through experimentation, and accepting failure as learning - these cultural attributes are vital to transformation. People think that, through rigid control, they'll get change done faster, but you won't.

Insurance Thought Leadership

My innovation mantra for decades has been, Think Big, Start Small, Learn Fast. Tell me a bit about how you approach experimentation.

Amy Radin

You pull a few people from different departments like claims, underwriting, distribution, and put them together. Explain your vision of the future. Give them a well-defined problem to solve aligned with your vision, some time and budget, and see what they come up with, what kind of tools they need. Assess the experience, then improve upon your approach with a view toward scaling across many small teams.

When someone comes into your office and says, "I have this crazy idea," and they've got some customer insight, whether it's from a policyholder or distributor, don’t discount it. Ask, “Why don't you develop that further? Can you come back with what the next step would be to help validate your hypothesis?"

It's not about throwing a million dollars at an idea right away. Instead, it's about creating some open time, allocating a little budget for follow-up client interviews, giving permission, creating space in the organization, and encouraging people to come forward with ideas aligned to the vision.

Insurance Thought Leadership

I assume this approach should be a sort of fractal, happening not just at the top levels of an organization but at every level.

Amy Radin

It's more important to encourage the middle and lower parts of the organization to open up.

This is not about having a suggestion box or any of that nonsense. What leaders can do that's powerful is help the organization understand the vision for what we want to become. Create a framework and structure around that vision, and then you can say we want to promote experimentation to help us move and change toward it. You have to tell people where you want to go. It's about uniting people around a common sense of purpose and vision.

Insurance companies like to talk about their purpose, but it's often at such a theoretical level. You have to bring it down to the ground and help people understand what that means in claims, what that means in servicing, what that means in underwriting. Too many insurance companies treat purpose and vision as just a marketing slogan. But it's not - it's about what goes on at every level of the organization, across all functions and business units. 

You've got to frame that out to people and help make it concrete, maybe even by example, and then create some process and structure that's not heavy-handed and not hierarchical that helps people understand we think it's valuable for them to help us cultivate concepts that can move us toward our vision.

Insurance Thought Leadership

I've become a big believer in teams. When you talk about middle and lower management, one thing they can do that those in the trenches can't is to connect people. For example, if someone has an idea here and another person has an idea there, the managers can bring them together. They can mix and match, so you're not just dealing with people in finance or claims or whatever.

Amy Radin

Totally. That's why I said one of the most important roles for leaders, rather than just telling people what to do or focusing solely on reporting relationships, is to inspire and empower belief. It's about cultivating the expansion of these networks across the organization.

Insurance Thought Leadership

How do you encourage a culture that embraces failure as part of the innovation process?

Amy Radin

It's not just about saying failure is okay - you have to build that idea into your processes and how you work. When we do an experiment and don't get the ideal result, we need to talk about what happened, what we can learn from it, and how we apply those learnings to the next iteration.

Too many organizations struggle with this. I remember in one of my insurance experiences, we were trying to move more marketing activities online. We went into the market, did a test, and got a result. When we took that into a management meeting, one of the senior executives immediately said, "That's terrible!" This not only brought down the whole room's energy, but they were wrong - the result for that particular type of digital campaign was pretty good. They just weren't accustomed to seeing results for digital campaigns. And even if it was terrible, the question should have been: "Help us understand how that test was constructed, what can we learn from it, and what would the next test look like?"

There's this tendency toward a "one and done" attitude that won't work. It took Steve Jobs nine years to perfect the iPad. When a great innovation comes out, when something has its miracle moment, nobody asks how long it really took to get there, and what their struggles were.

That's the reality of how transformative change happens: iteratively, through learning from how things go in each stage of experimentation.

Insurance Thought Leadership

I love the iPad example and have written about it in some detail. The idea actually originated some 25 years before the iPad’s introduction and was embodied in a video, driven by a longtime colleague of mine, about a Knowledge Navigator in 1987. That idea kept percolating along in the labs until Jobs grabbed hold of it and, as you say, perfected it. He did another super smart thing, too. During the experimentation process, he saw that he could introduce a phone, with a smaller screen, three years before the iPad was ready. That iPhone sparked the real revolution in communication even though it wasn’t the original intent.

Amy Radin

I think there are a lot of lessons in that. Your vision is crucial, and this is where executives trained in traditional management styles often struggle. People want things to be structured in black and white, but this is not just a world of gray; it's a world of many colors, and things happen serendipitously. It's important to set a vision and understand that you're embarking on a journey where you'll explore many paths.

Setting that vision gives people permission to start down the path and avoid being incremental or sticking to current methods. Another point about why we need to change the way we change is the shift in workforce attitudes and the work environment since the pandemic. You can't just gather everyone in a meeting room, even if you wanted to.

I don't know about you, but I don't know many Gen Zers or millennials who want to be told what to do. If you want to engage today's workforce and have them do their best work, these ideas about empowerment and fostering an environment where people can pursue new ideas are crucial. If you don't offer that to your best people, they'll go elsewhere.

We have to really reframe what it means to accomplish transformational change.

Insurance Thought Leadership

Thanks so much, Amy. It’s always a pleasure.


Insurance Thought Leadership

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Insurance Thought Leadership

Insurance Thought Leadership (ITL) delivers engaging, informative articles from our global network of thought leaders and decision makers. Their insights are transforming the insurance and risk management marketplace through knowledge sharing, big ideas on a wide variety of topics, and lessons learned through real-life applications of innovative technology.

We also connect our network of authors and readers in ways that help them uncover opportunities and that lead to innovation and strategic advantage.

The Crisis in Homeowners Insurance

In theory, increasing insurance premiums signals rising risk and spurs action that mitigates disasters like California's fires. In practice, climate is changing too fast, and government is being too slow.

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House signing insurance

There is a fundamental tension underlying the wildfire disaster playing out in California, and it's not going away. The tension is between climate change and human nature, as represented both in individual behavior and in the actions of our governments.

The damage from hurricanes, severe convective storms, drought and wildfires has grown even faster than expected over the past several years, and the increases show no signs of slowing. At the same time, we keep building in areas, such as along coasts and in the wildland-urban interface, that are especially vulnerable. 

And that's just the start of our behavioral problems. We aren't wired very well for planning for crises like wildfires. You're telling me I have a 2% chance of wildfire in the 10 years I'm going to own this house, and I'm supposed to spend how many tens of thousands of dollars to harden the property? Even if the math makes sense, most people will glide past the issue.

In theory, governments step in and represent all of us on issues like wildfire that we can handle collectively better than we do individually. But governments will slow roll solutions that require hard choices. Job 1 as a politician is getting reelected, so why tick off voters by letting insurance companies raise rates rapidly or not renew policies on properties that have become too risky? Why not stall as long as possible?

So we have a crisis that's accelerating, and our response is moving at the same old, snail-like pace. I'd love to wish the tension away, but I can't. I suspect we'll be wrestling with this tension for many, many years, while wringing our hands about the devastation caused by events such as the wildfires in Southern California. 

What I can do is offer a few thoughts on how we in the insurance industry can at least start to accelerate society's response, to mitigate the damage even as climate-related problems continue to proliferate and intensify. 

To be clear, I'm not saying homeowners insurance is in crisis everywhere in the U.S. — but we're not just talking California, either. A recent congressional report said Florida, Louisiana and Texas face the same sort of climate-related insurance problems. Colorado officials have said they worry their state could fall victim to the sorts of wildfire problems that afflict California. Insurance markets in Hawaii, Massachusetts, Oklahoma, and North and South Carolina are also unstable, according to a recent report.

I'm also not saying insurers have been asleep at the switch about the growing dangers of wildfires. A New Yorker article says:

"In 2019, the number of homeowners’ policies in California that were not renewed jumped by more than thirty per cent. In 2023, two giant insurers, State Farm and Allstate, announced that they would stop writing new policies for various forms of property insurance in California. State Farm said the move came in response to inflation and 'rapidly growing catastrophe exposure.' Last summer, it canceled coverage for more than fifteen hundred homes in Pacific Palisades, the wealthy enclave where the first of the L.A. blazes began."

Seven out of the 12 insurers with the biggest market share have cut coverage in California since 2022.

What I am saying is that the tension between the acceleration of climate change and the slow response caused by human nature is overwhelming the signals that insurers are sending about increasing risks. As a result, the insurance industry isn't being as effective as it could be at heading off the economic and personal devastation of climate-related catastrophes. 

What to do?

First, once the immediate danger is behind us, insurers should take the opportunity to argue for a suite of aggressive changes to the thinking about insurance in California and other states with climate-related insurance crises. This will be difficult, both because of the normal inertia and because so many people are spreading disinformation in the interest of scoring political points. (No, whatever you think of the state's policies on water and endangered fish, they didn't affect the firefighting efforts. No, however much you despise the billionaires who have bought up so much of the water rights in the Central Valley, they didn't affect the firefighting efforts. The reservoirs in the state are full or nearly fully, as usually happens during the rainy season.)

People tend to buy flood insurance after a flood and earthquake insurance after an earthquake, so we now surely have the attention of a lot of people about the growing dangers of wildfires. Let's use it. 

California has recently made some important changes to insurance regulation. Insurers can now use predictive models when pricing home insurance, letting them account for climate change rather than having to rely solely on (outdated) historical data. Insurers can also include in filings the costs they pay for reinsurance. But those changes should just be the beginning of an acknowledgment that California's rates have been artificially depressed since voters passed Proposition 103 in 1988 and that premiums need to catch up with risk.

Second, insurers should use every means at their disposal to encourage those who are rebuilding their homes to build them to more resilient standards. Mike Zukerman, CEO of CSAA, the third-largest home insurer in California, says his company "offers guaranteed renewals to customers who achieve a Wildfire Prepared Home certification from the Insurance Institute for Business and Home Safety, which mandates home hardening measures. (There are about 1,000 such homes in the entire state, according to IBHS.)" 

Building to the higher standard costs almost nothing, so let's get as many homeowners as possible to get those certifications.

Third, I'd love to build on Zillow's recent announcement that it will provide likely insurance costs up front in its listings, so prospective buyers can crank that information into their decision-making, rather than only considering insurance once they've completed the purchase. Insurance policies are annual, so, while Zillow's approach gives a homeowner valuable information, the information is just about the first year for what's likely a 30-year mortgage. We're getting better and better all the time at projecting the effects of climate change; why not provide guidance to homeowners up front about the whole 30-year lifetime?

Yes, the information will be imprecise, models will disagree and sellers will surely push back if they feel they're being maligned, but I'm idealistic enough to think there must be a way to make buyers more sophisticated at the time they're making key decisions. 

An article in Fortune says:

"Climate science can help us figure out how to live well in a warmer world. The same models that accurately anticipated rising heat and humidity, increased drought and deluge, rising oceans, bigger tropical storms, elevated wildfire risk, and weakening jet streams warned sophisticated investors away from insuring the [long-tail risks that are geting fatter]. The same research and data can help decision-makers of all kinds integrate this information into processes as diverse as city planning, building codes, mortgage underwriting (including by FNME and FMCC), and REIT valuation."

Fourth, I hope risk management consultants can help communities stress test their plans for climate-related disasters. As far as I can tell as of this writing, the big failure of government in the California disaster was that the city of Los Angeles counted on its experienced firefighters and a system of water tanks and hydrants. The approach was fine if a house is burning down, even if several are burning at once. But a whole community? Several communities? You can't fight wildfires with a few water tanks. 

Wouldn't that be useful? Come up with a simple methodology to help communities see how they'd handle a flood, a fire, a whatever? Then help them get the word out so they can better prepare, whether through a series of individual actions or through group efforts?

Chunka Mui and I have used a stress test methodology for years with corporate consulting clients and, just based on interviewing internal teams to surface concerns, have identified any number of efforts that were as clearly misguided as hoping fire hydrants could protect against wildfires.

We've also, I'm sorry to say, seen clients go ahead and spend tens of millions of dollars anyway on those brain-dead projects. One wasted billions of dollars by moving too fast into a market that, based on our devil's advocate review, was years away from being ready.

There's that human nature again.

I warned you this won't be easy.

Cheers,

Paul

 

How to Avoid Common Strategic Execution Failures

Understanding these six common pitfalls can help organizations achieve transformative strategic success.

Avoiding Common Strategic Execution Failures

Every strategic plan starts with ambition and vision, yet most of them fail or fall short. In fact, it is estimated that 90% of strategies are not successfully executed, and only a fraction of transformations hit the mark.

We are in the early days of a technology revolution that will exceed the transformative impact of electricity, the automobile and the internet. With both traditional insurance players and tech-savvy upstarts already investing billions into modernizing the industry in recent years, the rapid pace of AI development adds additional opportunities but also creates more complexity and, for some, strategic uncertainty.

Given this environment, in a highly competitive industry with compressed margins and a bumpy track record on growth, strategic missteps in the next few years could create devastating setbacks for businesses. Now, perhaps more than at any other time in a generation, it's critical that strategies and transformative projects are thoughtfully planned and brilliantly executed.

See also: How to Respond at Inflection Points

Common Reasons for Strategic Failures

The times may be changing, but the biggest reasons for failure are evergreen. We'll break down the top six reasons, but at the heart is poor execution.

1. Lack of Clear Vision and Objectives; Misalignment With Mission

Many strategic plans and initiatives fail due to the lack of a clear, actionable vision or poorly defined objectives that do not align with the company's core competencies or market reality. For example, "We must invest in and embrace AI" is not a strategy—it is a tactic. Yet many leaders are chasing the technology, without a clear objective.

2. Underestimating and Misunderstanding Disruptive Technologies

Predicting the future isn't easy, and it shows. Most business leaders tend to overestimate the impact of technology in the short term and underestimate it over the long term. Leaders often expect new technology to fix a range of problems, but unless they plan carefully and set realistic expectations, they are just digitizing many of their problems and sometimes even amplifying them. Over the longer term, technology often disrupts even the most unlikely and insulated of businesses.

Being too quick to adopt can lead to costly disappointment, while being too slow can put you at a competitive disadvantage.

3. Resistance to Change; Poor Change Management

This frustrating obstacle appears in multiple industries and environments. There are two distinct, though closely related, issues here:

First, there is likely a segment of your company who absolutely does not want your strategy or transformative project to succeed. This may manifest simply as indifference, but there are often one or more people actively working to undermine your plans. This is usually due to either (a) fear for their job or (b) fear of or unwillingness to change.

Second, companies often undervalue the impact of good change management and simply don't do enough of it, failing not only to combat the first problem but actually compounding it. When stakeholders do not clearly understand what the plan is, why it is important, how they will be affected, and other key details, the likelihood of failure skyrockets, confusion takes hold, and morale deteriorates.

4. Misalignment of Resources

If you like delays, errors, unexpected expenses, and poor morale, misaligning resources may be one of the best ways to unintentionally sabotage your plans. This comes in a variety of flavors, including not having enough people or budget allocated, having the wrong people or skills involved, bringing resources in at the wrong time, spending money in the wrong places, doing too much at once, and not prioritizing projects and resources for maximum alignment with strategy.

Having been through many strategic plans and transformational projects, I can assure you improper resourcing will always result in a greater cost and negative impact to the company.

5. Lack of Agile Development and Inability (or Unwillingness) to Pivot

Executing a significant strategy shift or transformational project often takes years, not months. Given the fierce competition for market share and the lightning-fast pace of innovation, your strategic plans may be outdated before you've even finished launching.

Leaders who refuse to embrace agile execution will almost certainly find themselves at a competitive disadvantage and at high risk for delays, rework, or completely missing the market opportunity. Leaders must be willing and able to adjust course and adapt during the process of executing their strategy.

6. Lack of Follow-Through and Continuing Improvement

Strategic execution is rarely a one-and-done effort. Failure to complete "day two" items, monitor results, and make continuing improvements has been the death of countless "successful" projects. Too often, senior leaders are eager to move on to the next big thing or bring a premature end to the project funding in an attempt to harvest the savings. Clients don't receive the full benefits promised, shareholders don't see the profits expected, and employees bear the brunt of systems and processes that "almost" do what was intended.

See also: 5 Key Mistakes in Long-Term Planning

Case Studies

1. Early in a career, one might participate in a "paperless transition" project. It could be a significant effort involving new teams, systems, and processes. Imagine the surprise when some teams were using just as much paper as before—and some even more! The capabilities of the new imaging system were not well understood, and some users resorted to printing documents to review, highlight, and annotate. Others were simply uncomfortable or struggled with visibility on their screens.

The problem? Key stakeholders on the front lines weren't properly engaged, and the change management and training were poorly executed. The solution? Additional training and the introduction of portrait-oriented monitors. Only then did paper usage begin to drop, as the mistakes were addressed, and lessons were learned for the future.

2, During the implementation phase, a groundbreaking project delivered a smooth launch of the desired capabilities despite inadequate resourcing. However, despite millions of dollars and years of effort into the project, the resulting sales were well below expectations, and as a result, the platform's costs were unsustainable.

The problem? The original objectives weren't aligned with the mission, and the strategy had been developed in an echo chamber without sufficient input from broader stakeholders. The solution? Because key elements weren't aligned to the core mission, they were repurposed and successfully implemented elsewhere in the organization, and the initiative was closed down.

Turning Strategy Into Results

The ability to make an honest assessment of both your past results and your current situation is the first step to improving your odds of success. Based on statistics about strategic failures, it's almost certain that your organization—no matter how capable—needs improvement in one or more areas. An assessment requires more than a report from the project manager; the C-suite should actively engage with stakeholders at all levels, particularly those on the front lines, along with customers and key partners, to gain an unfiltered, well-rounded perspective.

You may not like what you find—but that's how you learn and adjust.

The challenges of strategic execution are significant, but they are not insurmountable. By addressing common pitfalls—such as misaligned objectives, resistance to change, and inadequate resourcing—you can dramatically improve your chances of success. It begins with a clear vision and actionable objectives, continues with thoughtful planning and agile execution, and demands relentless follow-through and a commitment to continuous improvement.

In a world where technological disruption is rewriting the rules, businesses must rise to the occasion. Strategies that balance ambition with adaptability, supported by strong leaders and engaged teams, can drive transformation and deliver results. The road from vision to victory is rarely straightforward, but with focus, resilience, and the right execution, it is absolutely achievable.


Matt Mylroie

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Matt Mylroie

Matt Mylroie is the founder of Peak Elevation. 

He has over two decades of experience in life insurance distribution, with an emphasis on serving the HNW and UHNW market segments.

AI Can Enhance Medical Billing Accuracy

Combining machine learning with human oversight emerges as solution for medical billing errors and fraud.

100 Us Dollar Banknotes

Despite advances in technology, medical billing errors remain alarmingly prevalent.

75% of medical bills contain coding errors, creating a ripple effect of financial inefficiencies and regulatory risks. The impact extends beyond providers and insurers: 45% of consumers encountered faulty bills last year, and many chose not to dispute them, overwhelmed by opaque rules and coverage exclusions.

This decay of trust signals an urgent need for change. Artificial intelligence and human-in-the-loop machine learning (HITL/ML) offer a path forward. By streamlining claims processing and reducing errors, these technologies can enhance accuracy and compliance, restoring transparency and confidence in the healthcare system for all stakeholders — from patients to policymakers.

See also: Using Data Science to End Surprise Billing

Financial and Regulatory Impact of Medical Billing Errors

Medical billing errors burden healthcare providers and insurers with significant financial challenges, exacerbating inefficiencies across the system. Hospitals and health systems spent $19.7 billion attempting to overturn denied claims, reflecting the immense cost of addressing billing inaccuracies.

These errors disproportionately affect higher-cost treatments, with the average denied claim tied to charges around $14,000 or more. Additionally, 15% of claims submitted to private payers are denied, including many with prior authorization. For providers, each denial represents not only lost revenue but also the added expense of multiple rounds of appeals; more than half of denied claims are eventually overturned.

Regulatory compliance adds another layer of complexity, particularly as payer policies grow more burdensome. A recent survey by the American Hospital Association revealed that 84% of hospitals reported rising costs to comply with insurer policies, with 95% noting that staff now dedicate more time to prior authorization processes. These administrative burdens increase financial strain while introducing delays in patient care, undermining trust in the system. Moreover, gaps in interagency collaboration, such as those seen between the Centers for Medicare & Medicaid Services and the Veterans Health Administration, have led to costly errors, including $128 million in duplicate payments

These challenges highlight the urgency for industry leaders to adopt solutions addressing financial and regulatory inefficiencies. AI and machine learning offer transformative potential by automating claims processing, identifying discrepancies and ensuring compliance with complex billing regulations. By leveraging these technologies, healthcare organizations can reduce costly errors, streamline operations and refocus resources on delivering high-quality patient care.

Transforming Revenue Cycles With AI and ML

Revenue Cycle Management: AI and machine learning improve data quality and accuracy, providing insights that optimize financial performance for insurers and healthcare providers. These tools analyze billing data, coding trends and reimbursement patterns, uncovering potential up-coding or down-coding scenarios and improving charge capture accuracy, ensuring providers are compensated fairly.

These insights empower healthcare organizations to make informed decisions about billing strategies and payer negotiations. By addressing inefficiencies and pinpointing areas for improvement, AI-driven analytics not only boost revenue but also enhance the overall financial stability of healthcare institutions.

AI-Driven Compliance and Risk Reduction: Compliance with complex healthcare regulations and payer guidelines is a critical challenge in medical billing. AI automates compliance-related and routine tasks — checking claim status, posting payments — by continuously updating coding guidelines, regulatory changes and reimbursement policies. It reduces the risk of errors and associated penalties, protecting organizations from costly regulatory violations. By integrating AI systems, healthcare providers can efficiently navigate intricate regulatory landscapes, maintaining operational integrity and safeguarding their reputation while optimizing financial outcomes.

Fraud, Waste and Abuse: AI identifies and prevents fraudulent activities within the healthcare revenue cycle. It detects suspicious patterns in accounts payable transactions, such as unauthorized vendor payments or schemes involving bogus claims — in some cases reaching up to $2 billion in fraudulent claims to Medicaid and Medicare. AI systems monitor for anomalies, flagging inconsistencies for review and mitigating fraud risks before they escalate. Simultaneously, AI can reduce billing errors by meticulously analyzing claims for inconsistencies or missing codes, minimizing denials and ensuring accurate reimbursements. This dual capability not only protects financial resources but also strengthens trust and transparency within the healthcare ecosystem.

Furthermore, AI can enhance the patient's experience and satisfaction. By personalizing communication and optimizing billing processes, ML algorithms can tailor payment plans to individual needs, fostering transparency and trust between patients and providers. These patient-centered improvements raise satisfaction rates.

See also: How Data & AI Can Shape Group Benefits

Ensuring Ethical AI Implementation With HITL/ML

With the growing integration of AI in medical billing, establishing comprehensive ethical frameworks and regulatory guidelines is essential to ensure fairness and equity. One significant concern is the potential for algorithmic bias, which can arise from incomplete or unrepresentative data. Inaccurate or biased outcomes in medical billing, claims processing or patient care can exacerbate existing disparities and erode trust in the system. These frameworks must address critical issues such as privacy, fairness, transparency and accountability to safeguard patient rights and promote equitable practices.

HITL/ML frameworks address this challenge by combining AI's efficiency with human oversight. Skilled professionals validate and refine AI outputs, ensuring decisions align with ethical standards and real-world nuances. This collaboration introduces a critical layer of accountability, reducing the risk of biased or incorrect outcomes. Moreover, HITL/ML systems foster transparency, allowing healthcare organizations to explain AI-driven decisions clearly.

HITL/ML frameworks also play a pivotal role in preventing AI hallucinations — instances where the AI generates inaccurate or misleading information. By incorporating human expertise into the machine learning pipeline, these frameworks enable real-time validation and correction of AI results.

Collaboration among healthcare organizations, technology developers and global regulatory bodies is crucial to creating standards that promote responsible AI use. These guidelines should mandate the protection of patient data, unbiased billing decisions and clear communication of AI processes. This openness builds patient and stakeholder trust, ensuring AI technologies are applied responsibly and equitably. This approach mitigates potential risks, reinforcing the integrity of AI-driven processes and ensuring that technological advancements benefit all stakeholders without compromising ethical standards.


John Bright

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John Bright

John T. Bright is the founder and CEO of Med Claims Compliance Corporation (MCC)

With over three decades of experience, he has driven the development of innovative medical claims processing systems, including VetPoint, CliniPoint, and RemitOne. Prior to establishing MCC in 2013, he held senior roles at Medsphere Systems and Henry Schein Medical Systems.

The Tripling of Verdict Size Post-COVID

An analysis of 11,000 P&C verdicts shows the power of granular data to make judgments fairer--shaping all the settlements that are based on those damage amounts.  

Gavel in front of judge signing papers

The property/casualty insurance litigation industry maintains the largest negotiation network in the world. Tens of thousands of insurance claim professionals partner with more than 30,000 defense attorneys to reach the most appropriate resolutions on more than 750,000 litigated claims annually. 

Because our company’s mission is to help insurance litigation defense teams be more successful, we are obsessed with data that paints a clear picture of the litigation environment in which a litigated file is being defended. 

Why? Because the litigation environment defines the true BATNA, or Best Alternative to a Negotiated Agreement. And in our world of litigation, the only BATNA available to us is taking a case to trial. 

The litigation environment is composed of many factors. The venue, the plaintiff attorney, the judge – all these entities have track records, and that information is critical to quantifying the BATNA, establishing settlement values, deciding which cases to try, and not overpaying on files. 

Doing this well yields significant short- and long-term benefit. The amounts paid on litigated files drive the case values on pre-litigated files. Given this broad impact on all negotiated settlements (the #1 expense for liability insurers), the tort litigation environment is arguably a core driver of the pricing and cost structure of the carrier itself.  

The challenge for insurers is that they only see their slice of the litigation data, commensurate with their market share, which for the average insurer is 1% or less. In contrast, our industry-wide database gives us an unprecedented understanding of the litigation environment to understand the BATNA, including how it is affected by specific venues and attorneys.

To better understand whether and how trial verdicts have changed in the post-COVID period, we analyzed 11,000 validated plaintiff tort verdicts in our database. This article summarizes our findings and discusses implications for both understanding the BATNA and trial selection at a tactical, actionable level. 

Pre- and Post-COVID Verdict Analysis - Methodology

To better understand the litigation environments in the pre- and post-COVID timeframes, we analyzed 11,000 validated plaintiff verdicts in our database, broken into three distinct periods: 

  • Pre-COVID (2015-2019)
  • COVID (2020-2021)
  • Post-COVID (2022-2023)

We examined verdict size (both including and excluding punitive damages), as well as non-economic damages award levels across these time frames. 

Our methodology included: 

  • The use of detailed actual jury verdict numbers
  • A non-economic performance assessment using a machine learning model
  • Rigorous bottoms-up analysis, controlled for inflation and other factors

The Relevance of Non-Economic Award Levels

We focus significantly on non-economic damages performance because it is one of the purest indicators, in our view, of the social inflation pressures that juries bring to bear. We all know what the economic damages are in a file; the unknown is what a jury might do with the non-economic award. 

To maximize insight into non-economic performance, we use a machine learning model, as this enables us to account for changes in injury severity, plaintiff age, and a host of other factors. Using this model also enables us to isolate venue influences from individual attorney influences, and we think defense teams are stronger when they can distinguish between those two. 

Data that shows which plaintiff attorneys are better at extracting higher non-economic awards, and which venues are more likely to give them, is critically important to understanding the BATNA on a specific case.  

Our Most Important Finding: Granularity Matters

Our most important observation from this detailed analysis is that granularity matters. A lot. 

Although we arrive at some sweeping conclusions about jury verdicts and non-economic performance in the post-COVID timeframe (see below), what stood out more for us was how granular the data needs to be to be helpful in understanding the litigation environment. 

More specifically, two things are very clear: 

  • Geography matters
  • The attorney matters

Just focusing on geography for a minute, our data shows that the most plaintiff-favorable large venue in Maryland (Prince George’s) is more favorable to the defense than the most defense-favorable large venue in the state of Connecticut (Hartford). This may be irrelevant to a litigation executive with all their files in Maryland, but it is highly relevant to an organization with litigated files in both places. 

In the same vein, but within a single state, non-economic damages performance in Los Angeles County is significantly higher than San Diego and Orange Counties. These differences suggest that thinking about the case as being “in California” may be less helpful than understanding the litigation environment in each county. 

On the plaintiff attorney front, we all know that specific attorneys are simply better at extracting high non-economic awards from juries than other attorneys. Understanding the specific verdict track records of these attorneys enables defense teams to quantify more accurately file-specific BATNAs. (As an aside, those track records can also be compared with the accomplishments that plaintiff attorneys list on their websites, which can be quite amusing). 

See also: Insurance Industry Faces Major Changes in 2025

Example – 10 Large Counties

In our analysis we examined 10 large litigious counties nationally in our database and compared their non-economic model results. 

The results emphasized for us how difficult (or at least unhelpful) it is to make sweeping generalizations about the COVID and post-COVID timeframes. 

During the actual COVID period (2020-2021) itself, more of these 10 counties went down than up. In fact, two went “way down” while one went “way up.” 

Pre-Covid/Post-Covid Comparison Chart

Key:

  • Way down = more than 40%
  • Down = between 15% and 40%
  • Neutral = within 15%
  • Up = between 15% and 40%
  • Way up = more than 40%

Our point about the granularity is that, while overall non-economic performance has increased post-COVID, that may not be relevant to you if your case is in a jurisdiction where that performance has actually decreased. 

Example – Texas and New York

Results were also mixed across counties within the same state. Texas demonstrated the most extremes. For two of the largest counties, one went way down while the other went way up. 

Other states were not so extreme. Across the three largest counties in New York, one remained neutral, one went up, and one went way down. To say that “New York as a whole has gotten worse” would be inaccurate. 

Example – Philadelphia County

Other venues have experienced dramatic changes in non-economic model performance. As an example, prior to COVID, Philadelphia County was somewhat favorable to the defense. During the pre-COVID period, this venue produced a -27% non-economic model result, meaning that it under-performed the machine learning model by 27%. 

However, in the post-COVID period, Philadelphia County is at +75% and a scary place for the defense.  

FindingsThe Post-COVID Litigation Environment

With the important caveats listed above about the need to understand the litigation environment at a very granular level, the key findings produced during our analysis included: 

Verdict Size

  • With punitive damages excluded, average verdict sizes rose 28% during COVID and rose 179% from the pre-COVID period (2015-2019) to the post-COVID period (2022-2023), nearly tripling over that timeframe.
  • Applying statistical methods to account for outliers, the values were 18% and 107%, respectively
  • When punitive damages are included in the results, average verdict sizes have risen by 12% over the COVID timeframe and have increased by 274% when compared with the pre-COVID period.  

The cause of this is mixed. From the pre-COVID to post-COVID period, there was both a rise in case severity (based on medical specials and injury severities) and a rise in non-economic damages performance 

Non-Economic Performance 

  • Average non-economic performance has increased by 37% over the COVID timeframe and has increased by 40% when compared with the pre-Covid period.
  • The state of Texas is responsible for about half of this increase. Average non-economic performance increased by a whopping 211% during COVID, only retracting slightly in the post-COVID period (2022-2023) for an overall rise of 165%. This was despite near-zero changes in medical specials or injury severity during the COVID and post-COVID periods. Again, this was not consistent across the state.
  • Excluding Texas, average non-economic performance was flat during COVID and then increased by 21% post-COVID (2022-2023).

See also: Does the P&C Insurance Cycle No Longer Exist?

Moving from broad generalizations to actionable intelligence

Historically, we have tended to speak about the litigation environment at a macro level. We are inundated with bad news stories about runaway juries and detailed reports reminding us that nuclear verdicts are a growing problem. While this information is very important for highlighting generalized social trends and setting the stage for broader societal policy reform, it is less helpful to a defense team facing a trucking lawsuit in San Diego County.  

From our vantage point, focusing only on the macro (nuclear verdicts) is having a chilling effect on our industry. We are taking fewer cases to trial, are paying more in settlements, and have been unable to diminish litigation costs. Attorney representation on pre-litigated files has skyrocketed. 

On the other side of the battlefield, the plaintiff bar is investing heavily in technology to make itself even more effective. We have written before about EvenUp Law, a company that secured more than $220 million in investment in 18 months, has achieved unicorn status, and claims thousands of plaintiff firms as their clients. The use of data that maximizes trial and settlement amounts is attractive to the plaintiff bar, to say the least. 

We believe it is time for the defense to do the same, and, in light of our findings, there is no question that the BATNAs we face across our litigation portfolios are changing.  

For us, the more relevant question is a fundamental one about how we respond as an industry. 

One option is to feel powerfulness and blame the problem on others, by saying that juries have gone crazy and the plaintiff bar is beating us. This option doesn’t accomplish much and simply becomes a self-fulfilling prophecy. We cannot think of any litigation executive with whom we interact who finds this option attractive. 

Option two is to respond to the plaintiff bar by taking a more data-driven plan of action that improves litigation outcomes. This option stems from the knowledge that a deep understanding of the litigation environment in which a case resides yields a better quantification of the true BATNA on the file. Further, it recognizes that our perception of the BATNA translates to values on pre-litigated files as well, and therefore has wide-ranging implications.

Litigation settlements involve “bargaining under the shadow of trial,” which requires an in-depth understanding of the BATNA (verdict risk), which requires an in-depth understanding of the litigation environment. As in other areas of insurance, values need to reflect risk, and to understand risk we need data.

Option two requires three things:  

  • Being highly granular in our litigation environment analysis
  • Using detailed data about venue and geographic differences
  • Leveraging a deep understanding of actual track record (instead of reputation), for both plaintiff attorneys and venues

These actions will help us to make more informed, data-driven, settlement decisions. They will help us to better understand which cases to try, and to make higher-quality decisions overall. 

Said another way, they will help us to reclaim our BATNAs. 


John Burge

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John Burge

John Burge is an engineer/attorney-turned-entrepreneur and operating executive at SigmaSight.

For the last 25 years he has led technology startups and turnarounds in the medical, insurance and litigation verticals, including managing a $400 million portfolio of medical malpractice runoff. Prior to becoming an entrepreneur, he was a product liability litigator and served in engineering roles with Upjohn and Eastman Kodak.