In 2023 and 2024, middle managers accounted for approximately one-third of all job cuts. Now, their one-time peers are feeling new pressure. They have staff looking to them for guidance on tasks and job functions these leaders aren't familiar with. They have senior leaders looking for progress on initiatives that only a few weeks or months ago weren't theirs to manage.

Meanwhile, these middle managers are stretched so thin that even the work they typically excel at is starting to dip in quality, productivity or both. The middle managers remaining in their roles after early retirements, layoffs and greener grass feel guilty and ill-equipped to take on the challenge. 

We don't have to stay in this state of frustration and feeling overwhelmed. There are ways to empower, prioritize and regain confidence for both the manager affected and their senior leadership.

For Senior Leaders

As senior leaders guiding departments and entire companies through these changes, your top initiatives become listening, empowering and prioritizing to support your directors and managers and see success long term.

Listen early, often and with your eyes

Listening is a critical skill for leaders. As senior leaders, we're tempted to think of ourselves and your managers listening to individuals. We sometimes forget to listen to the leaders reporting to us. Your managers need your support on a personal and professional level. In many instances, they have lost friends and confidants. You can't replace their workplace bestie, but you can empathize with the impact of this loss. Recognize, too, that after seeing valued colleagues be laid off or important roles getting absorbed, they may have a harder time coming to you with concerns. 

Let's look at an example.

One chief operating officer took a traditional approach after layoffs removed her second in command. She immediately went tactical, redistributing duties. Almost instantly, important metrics, like customer response time, began to falter. When she took a step back and listened, she realized she'd gone too fast. Back from one listening session, she shared she could see the fear on her management team's faces. Worried about making a mistake on a newly assigned task, they neglected the basics. Once she started listening fully, she met them where they were. Then she could speak to their specific concerns and work with them, leveraging what each brought to the table.

Recognize their expertise

Supporting your middle management layer does not mean micromanaging them. Often, in times of constricting budgets and personnel change, senior leaders take on an authoritative approach as they reallocate resources. Stop trying to regain control and lean into what makes your leaders great. Encourage them to get creative and use their strengths. You'll ease their strain while building their confidence as the experts they are. Your job is to set the direction; theirs is to organize the troops to get there. Remind them how much you trust them to do that work well.

In our efforts to regain control, we often get this wrong. One underwriting director was asked to take on the responsibility for a full support team while maintaining her existing department. Her boss offered to have her underwriting supervisors report to him while she learned the ins and outs of the new support team. She felt as though she was being demoted from director of underwriting to support supervisor and, with the recent cuts, was terrified to push back.

Prioritize the workload

As you and your reduced leadership team acclimate to your new normal, your standards must adapt. You can't immediately see the same progress with reduced resources. In time, your leaders will improve new skills, and their employees will become more efficient, just like all the projections showed when the organization decided to reduce staff. However, it doesn't happen overnight. So, you must be incredibly clear on what the priorities are so you can truly prioritize what needs to be done. This creates focus, results and renewed hope for what the collective team can do. Missing the need for clear priorities will cause frustration, confusion and missed goals on multiple sides.

What happens when you miss

One client had to reduce her supervisory team by 50% in 2024. She spent exactly one moment holding on to the fear of what that would mean going forward and moved into action almost immediately. She had the decisions made and logistics locked down within the first week. Then, we spent our coaching sessions focused on communication, change management and the culture of the team. She was focused on her biggest priorities, making sure her team was supported so they could carry out their work.

Her boss, however, had new goals he wanted to see progress on. He checked status on these ideas and metrics weekly. In one of our sessions, she shared that she felt micromanaged in the areas she had a proven track record of leading but didn't feel heard or supported in all the one-off projects he assigned. She was now feeling disconnected from her boss, strained with the added workload and fearful for the impact on the team members remaining with the company. Her confidence and progress started to slow because her focus was spread so thin. The following recommendations were those I gave to her to help her right the ship.

Relieve your own pressure

You have the ability to shape your new reality and make a way for yourself as a leader in the future of the organization.

Bring solutions, with a strategy

As an effective middle manager, you are still with the organization for a reason. The fear, frustration and feelings of being overwhelmed are temporary signs that you're growing and adapting. Every problem you encounter is an opportunity for you to expand. The most common issue that you'll run into right off the bat is some version of, how do we do more with less? That could be, how do we serve more customers with less staff? How do we get more efficient with fewer vendors? Many middle managers in this situation will come with complaints or legitimate reasons it won't work. A great leader comes with a clear view of the problem and a prioritized solution.

Align the values

Leading means seeing the forest and the trees. It will take some effort in this environment, but, when you're able, try to see the benefit to the organization from the changes. I don't say this to have you force a toxic positivity mindset but to consider a different lens. What is good for the organization can be good for you, too, when you take an active approach. The biggest growth and success is born in difficult situations. When oysters get a toxin inside of them, they don't remove it. We don't have oysters spitting grains of sand back in the ocean. Instead, they get to work. The oyster takes the irritant and molds it into something beautiful, something valuable, a pearl. You can do that, too, when you understand the value to the organization and align it with what you value.

Take a page from leadership experience

Prior to a latest wave of layoffs, the department I worked in went through its own reduction in staff. Some teams were realigned, some new leaders were brought in and some tenured middle managers remained on the team. With so much churn, we needed clean compliance processes to replace the tribal knowledge that was once relied on. Everyone had an opinion on how things should work. Each person had their own goals and lenses they were looking through.

I could have sat on the sidelines because it was a difficult time. I could have been distracted by office politics and aligning with the right people. Instead, I chose to focus on finding the best solution for the problem that would benefit the organization and their goals. I strategically came up with three. I explained the risks and benefits of each option, but I sold my vice president on the one I wanted to move forward with and why. Following the 1-3-1 model in decision making showcased that I had thought through the issue logically. Taking the lead meant I could position myself as someone who made things happen and fixed problems. Even in a difficult situation, I could regain control, focus on solutions and grow despite adversity by aligning the values.

You have more influence than you think, at any level of leadership. Reduce the pressure and make yourself recession-proof by building the skills and mindset you need to persevere in every situation.

Although China's insurance market started late, it expanded rapidly, benefiting from economic growth, demographic dividends, regulatory support and the internet. However, many underlying issues were masked by rapidly rising numbers. 

Traditional strategies in the insurance industry have struggled to keep pace with current challenges, particularly with the widespread use of the "funnel model" in marketing. Initially, I hoped that artificial intelligence could reduce costs and enhance conversion outcomes, but I quickly realized that technological advancement alone wasn't enough. Breaking through existing difficulties required a new marketing perspective, leading me to question the limitations of the funnel model.

When conversion rates drop, traditional remedies usually involve adding incentives or increasing channel commissions. However, with rising intermediary costs and competitive price pressures, insurance companies must sacrifice profits to stay competitive. Regardless of marketers' efforts, the traditional funnel model inevitably leads to increasing inefficiency, resulting in a predicament where "inputs exceed outputs." 

I question the effectiveness and sustainability of the funnel model and instead recommend an innovative solution — the "Echo Model," also known as the "Circular Experience Model" (CEM).

The new model focuses on a user-centered cycle, replacing the linear flow of the funnel with brand-user interactions that emphasize two-way feedback and long-term value creation. This process is iterative, involving dynamic participation (not just simplified steps), prioritizing valuable interactions (rather than low-friction steps), and establishing a two-way value chain (instead of solely focusing on high-value users).

See also: The Sales Funnel Is Obsolete

The Funnel Model and Its Three Rules

The funnel model is a widely recognized framework for user conversion, particularly in digital marketing and product design. It suggests that the more steps users must complete, the less likely they are to finish the desired task due to user fatigue and the "sunk cost" effect.

In Nir Zicherman's article, "The Law of Funnels," he expands on three key rules:

• Rule One: Minimize User Steps — The fewer steps users must complete, the fewer will drop off. Simplification must strike a balance between reducing steps and avoiding excessive clutter.
• Rule Two: Place Low-Friction Steps Before High-Friction Ones — Easier steps should be placed earlier in the flow, using the "sunk cost" effect to motivate users to complete subsequent steps.
• Rule Three: Optimize for High-Value Users, Not Just High-Conversion Users — Products should focus on converting high-potential users, not just existing high-conversion groups.

Confusions About the Funnel Model and Its Rules

The funnel model and its basic rules still hold sway among many marketing and user experience experts, who view them as vital for optimizing conversion processes. However, with the changing marketing environment, such as the emergence of short videos and WeChat for Business, consumer behavior and expectations have also significantly evolved, challenging the effectiveness of the traditional funnel model.

• Confusion One: Does WeChat for Business Defy Funnel Logic?

The funnel model suggests fewer steps lead to higher completion rates. However, WeChat for Business requires multiple interactions to convert potential customers, adding steps and potentially increasing dropout rates.

• Confusion Two: Are Low-Friction Strategies Suitable for All Scenarios?

While low friction can boost conversion rates, high-friction steps may better identify valuable users, especially in high-value products such as annuities.

• Confusion Three: Do Different Market Environments Require Different Conversion Strategies?

Different products and markets may need different approaches. For instance, a "90% * 80% * 50%" strategy may be more suitable for mass markets, while a "50% * 80% * 90%" strategy could work better for niche high-value markets.

• Confusion Four: Do Rules Two and Three Contradict Each Other?

Focusing on high-value users often requires higher initial friction, potentially conflicting with Rule Two, which advises minimizing early steps to improve conversion.

The Necessity of Reevaluating the Funnel Model

The funnel model and its derived rules are fundamentally oriented toward the company, rather than the user. This perspective is increasingly inadequate in today's market, where consumers demand deeper engagement and respect in the buying process, beyond simplified processes. A new model that embraces continuous interactions, feedback and dynamic adjustment — not just a linear funnel — is needed to meet modern consumer expectations.

• Step One: Break Away From the Funnel Model 

The Echo Model replaces the linear funnel with a dynamic, multi-touchpoint cycle, viewing users as long-term experience partners. Companies continuously interact with users in diverse contexts, ensuring each interaction adds value and provides an opportunity for users to participate in the company's services.

• Step Two: Rewrite the Rules — Driven by User Needs and Dynamic Flywheels
  • New Rule One: Dynamic Participation Instead of Fewer Steps — Instead of merely reducing steps, companies should make each step valuable, encouraging users to engage meaningfully.
  • New Rule Two: Prioritize Valuable Interactions Over Low-Friction Steps — The goal isn't simply to minimize friction but to foster meaningful engagements that demonstrate product value.
  • New Rule Three: Establish a Two-Way Value Chain — Focus on building mutually beneficial relationships, considering how each interaction can add value for the user, regardless of their profitability.

The Assistance and Resistance of the Echo Model

The Echo Model benefits significantly from advancements in AI technology, which plays a crucial role in enabling a more personalized, dynamic and adaptive marketing approach. AI empowers companies to continuously adjust and optimize interactions based on real-time data, ensuring each interaction is personalized and meaningful for the user. Below, we explore both the supporting factors and challenges in implementing the Echo Model.

See also: Transforming Insurance Operations With AI

Assistance From AI

1. Personalization and Dynamic Adaptation: AI allows brands to dynamically personalize interactions by analyzing user behavior and preferences in real time. This continuous adaptation not only enhances the user experience but also fosters deeper engagement. Instead of following a rigid, one-size-fits-all funnel, AI-driven insights can recommend products or services tailored to an individual user's needs and interests, making each touchpoint valuable.

2. Proactive User Engagement: AI-driven chatbots and recommendation engines can proactively engage users at different stages of their journey. By understanding when and how to reach out to users, brands can create a more seamless experience that guides users without overwhelming them. This helps reduce drop-off rates and keeps users engaged through intelligent prompts and valuable content.

3. Enhanced Feedback Loop: The Echo Model thrives on continuous feedback, which AI can facilitate effectively. By collecting data from user interactions, companies can rapidly iterate and improve their offerings. AI can identify patterns in user behavior, providing actionable insights that allow brands to adjust their strategies in real time. This iterative process strengthens brand-user relationships, emphasizing a user-centric approach.

4. Multi-Channel Integration: The Echo Model involves engaging users across multiple touchpoints. AI helps manage and unify these interactions across channels — such as social media, email and chat — creating a coherent and consistent experience. Users benefit from a holistic approach where each interaction feels connected, regardless of the platform or medium.

The above picture is a schematic diagram of an AI intelligent and automated WeChat for Business operation, which supports the realization of a marketing innovation business model of two-stage sales and online-to-offline integration.

Resistance and Challenges

1. Data Quality and Management: Implementing the Echo Model requires high-quality data for personalization and decision-making. Many companies face challenges related to data fragmentation, data silos and low data quality, which can hinder AI's ability to deliver meaningful insights. Effective data integration across departments and platforms is critical for overcoming these barriers.

2. Organizational Structure and Culture: The Echo Model necessitates a shift from traditional, linear workflows to more collaborative, cross-functional teams. Departments such as marketing, product, customer service and IT need to work in synergy to deliver a consistent user experience. This requires breaking down organizational silos and fostering a culture of collaboration, which can be challenging in large, traditional organizations resistant to change.

3. Balancing Personalization With Privacy: While personalization is at the core of the Echo Model, it raises concerns about user privacy and data security. Users today are more conscious of how their data is used, and brands must navigate the fine line between delivering personalized experiences and respecting user privacy. Transparent data practices and strong privacy safeguards are essential to gain and maintain user trust.

4. Technical and Implementation Complexity: Deploying AI-driven solutions requires significant technical expertise and investment. Companies may face hurdles related to integrating AI technologies with existing systems, developing accurate predictive models and maintaining them. Furthermore, AI algorithms must be trained to avoid biases and inaccuracies that could damage the user experience. These technical challenges demand resources, both in terms of financial investment and skilled personnel.

5. Managing User Expectations: Modern consumers have high expectations when it comes to personalized experiences. If an AI-driven interaction falls short — whether due to inaccurate recommendations, delayed responses or inconsistent experiences — it can lead to user dissatisfaction. Brands must carefully manage these expectations and ensure that the AI systems in place are well-calibrated to provide consistent value.

Despite these challenges, the Echo Model, supported by AI, represents a transformative shift toward a more adaptive, user-centric approach to marketing and customer engagement. By addressing the barriers effectively, companies can leverage the full potential of the Echo Model to foster deeper, more meaningful relationships with their users.

See also: Which Insurance Model Will Dominate?

Funnel Model No Longer Meets Needs of Digital Users

The evolution of digital marketing has fundamentally changed how consumers interact with brands. The linear, one-way funnel model is increasingly outdated in an environment where users seek deeper, continuing relationships with brands. The Echo Model's emphasis on continuous interaction and dynamic feedback provides a sustainable approach, breaking away from the rigid funnel structure. It fosters enduring relationships and genuine value exchanges, better suiting the expectations of today's empowered consumers.

The Echo Model, with its focus on dynamic engagement, continuous optimization and value creation, holds greater potential for helping companies maintain their competitive edge in a rapidly changing market.

Lots of questions are flying around. Are "tech bros" taking over the White House? Why do we need more “masculine energy,” and what does that even mean? What else can we expect from the White House and the U.S. more generally?

As Trump settles into his presidency, it’s useful to take a look at what he might mean for insurance, and why dealing with uncertainty is the industry's untapped superpower.

People are referring to Trump 2.0, and for good reason. Having Elon, Mark and Jeff sit together at the inauguration signals that tech will feature strongly in Trump's second term. 

We have also seen the rallying cries across fintech generally and niche areas such as cryptocurrencies. The view is that Trump favors these sectors and is likely to reduce regulation, perhaps even establishing more favorable tax regimens for them.

Leo Schwartz, writing in Fortune, sees the balance of power shifting from banks to Silicon Valley. You could argue that fintech is a tech investment, but I’m inclined to believe the momentum will increasingly favor technology companies themselves, rather than those simply leveraging technology to disrupt other markets.

For insurance, we are already seeing traction in the U.S. due to more dynamic and growing financial markets. Only recently, Aspen Insurance Group decided to stick with New York as its preferred venue for an initial public offering. That's a blow to London, for sure, having a Lloyd’s insurer snub London for a U.S. listing. But one can entirely understand why, despite being engaged with the London markets, the company would choose to float in a more dynamic and growing financial market.

All in all, we will see a degree of volatility that isn't straightforward for any financial services business, including insurance. In addition, we will see the global economic and competitive landscape changing, in turn affecting inflation and interest rates to varying degrees.

See also: What Trump 2.0 Means for Climate Initiatives

Things driving this include:

• The president’s focus will drive investment into different areas of industry
• Global markets will change, and supply chains are likely to be disrupted by foreign policy changes
• More U.S. domestic focus will reduce the U.S.'s own interests in investing overseas, but it could be good for the global economy anyway
• We are already seeing sustainability stocks struggle, and other markets are similarly feeling the strain in areas like energy policy

I therefore think that coming out of Trump 2.0 will be a more stress tested insurtech and fintech market, which will have access to a much stronger advanced technologies market. And all of this will be centered on an even more attractive U.S. market in the short term.

As always, insurers need to be highly adaptive, able to adjust to geopolitics, economics and societal changes like never before. Selective growth will be key, as will keeping a keen eye on profitability and the quickest path to it.

This adaptability is the untapped superpower of the industry. 

See also: Insurance Industry Faces Major Changes in 2025

Blessed with the need to assess risk in the context of macro-environmental changes, insurance is uniquely capable of tuning into data (real-time) and using its actuarial muscle to make core changes. 

However, this ability to use data, make predictions and adapt isn’t used to the same effect across the entire insurance business. We often see just little changes in customer communications and empathy, and the industry's efforts to proliferate and manage a deepening ecosystem of suppliers can get bogged down in a lot of mainframe integrations and code. 

Even the industry's use of connected things and the data that binds them altogether, are all too often point solutions with little to no dynamism. 

Yet this could change. Insurance could use its ability to act on risk, near-real-time, to be better at putting its adaptive power in the hands of its customers.

For some time now, many have observed the industry at a protracted tipping point, with consumer markets overly dependent on price, with corporate insurance being slow to get to risk mitigation models, and so on. 

Trump 2.0 should be used as an impetus to raise the industry's profile. The recent California fires alone represent enough economic reasons for a bigger conversation between insurers and the White House. 

By embracing wholesale changes to enterprise design -- centering operations on customers, leveraging AI to intelligently orchestrate customer relationships and supplier networks, and adopting innovative business models such as embedded, risk-mitigating, and adaptive strategies -- the industry can amplify its role as a growth engine for the global economy.

Trump 2.0 isn’t as interesting to me as Insurance 2.0, but the two could be symbiotic. Either way, insurance will need to adapt and use this as an opportunity to progress into a redefined era. 

Organizations today generate, store, process, and manage more data than ever before. Data is the backbone of the modern organization. As the volume of on-premises and cloud data continues to skyrocket, the challenges of protecting it also rise. 

Data needing protection can be broadly classified as structured and unstructured data, and each has its own set of security requirements. 

Structured Vs. Unstructured Data

Structured data is highly organized, easily searchable, and often stored in databases. This data type follows a specific structured format, such as rows and columns in a database. Customer information, transaction records, and inventory data are all examples of structured data, and it is easier to manage and analyze than unstructured data due to its predefined structure. 

Unstructured data lacks a specific format, schema or structure, making it harder to identify and more challenging to analyze, store, and manage than structured data. Unstructured data includes emails, message text, attachments, metadata, and communication threads. Unstructured data also includes text found in Word documents, PDFs, or plain text files containing unorganized information, such as articles, reports, and contracts. In addition, multimedia files including images, videos and audio files often contain vast amounts of information without a consistent format to protect. Social media posts are another class of unstructured data, including text, image, video, and metadata content from platforms such as LinkedIn, Twitter, TikTok, Facebook, and Instagram. 

See also: The Role of Data Cleansing in Insurance

Unstructured Data Characteristics 

The traits of unstructured data can be characterized by four “V” words. First there is volume, as unstructured data is exponentially growing due to digital communication, internet-connected devices and social media. Next, the variety of unstructured data takes on numerous formats and types, making it difficult to manage and analyze. The rapid generation and sharing velocity of this data cause significant storage, processing, and security challenges. Finally, the veracity of unstructured data, with its varying quality and accuracy, requires investment in validation and cleanup. 

Risks and Challenges of Protecting Unstructured Data  

Some of the main risks and challenges associated with unstructured data include: 

• Data breaches – Unprotected or poorly managed unstructured data is vulnerable to cyber-attacks, which can result in data breaches and unauthorized disclosure of sensitive information. The lack of a consistent structure makes it difficult to apply uniform security measures to avoid these breaches.
• Compliance issues and risks – Compliance with data protection regulations, such as GDPR and CCPA, requires proper management, protection and auditing of unstructured data, including personal data.
• Storage and management concerns – The sheer volume and variety of unstructured data can tax an organization’s resources, requiring adequate storage, processing power, and efficient secure management practices.
• Identification and categorization challenges – Identifying and classifying sensitive unstructured data is difficult, labor-intensive and time-consuming. 
• Limited access controls – Unstructured data often has minimal or inconsistent access controls, significantly increasing the risk of unauthorized access.   

Due to many of the challenges discussed, unstructured data has become an attractive target for cybercriminals. Given the importance and potential risks associated with unstructured data, it is critical for organizations to invest in effective strategies and solutions to safeguard it. 

Unstructured Data Protection Strategies  

Whether data is structured or unstructured, there are three key components to a successful protection strategy – identifying the data, classifying it, and remediating the risk. 

Organizations need to be able to identify sources of unstructured data and classify and categorize them based on sensitivity. To reduce risk, organizations need to use role-based access controls and the 'least privilege access' principles (for example, zero trust) to limit access to sensitive data. To protect data from unauthorized access, organizations should encrypt data in transit and at rest. And regularly monitoring and reviewing access logs and addressing suspicious activities help improve data security hygiene. 

The best solutions for protecting unstructured data leverage AI and machine learning. AI-driven data classification speeds the process and accuracy of identifying and categorizing sensitive data, while AI-powered threat prevention and anomaly detection tools can detect and prevent threats in real time, reducing the risk of data loss. In addition, machine learning algorithms are equipped to analyze user behavior and suggest appropriate access controls. 

See also: Top 10 Challenges for Data Security

Protecting Both Types of Data with DSPM

To achieve comprehensive data protection across the board, organizations must adopt a unified approach that covers both structured and unstructured data. Effective data protection solutions should provide a holistic view of all data types, enabling organizations to implement consistent security policies and practices across their entire data landscape. 

One popular, proven approach to this challenge is advanced data security posture management (DSPM). DSPM empowers organizations to discover structured and unstructured data and gain comprehensive visibility into where sensitive data resides and the types of sensitive data that exist. It also classifies data by tagging and labeling it. In addition, DSPM monitors and identifies risks by detecting and assessing behavior and usage of business-critical data, preventing potential breaches before they occur. Finally, DSPM remediates and protects sensitive information against unauthorized access and data loss. 

With DSPM, as sensitive structured and unstructured data moves through the network and across data stores, it is labeled appropriately no matter where it resides. It is then monitored for risks, such as inappropriate permissions, risky sharing, inaccurate entitlements, and wrong location. If any risks are detected, they can be remediated. 

Understanding the differences between structured and unstructured data is crucial for implementing effective holistic data protection strategies. Organizations must recognize the unique challenges posed by unstructured data and adopt advanced solutions, such as advanced DSPM, that leverage AI and machine learning to safeguard all types of data. By doing so, they can mitigate risks, ensure compliance, and derive valuable insights to drive growth and innovation.  

Insurance Thought Leadership

I'm interested in the report you did on M&A, especially the part on agencies and brokerages. Could you outline the basic outlook for this year?

Mark Friedman

I'm glad you're focusing on agents and brokers, because that’s a lot more straightforward than other parts of the industry, and that’s where most of the activity is. The theme broadly in P&C deals is that 2025 is going to be a year of rebound – though we’ve already been at pretty elevated levels with insurance brokerages, both in terms of deal volumes and deal values. 

Insurance brokerage distribution remains a really stable business, generating predictable cash flow and requiring little working capital, which is why private equity loves it. They're reminded of those qualities in down markets, where other more cyclical businesses have stresses on their business model, be they luxury goods, restaurants, or hospitality. Other sectors are a lot more cyclical, whereas insurance is only really affected by two macroeconomic factors: employment and housing. When you employ people, there's a lot of coverage, and with housing comes a lot of insurance. 

We haven't really seen a significant jump in unemployment. We have seen economic growth slow, but as a result of inflation over the last couple years insurance rates have gone up quite a bit. So brokers are not only retaining their business, but because premium rates are largely rising, we're actually seeing significant growth. 

In 2024, we saw a number of corporate buyers do sizable acquisitions, and at the beginning of 2025 we're starting to see that, as well. That is a function of interest rates. With interest rates having come down by about 100 basis points over the course of 2024, we're definitely seeing a lot more interest on the part of private equity.

Separately, but very much related, there is a backlog of exits. There are a lot of these broker platforms that have grown exponentially through consolidation over the last couple of years, owned by private equity. Their time is coming due for an exit, and there's no lack of buyer demand. 

Valuations are going to remain high, and we expect to see volumes continue. We're just into the new year, and we've already seen a number of pretty sizable transactions announced. It's already a very active market in 2025.

Insurance Thought Leadership

Do you think the new administration will reduce the focus on antitrust issues?

Mark Friedman

It could be. But I would say the impact is marginal, because most of the deals that are getting done are not ones that would otherwise have been challenged. We saw a lot of mega deals in 2021 under the old administration that were not challenged. So while a business-friendly administration is definitely very helpful, I don't think we're going to see floodgates open. 

The change does add to the competitive dynamics on the buy side, where some of those larger players that were maybe a bit worried that a sizable deal may get scrutiny from an antitrust perspective will have more confidence. They'll be more inclined to jump in and be willing to buy.

Insurance Thought Leadership

For some years now, agencies and brokerages have had to invest more in technology, and larger companies can do this more effectively. With the recent burst of AI activity, is the need for technological progress a factor in the elevated M&A activity, as well?

Mark Friedman

Yes, but there are two factors at play here. The brokers that have done a nice job streamlining operations and integrating their businesses, particularly their acquisitions, are definitely seeing better margins, more efficient businesses, more profitable businesses, and they get higher valuations. But as folks in this industry are well aware, you can't really upset the apple cart too much. Integration is good, but you can't buy a brokerage and just tell them they're going to start writing business very differently. You're not going to change how they interact with people. They're fussy about how they do business. So there’s a fine balance. 

To get to your point about AI, there's a lot of opportunity for revenue synergies and cross-selling opportunities if brokers do a better job leveraging their data. That is going to be the next big differentiator, and scale matters. You get better commission rates if you've got better volumes, so that does have some impact. But a lot of brokers already have that and are getting the top-tier overrides. 

Those that are able to leverage AI will have an advantage -- and we are seeing some products come to market already where some of these large AI platforms are focused on it because they see the opportunity in the brokerage space. There's AI being leveraged in underwriting and claims, but as it relates to brokers, I think the single biggest opportunity is harnessing the data they have and the ability to leverage that data to identify new opportunities for revenue.

Insurance Thought Leadership

In a conversation about M&A a few years ago, I was told that, despite a lot of activity, the number of agents and brokers has remained stable. New businesses form as old ones are consolidated. Are you seeing a similar trend, or is there an absolute consolidation happening in the industry?

Mark Friedman

It's an interesting perspective. The average age of an insurance broker in the U.S. continues to creep up, but we’re seeing them consolidating under umbrellas. What we're also seeing, in terms of startups, is a lot more activity on the wholesale side, meaning MGAs and MGUs. 

If you look at the insurance industry as a whole, it is largely a zero-sum game, meaning you're not going to find under-penetrated markets in the U.S. If you go out to India, for example, various statistics suggest that 70% of India is not banked or insured, so you've got massive opportunity for organic growth in the insurance sector there. There are new products in the U.S. market. For example, rep and warranty insurance was 10% penetrated 10 years ago; it's now somewhere between 60% and 80% penetrated. Cyber insurance is another real growth area. On the flip side, there are areas that are no longer as necessary or popular, like financial guaranty insurance. 

In general, there is natural growth. There's growth in premium rates, but volume growth is in single digits. What is changing in the P&C space is that we used to have one-stop shops where insurance companies wrote every product. We're seeing a lot more insurance companies looking at their portfolios and saying, "We haven't figured out how to write this stuff profitably. We're going to exit." When they exit, they're either going to stop writing completely, or they're going to outsource the underwriting. They're going to have MGAs that are just focused on this specific product, and they'll hand the pen to them. 

We are seeing a significant number of MGAs pop up. This is just a shift from traditional brokers to MGAs or MGUs. There may be two brokers involved because you may have a referring broker. A lot of the large guys don't have the MGAs, though they'll leverage them. So it's the same policy, it's just being underwritten differently. But with MGAs comes a need for fronting carriers and reinsurance brokerage. 

There is definitely a changing mix in how the business is written, and that's having an impact on brokers. For example, most of the large brokers are focused on growing their MGA platforms because they see MGAs as a threat to the traditional brokerage model.

Insurance Thought Leadership

Are there any other trends you are observing in the marketplace that might interest agents and brokers?

Mark Friedman

People frequently ask about online, direct-to-consumer models, but no one has quite figured out how to make that work economically. The customer acquisition cost is right in line with any insurance company that uses agency distribution. 

That said, technology evolves. As insured consumers become more technologically and digitally sophisticated, we could start to see more of a shift toward digital brokerage platforms or direct-to-consumer digital marketing. But what’s happening is similar to banking -- despite predictions that brick-and-mortar banking would disappear, you still see banks opening branches. The same applies to the brokerage space. Most insurance is still very much a broker-consumer relationship.

Insurance Thought Leadership

Thanks so much, Mark.

About Mark Friedman

Mark Friedman leads PwC's Insurance deals practice in the US. He specializes in a broad range of deal-related services including buy-side due diligence, divestiture support, and transaction structuring advice. In addition to leading due diligence teams, Friedman provides assistance in the drafting and negotiating of sale and purchase agreements and assists with developing positions related to post-closing purchase price adjustment disputes. Friedman has more than 19 years of experience in the insurance industry during which he has been focused on serving US and Global insurance and reinsurance companies as well as several large private equity clients with transactions in the life and annuity, health, and property & casualty insurance sectors. He also has extensive experience supporting clients with transactions involving insurance brokers, agencies, TPAs, MGAs and MGUs. Mark earned his bachelor of science in accounting from Touro College and is a Certified Public Accountant licensed in the State of New York.

Munich Re’s global medical team recently collaborated on a wide-ranging thought leadership project intended to help life insurers better understand and navigate the most prevalent emerging medical trends and risks across five critical topics: AI in Healthcare, Improving Cancer Outcomes, Prevention, Obesity, and Climate Change. The first chapter, AI in Healthcare, is now live. It covers how AI will enhance healthcare through advancements in disease prevention, diagnosis, and treatment, with profound impacts on life and health insurance. These advancements in AI technology promise to improve mortality and morbidity, reshaping the future of life and health insurance.

Key Insights:

• Improved Mortality & Morbidity: AI will drive improvements in mortality and morbidity for many medical conditions through better prevention, earlier diagnoses, and individualized therapies. This will expand insurability.
• Disease Prevention: Major progress in disease prevention is anticipated, offering opportunities for insurers to enrich insured-lives portfolios and innovate product offerings.
• Underwriting & Risk Selection: The analysis of vast datasets from electronic health records (EHRs), imaging, and other biomedical sources will provide a rich resource for risk selection, enabling more accurate and sophisticated underwriting.
• Critical Illness: Critical illness products will need constant updating as earlier diagnosis and new disease classifications emerge. Antiselection may become problematic, as may overdiagnosis.
• Complex Claims Management: As disease understanding shifts towards genetic and molecular diagnoses, claims management will become more complex. Insurers will need cutting-edge medical expertise for claims analysis and dispute resolution.

Bookmark our Life Science Report landing page to access all chapters and to sign up for our newsletter so you are alerted when the subsequent chapters on Improving Cancer Outcomes, Prevention, Obesity, and Climate Change are released. 

Sponsored by ITL Partner: Munich Re

I recently got a look at the sweep of AI's progress through a fascinating book, "The MANIAC." It's a fictionalized oral history of the life of John von Neumann, a pioneer in mathematics, physics, computer science and more. He died young, in 1957, less than a year after the term "artificial intelligence" was coined, but the book carries his legacy through to today as a spark for DeepMind. 

The AI company, founded in 2010 and now owned by Google, made a splash in 2016 when it dominated a match against the world's best player at Go, a game considered to be much harder for computers than, say, chess. DeepMind has since moved on to far more serious matters; two of its founders won the Nobel Prize in Chemistry in 2024 for a breakthrough in understanding how proteins fold, an issue that has massive implications for developing drugs to treat disease.

Much of the progress can be traced to the mind-boggling improvements in computer hardware — von Neumann's massive computer, known as the MANIAC, had all of five kilobytes of memory, while you may have 200 million times that amount just in your phone. The progress also obviously stems from the big brains, such as those at DeepMind, who've made AI their life's work. And the progress will continue at a furious pace, both because the computational capacity available to AI is doubling every three or four months and because AI has become perhaps the great intellectual challenge of our time. 

But as much as I enjoy reading about intellectual titans like von Neumann and marvel at the sweep of history, the key question is: What are we humans doing with all this power that's being given to us?    

Which brings me to a recent Harvard Business Review article that shows how companies really sank their teeth into generative AI last year and lays out where they can go from here in 2025.

The article, based on a survey of C-suite executives from 125 companies that the author has been conducting since 2012, opens with a bleak statistic that is all too familiar to those in the insurance industry: Just 37% of companies reported that efforts to improve data quality had succeeded. 

But the article continues: "This year’s survey findings suggest that we are experiencing a once-in-a-generation transformational moment, akin to the founding of the internet in the 1990s.... 89% [report] that AI is expected to be the most transformational technology in a generation, up from 64% in last year’s survey."

The report describes six major changes in 2024, four of which I'll highlight here:

• 98% of organizations said they were increasing investments in AI and data, up from 82% last year.
• "94% report that... they are seeing quantifiable business results, which can be measured by metrics including increased customer acquisition and retention, improved customer satisfaction, and revenue and productivity improvements.... 18% report a high level of measurable business value, and 28% report rapidly increasing business value. Another 32% see a modest but rapidly growing level of business value based on these quantifiable metrics.... The source of this value is significant: 75% see it as coming from productivity gain and customer service improvement, notably through efficiencies resulting from the application of generative AI into traditional production processes."
• "Organizational transformation due to AI is seen as steady, but gradual. Most organizations characterize their AI efforts to be at an early stage, with 76% in experimentation, testing, and limited production. But... 24% reported implementing AI in production at scale this year, up from just 4.9% last year.... 91% of organizations report the greatest barriers to business transformation are due to cultural factors, not technology."
• While many companies are now appointing chief AI officers, "51% report that the AI and data leadership roles are not well understood within their organizations," and turnover is high. On the flip side, 36% of AI and data leaders "now report to the most senior business leadership of their organization," and the "AI and data leadership roles are now focused on business innovation, business growth, and business transformation efforts," not just on the technology.

A one-year snapshot isn't nearly as impressive as the 80-year sweep in "The MANIAC," but the HBR article still describes an awful lot of progress for one year, and 2025 is just getting going.

Cheers,

Paul

P.S. Von Neumann is a fascinating character, with an intellect that was intimidating, even scary. When he was three years old, growing up in Budapest, his parents would entertain guests by having them pick a page in the phone book. They'd show it to Johnny for a minute, then ask him anything. Who has this phone number? What is the phone number associated with this address? What is the address of this person? The question didn't matter. Little Johnny had the page memorized. "The MANIAC" describes a situation where a prominent mathematician told a class of students at maybe the world's preeminent technical high school that he wanted them to think about an unsolved problem that the mathematician had been wrestling with for years. As the students started to talk, 14-year-old von Neumann went silent. After about three minutes, he raised his hand, went to the board, and wrote down the answer. 

Von Neumann gave us game theory, was one of the founders of operations research (which is how UPS and Fedex come close to optimizing how they handle all the packages they accept and deliver every day), laid out the mathematical foundations for quantum mechanics, figured out how in the 1940s computers could go beyond being hard-wired for every problem and could use "stored programs" (what we now call software) and much, much more. When he was dying of cancer, likely due to radiation he absorbed while working on the Manhattan Project (where he developed the implosion model used in the second atomic bomb), the Department of Defense surrounded his hospital room with security, lest he blurt out any of the numerous secrets he knew during his frequent bouts of delirium. 

He also, according to "The MANIAC" and other books I've read about him, had no particular moral compass, unlike Robert Oppenheimer, the leader of the Manhattan Project.  Von Neumann was just fascinated by the problem. He was the model for the main Peter Sellers character in "Dr. Strangelove." 

Von Neumann was the prime example of the two sides of technology, the potential for almost magical progress and the simultaneous prospect of unintentional, dangerous consequences. 

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.

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.

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.