July 28, 2020
AI in a Post-Pandemic Future
The post-COVID-19 world requires accelerated adoption of AI to deliver the efficiencies and augmentations of a highly digitized workplace.
The COVID-19 pandemic put businesses under extreme pressure and has led to a massively accelerated digitalization of the workplace. The silver lining is the opportunity to develop more efficient, digital operating models by reinventing work and leveraging the power of artificial intelligence and automation.
Artificial intelligence and why it matters
Hype has for some time surrounded AI, but promises first made more than 60 years ago are now finally being delivered. What has been the game changer responsible for putting AI back on the map and on the verge of changing, well, just about everything? The answer is deep learning, an old idea that found an opportunity to mature in the late 1990s and early 2000s.
Based on learning tasks using artificial neural networks inspired by the biological nervous system, deep learning technology is highly advanced and requires vast volumes of data and computing power only recently made possible. By 2030, AI is estimated to contribute as much as $15 trillion to the world economy, making it the biggest commercial opportunity in today’s fast-changing economy. Indeed, the new realities of the post-COVID-19 world require the accelerated adoption of AI to deliver the efficiencies and augmentations of a highly digitized workplace.
Figure 1: AI’s projected impact on global GDP
For more than 250 years, the fundamental drivers of economic growth have been technological innovations, the most important being general-purpose technologies such as electricity and the steam engine. Now it is AI that stands out as the transformational technology of our digital age, which, as with previous GPTs (general purpose technologies), is expected to trigger waves of complementary innovations and opportunities.
What tangible opportunities does AI offer businesses right now? We are currently witnessing the first wave, usually as a result of companies automating tasks and processes, reducing costs and creating more efficiencies. The work dividends from this first wave are mostly positive. Low-level, tedious, hazardous and boring tasks are taken over by machines, freeing time for the humans to do the higher-level, more productive tasks.
Significant shifts in computing power and availability of large-scale data advance the development of AI applications that continue to rapidly grow in complexity and autonomy. AI’s autonomous nature and the way it is trained on data – essentially learning from the mistakes made in the past – make the technology both an opportunity and a risk.
See also: 4 Post-COVID-19 Trends for Insurers
AI at work
As organizations deploy technologies that automate work or introduce machine intelligence in the organization, the limiting factor in translating these innovations into real business benefits will be talent. Beyond the designers, developers and data scientists that everyone is battling for today, companies will need to explore what new roles are likely to emerge in digital disruptors.
As with many professions, underwriters have been doing a job one way for decades and now are expected to do things differently. The role is primed for transformation as AI is poised to reconfigure and augment insurance underwriting. Fueled by an explosion of data, low-cost data storage and open source technology, AI has the potential to help underwriters analyze an incredible amount of information, find red flags and help make more accurate decisions.
While there is no expectation for human underwriters to be replaced, as their judgment will still be needed for complex cases, future underwriters will be expected to work alongside AI systems to ensure all risks are accurately measured and priced. As underwriters increasingly interact with automated AI systems, there will be a need for new skill sets to develop, with some old skills potentially becoming obsolete.
Meanwhile, demand for these new skills far outstrips supply at present, which indicates that the main roadblock to insurers capturing the full value of this new technology is not the science, but the human change management factor. It is a tall order, but starting by having the right people with the right skills in the right roles will far outweigh picking the right technology, algorithm or latest start-up to work with.
More digital, more human
One of the major transformations of the digital age is to see more companies adopting a flat working structure, where career paths are less clear and the turnaround of young talent greater. In this new environment, a next-generation operating model that supports the opportunity to learn skills, to have thought leaders provide mentoring and to involve new staff in meaningful projects will be critical to attract and retain the best digital talent.
By moving beyond a one-size-fits-all approach to human resources and talent management, digital workforce platforms can help create the conditions in which employees feel energized by their work, valued by their organization and happy in their environment.
Google and Apple are examples of early adopters of digital workforce platforms that built ecosystems allowing them to innovate, take advantage of new technologies to cut costs, improve quality, build value and respond quickly to the fast-changing and rising digital expectations of consumers. How can this model be replicated across other industries?
The answer may depend on the ability of corporate leaders to restabilize the workforce — and to reconceive organizational structures — by using the very same digital technologies that have destabilized it in the first place. The incoming AI revolution should reinforce, not weaken, the uniquely human characteristics that define how we work, particularly in the way that we collaborate, communicate and develop relationships. To fully exploit emerging digital capabilities, most organizations will continue to depend on people, with human skills actually becoming more critical in the digital world, not less.
As tasks are automated, they tend to become commoditized; a “cutting edge” technology such as smartphone submission of insurance claims quickly becomes almost ubiquitous. In many contexts, therefore, competitive advantage is likely to depend even more on human capacity, on providing thoughtful advice to an investor saving for retirement or calm guidance to an insurance customer after an accident.
AI is likely to be one of the biggest game changers in insurance history, offering a wide range of opportunities from faster and more efficient claims management to a greater variety of on-demand insurance services. As organizations transform to thrive in a digital environment, their success will be affected by how well they integrate their workforce into the transformation journey and manage the tension between the constant drive to innovate and improve and the new governance, compliance and regulatory risks created by new AI technologies. Digital transformation requires the overhaul of culture beyond technology updates or process redesign to reap the anticipated benefits.