The age of autonomous technologies in insurance: separating myth from reality

Depending on where you live, self-driving cars and autonomous taxis may already be a familiar sight; for others, they are coming soon to a city near you. Globally, it is estimated that over 1 million robotaxi rides with no safety driver are being completed each month.  Adoption of this technology is already rapidly increasing in multiple US cities with new launches and partnerships being announced regularly.¹

Agentic AI is poised for similar exponential growth. Gartner predicts that it will feature in 33% of enterprise software applications — a huge leap from less than 1% in 2024 — and autonomously handle up to 15% of everyday work decisions.² As AI agents learn to handle more complex tasks, adoption will only accelerate. The most forward-thinking insurers are already using GenAI to improve operations, from customer service to claims processing.

The AI revolution extends beyond software, as physical robots are increasingly common in manufacturing and warehouse environments, with food delivery robots in use in cities across the globe. According to Citi, the global AI robot market could reach 1.3 billion units by 2035 and 4 billion by 2050.³ Tesla plans to ramp up production to 50,000–100,000 units in the next year.⁴ Health care, food service and hospitality, transportation and construction will be early adopters, as next-generation humanoid robots can help solve labor shortages. Research from Citi estimates that the payback cycle for deploying robots in some roles, such as nursing, could be as brief as one month. Major Silicon Valley tech companies, including NVIDIA, are investing heavily in AI to power advanced humanoid robots engineered by firms such as Figure AI.⁵ This strategic move is expected to accelerate the development and adoption of these technologies across multiple sectors.

Even if these forecasts are only partially accurate, they signal an inevitable shift. While insurers don’t need to prioritize first-generation use cases immediately, they should start planning for the advancements and adoption expected over the next three to five years.

While AI investments are often justified by lower labor costs, larger-scale workforce reductions have yet to materialize. Both software AI (i.e., agents) and physical AI (i.e., robots) still have a need for supervision, with skilled humans applying technical and functional knowledge in decision-making processes.

Labor cost savings and operational efficiency gains represent significant opportunities but are just one element of a broader value proposition. Market-facing innovations — particularly new products and services — hold even greater long-term potential. These innovations will be critical, as EY analysis projects that auto premiums could decline by 30%–50% in the coming decades due to autonomous vehicles drastically reducing accidents and transforming mobility patterns.

Consider how consumer AI agents, soon to be commercially available from major technology platforms, will enable new engagement models. First-generation agents will manage comparison shopping, purchase completion and administrative changes (e.g., policy renewals, address updates, adding insureds). More importantly, individual customer experiences will be personalized through deeper context and enhanced memory about specific risks that will result in more precise coverages and tailored services.

When integrated with real-time underwriting and dynamic pricing capabilities, agentic AI can help insurers realize the vision of fully data-driven and tech-enabled operations. This goal requires multi-agent systems (MAS) working within integrated ecosystems that automate complex, data-driven tasks across functional silos – an evolution from today’s largely vertical use cases.

AI undeniably gives bad actors more tools, while autonomous vehicles and robots increase the attack surface. However, AI can also strengthen cyber defenses via more sophisticated threat monitoring, detection and response capabilities. Rather than letting security concerns paralyze progress, insurers should integrate robust protection measures into their strategic plans for autonomous technologies.

Similarly, regulatory ambiguity should not justify inaction. Organizations that delay adoption risk ceding ground to competitors and new market entrants that are already leveraging these technologies to reshape insurance offerings. As the industry learned from GenAI deployments, strategic plans must remain flexible enough to adapt to evolving standards.

Proactively addressing security concerns enables insurers to drive more innovation. Real-time data feeds from connected devices enables dynamic premium pricing that reflects actual risk exposure and helps large fleet operators optimize safety protocols. Partnerships with automotive OEMs can drive growth in embedded insurance via mobility subscriptions. As smart, connected homes become more prevalent, property insurance offerings will get smarter by incorporating AI agents that actively identify risks and take steps to prevent claims.

Insurers must strategically expand their technology budgets to harness next-generation tools. Gartner estimates an average increase of 3.7% in 2025, with AI, GenAI and cloud platforms being the focal points.⁶ Early investments in foundational infrastructures and capabilities are laying the groundwork for breakthrough returns on frontier technology investments.

According to Source Advisors, many insurers, along with their peers in financial services, have increased R&D technology investments in the last few years,⁷  enabling a shift from maintenance of costly legacy services — which by some estimates consumes well over half of insurers’ IT budgets — to more innovative pursuits. In fact, Gartner research shows that a full 40% of insurers predict decreases in their legacy infrastructure and data center investments in 2025.⁸

Technology partners are making autonomous solutions more accessible than ever. Leading platforms and InsurTechs offer both consumer-facing solutions and enterprise-ready options that fit any carrier's scale. Cloud-based AI and SaaS models enable cost-effective adoption of agentic AI, while insurance-specific language models (both LLMs and SLMs) are maturing rapidly. This enables carriers to blend external innovations with internal capabilities, following the successful pattern they established in digitizing underwriting and claims processes.

The insurance industry has historically been viewed as a technology laggard, but recent advancements challenge that perception. Machine learning and AI have become fundamental to risk modeling, underwriting and pricing, while increased automation in claims demonstrates the industry's growing technological sophistication. To accelerate this momentum, insurance leaders must continue making bold investments in innovation.

Autonomous vehicles and shifts in mobility will require insurers to develop new products tailored to liability risks rather than property damage. Similarly, the emergence of humanoid robots will revolutionize commercial insurance, particularly in workers' compensation, where automation will significantly reduce workplace incidents and profoundly alter traditional premium models. As organizations increasingly depend on AI agents and automation, business continuity coverage will evolve to address new operational risks.

Early adopters of AI technologies will define the future of insurance. AI agents coordinating with drones could transform disaster response, delivering faster, more personalized claims experiences. Strategic partnerships with robotics manufacturers could expand insurers’ capabilities into proactive risk management and automated repair services. While these technologies will challenge conventional business models, they open unprecedented opportunities for innovation and value creation.

The way forward: a strategic framework of critical questions

To thrive in the autonomous era, insurers must develop strategic plans for long-term implementation and business impacts. These plans should progress beyond pilot programs to establish clear adoption roadmaps and compelling business cases aligned with core organizational objectives. A thorough assessment of risks — spanning regulatory, reputational, technological and competitive dimensions — is essential now, before critical mass is reached, and competitors can gain first-mover advantage with superior solutions for AI-enabled customer engagement or autonomous vehicle coverage.

The following framework provides a guide for navigating the autonomous future. Addressing these critical questions will help shape strategies that maximize value creation while managing risks as frontier technologies evolve from cutting-edge innovations to industry standards.

Critical Questions to ask

Conclusion

“The future is already here. It’s just not evenly distributed." William Gibson⁹ wasn’t talking specifically about autonomous technologies when he said that, but his statement certainly applies today. These technologies are no longer speculative, but inevitable. Forward-thinking leaders must thoroughly assess the business impact of these innovations to remain competitive. Those who take decisive action now will not only adapt to this transformation but help define it, creating unprecedented value for customers and stakeholders.

Take action now: Develop comprehensive strategies that integrate frontier technologies into your business planning today to secure your organization’s position in the future.