When people talk about the forces driving AI innovation, the spotlight usually falls on tech giants and research labs. These institutions may build the models and release the breakthroughs, but they’re not the only ones shaping the future of intelligent systems.

There’s another key player, often overlooked, that has a quiet yet critical role in accelerating innovation and adoption: insurance companies.

Across sectors, businesses are exploring ways to harness agentic AI. But many of these initiatives are focused on a single area or workflow. Fewer companies are adopting the technology at scale. Some cite risks such as algorithmic failure, model bias, regulatory uncertainty, and reputational harm.

That’s where insurance comes in. Insurers have the power to take many of the risks out of companies leveraging AI for innovation. De-risking AI involves designing insurance coverage solutions that address emerging AI exposures and pairing them with advisory services and governance insights. Insurance can do much more than protect against loss. It can be the foundation that enables safer AI adoption at scale for companies in all industries.

A History Fueling Innovation

Insurance has been a catalyst for change before. In the 17th and 18th centuries, insurance helped transform maritime trade. Before the formal insurance market emerged, financial losses from shipwrecks, piracy, and unpredictable weather could be catastrophic and occurred frequently enough to bankrupt merchants and trading companies. The rise of marine insurance in London pooled risk and offered financial protection. Marine insurers were then able to invest in larger fleets, explore new trade routes, and finance global commerce. In essence, insurance powered the rise of international trade, and eventually the modern global economy.

Today, insurers have a similar opportunity to shape the future, supporting the safe development of agentic AI. By transferring performance and algorithmic risks to insurers, businesses can pursue ambitious AI initiatives without fear of catastrophic losses driving broader adoption of autonomous systems.

Coverage can also help build stakeholder trust. When insurers back AI deployments with liability coverage and performance warranties, it signals that these systems are responsibly governed and risk-aware.

Beyond financial protection, insurers can help define best practices. They can set policy conditions that promote sound AI governance—such as requiring bias audits, robust security protocols, and ethical oversight. These requirements not only mitigate losses but also align with evolving regulatory expectations.

As AI adoption accelerates across mid-market and enterprise sectors, standardized insurance offerings can scale efficiently across geographies. Much like cyber insurance evolved from niche to necessity, AI insurance is poised to become a staple of modern enterprise risk management.

Designing Coverage for the Agentic AI Future

As agentic AI becomes integral to critical business operations, demand for specialized coverage will surge, opening new lines of business within P/C insurance portfolios.

To meet this need, insurers can design products that address novel risks traditional policies weren’t built to cover, such as:

• AI Algorithmic Liability (“AI E&O”): As businesses increasingly rely on AI for decision-making, gaps in traditional tech E&O or professional indemnity policies become evident. Tailored coverage that explicitly addresses algorithmic bias and performance failure will be critical in mitigating liability exposure and enabling broader deployment.
• AI Performance Guarantees and Warranties: Enterprises are wary of deploying AI in high-stakes environments without performance assurances. This offering will offer protection when AI products fail to meet agreed-upon performance thresholds, such as accuracy, availability, and fairness.
• First-Party AI Failure and Business Interruption: Standard business interruption (BI) policies often require physical damage to trigger coverage, leaving a gap for digital-first failures. AI-specific BI policies can close this loophole by reimbursing losses tied to non-physical but operationally critical system failures, including those involving third-party AI vendors.
• Cyber Extensions for AI: Agentic AI introduces new cyber risks, such as adversarial attacks, model poisoning, and data exfiltration. Modern cyber policies must evolve to explicitly address these vulnerabilities and eliminate exclusions that could leave policyholders unprotected.

Related articles: Where the AI Risks Are: Swiss Re’s Top 10 Ranking by Industry; AI Insurance Takes a Step Toward Becoming a Market ;; Is AI Risk Insurance the Next Cyber for Insurers?; Emerging Risks: Does Generative AI Impact Businesses’ Liability Exposure?; Writing Cyber Is Key To Survival, Munich Re Exec Says

Capitalizing on the AI Opportunity

To lead in this space, insurers must first develop a foundation of AI risk expertise. Multidisciplinary teams must assess model failure modes, adversarial threats, and systemic bias. Carriers also need to develop proprietary risk assessment frameworks that evaluate clients’ AI governance, data quality, and security posture.

After the foundation is set, launching targeted pilot programs is an important start. AI performance warranties to healthcare startups or business interruption coverage to cloud-native AI platforms are good examples. Collaborating with reinsurers can help refine underwriting approaches, share risk, and build institutional knowledge.

Insurers can also embed value-added services into the insurance lifecycle. Prebinding reviews, bias assessments, and model security audits not only reduce risk but enhance client trust. When failures do occur, AI-specific incident response protocols can minimize downtime and reputational damage.

Regulatory engagement will be equally important. By working with policymakers and contributing to AI governance frameworks, insurers can position themselves as key enablers of responsible innovation. Aligning policy language with regulatory expectations, including insurability of certain fines or compliance costs, will further enhance their value proposition.

Standardization will enable these insurance solutions to scale. Modular endorsements to existing cyber or E&O products can be developed to address emerging AI risks like bias, performance failures, or intellectual property disputes. Digital platforms that enable seamless quoting, underwriting, and claims processing will be key to distributing these products efficiently—bringing the speed and convenience of InsurTechs to the AI insurance market.

The rise of agentic AI marks a pivotal shift in how businesses operate, and how risk must be understood, managed, and transferred. Insurers have a rare opportunity not only to protect against the downside of this transformation, but to actively accelerate its responsible adoption. By stepping into the role of enabler, not just responder, the insurance industry can once again prove its historical power to underwrite progress.

AI insurance can become the backbone of tomorrow’s innovation economy: ensuring that the boldest ideas don’t just launch, but endure.