Technology shifts, policy decisions, and attacker behavior are changing at the same time, and their effects increasingly overlap. Insurers, brokers, and security teams are feeling that pressure across underwriting, claims, and risk management. A new global study by CyberCube examines how these changes are expected to influence cyber risk through 2026.
AI moves from promise to practice
AI remains a top priority across the insurance sector, though adoption still trails ambition. 82% of insurance leaders say AI ranks as a top business imperative. Deployment at scale remains limited.
The research finds that 2026 will distinguish organizations experimenting with AI from those applying it to defined operational problems. Early gains center on narrow use cases that reduce manual work. Data extraction, enrichment, and workflow support show the strongest uptake.
Cyber insurers are beginning to use LLMs to translate internet scale data into structured inputs for underwriting and portfolio analysis. These applications target specific pain points such as data gaps and processing delays. Broader change across pricing or risk selection remains gradual.
The study describes a period of reassessment as organizations encounter data quality challenges, integration limits, and governance requirements. Progress continues through testing and targeted deployment instead of broad rollouts.
“AI will reduce repetitive manual tasks and deliver relevant insights, while humans will make all the critical decisions in a claim. 2026 will transform the way claims shops operate, leading to better claims management and freeing up time for more high-value tasks,” said Bob Petrie, CyberCube Board Member.
Claims operations shift toward automation
Claims handling emerges as one of the earliest areas to see impact from AI driven change. The study breaks claims into discrete workflows including intake, reserve setting, fraud checks, compliance, and settlement. Most of these steps rely heavily on human review today.
AI supported workflows begin to reduce repetitive tasks across those stages. Automation supports data entry, document review, and routine verification. Human oversight remains central for judgment based decisions.
The research links this shift to measurable operational effects. Fewer manual touches per claim reduce processing time and error rates. Claims teams gain capacity without proportional increases in staffing. Adoption varies based on risk tolerance and validation standards, though scaled deployment becomes more common during the year.
Regulation creates new exposure paths
Age verification and online safety legislation introduce unintended cyber risk. Requirements that reduce online anonymity create high value identity datasets that attract attackers.
The research highlights rising exposure to identity based coercion, insider compromise, and extortion. Once personal identity data is leaked, attackers gain leverage that can translate into access to corporate systems. This dynamic supports long term campaigns by organized groups and state aligned actors.
Limits on personal VPN use compound the issue in some jurisdictions. The study describes scenarios where regulatory pressure pushes commercial VPN providers toward identity checks and logging mandates. That shift weakens privacy protections relied on by individuals and organizations.
Insurers may see growth in attritional losses tied to credential theft, insecure networks, and targeted coercion instead of isolated large events.
Brokers shift toward quantified advice
Soft market conditions continue to shape broker behavior in 2026. Capacity remains high, and pricing pressure persists. Brokers increasingly compete on advisory capability rather than transaction speed.
Analytics and benchmarking support this shift. Brokers use peer comparisons and loss modeling to frame cyber risk in financial terms. This approach helps clients understand exposure relative to industry norms.
Specialization also grows in importance. Vertical focus allows brokers to address sector specific risks such as the convergence of IT and operational technology in manufacturing or service disruption in healthcare.
The research links advisory depth to stronger engagement with executive leadership. Financial impact modeling supports discussions around limits, controls, and investment priorities.
Analytics move into core workflows
Demand increases for analytics delivered inside existing underwriting and risk management systems. Users seek insight at the moment decisions are made instead of through separate tools.
The study describes platforms evolving from systems of record into systems of insight. Embedded analytics, APIs, and automation reduce manual handoffs across underwriting, placement, and capital allocation.
Data orchestration becomes a core capability. Insurers and reinsurers integrate signals including security posture, threat activity, and loss experience into shared models. Consistent views across teams and regions support portfolio governance.
This shift places emphasis on actionability. Data value depends on timing and relevance within workflows rather than volume alone.
Portfolio discipline gains focus
Portfolio health receives increased attention as growth opportunities remain constrained. The research shows a focus on underwriting consistency and early identification of adverse selection.
Actionable portfolio data supports this effort. Insurers use it to monitor exposure concentration and reinforce underwriting standards across teams. This approach supports stability in competitive conditions.
Streamlined workflows help carriers serve new markets without proportional increases in headcount. Expansion into regions such as parts of Europe and Asia relies on defined playbooks supported by data and automation.
Innovation continues under pressure
Product and capital innovation accelerates under pricing and claims pressure. The study points to new reinsurance structures and alternative capital vehicles that address loss volatility and accumulation concerns.
Innovation also responds to AI driven risk. As commercial AI adoption grows, insurers track how it changes attack patterns and loss frequency. Early evidence points toward incremental effects on routine losses rather than systemic events.
Quantum risk enters early discussion
Quantum computing remains a long term issue, though 2026 marks a shift in attention. Incremental advances in hardware and error mitigation increase confidence in development timelines.
The study notes growing interest in harvest now decrypt later scenarios. Data with long confidentiality horizons such as healthcare and government records draw increased scrutiny.
Insurers begin exploring indicators related to cryptographic readiness. These discussions support education and scenario analysis rather than immediate pricing changes.