Insurers push ahead with AI despite a growing skills gap
AI spend is set to rise across insurance in 2026. According to Accenture's latest Pulse of Change survey, 90% of insurance executives plan to increase AI investment, and 85% see the upside more in growth than cost savings.
AI is no longer a side project. A third of carriers report enterprise deployment of AI agents, and many leaders are now using generative tools every week. The momentum is real-so are the bottlenecks.
What the data says
- 90% of insurance executives plan to invest more in AI this year.
- 85% say AI's biggest value is revenue growth, not cost reduction.
- 34% are deploying AI agents across multiple functions.
- 29% are redesigning end-to-end processes with AI at the core.
- Generative AI usage: ~33% daily, 57% at least weekly.
- Top barriers: skilled talent shortages (25%) and weak integration with business strategy (24%).
- Only 24% have continuous AI learning in place; just 5% are redesigning roles for AI.
- Preparedness: tech disruption (67%) vs environmental (39%) and geopolitical (44%).
- If an AI "bubble" bursts: 47% would invest more; 37% would increase hiring.
The blocker: skills and strategy
Insurers want scale, but the skills gap is the choke point. Even as budgets rise, few organizations have ongoing AI upskilling or role redesign in place.
The result: fragmented pilots, isolated wins, and slow value capture. Strategy and talent need to move in lockstep or the spend won't translate into outcomes.
Where AI is already working in insurance
- Claims: FNOL triage, document intake, routing, subrogation identification, and payment accuracy.
- Underwriting: prefill, risk signals, appetite screening, referral quality, and submission prioritization.
- Fraud/SIU: anomaly detection, network analysis, and case scoring.
- Distribution: producer enablement, quoting assistance, and cross-sell insights.
- Service: agent/copilot assistance, knowledge search, and next-best-action.
- Finance/Operations: close acceleration, reconciliations, and audit prep.
What to do now: a practical playbook
- Stand up continuous learning: baseline literacy for all, role-based depth for actuaries, underwriters, claims, and IT. Ship updates quarterly.
- Redesign roles, not just workflows: define who decides, who reviews, and how human-in-the-loop works per process.
- Tie AI to the P&L: pick 3-5 use cases with measurable impact (loss ratio, expense ratio, cycle time, NPS). Lock in owners and targets.
- Build a lightweight governance spine: data quality standards, model risk review, explainability thresholds, and audit trails aligned with NAIC AI principles.
- Choose an integration path: decide where to embed AI (core systems, middleware, or agent layer). Avoid tool sprawl-consolidate.
- Measure full value: growth, speed, accuracy, leakage reduction, and employee productivity-not just cost takeout.
- Talent model: pair domain experts with data scientists, ML engineers, and product managers. Create "AI process owners" for claims and underwriting.
If the AI bubble pops
Leaders say they would double down, not retreat. That works only if your pipeline is tied to hard metrics, governed data, and production-ready workflows.
Keep funding what is in production and hitting targets. Sunset pilots that don't show traction in 90 days. Reallocate capacity to the few initiatives that move combined ratio or new business growth.
Quick readiness checklist
- We have 3-5 production use cases with named owners and KPIs.
- We run continuous AI training for all roles, refreshed quarterly.
- Roles and controls are defined for human-in-the-loop decisions.
- Data quality rules and model risk reviews are documented and auditable.
- We report business impact monthly (growth, loss, expense, cycle time).
- Our AI stack is integrated into core systems with minimal tool overlap.
Resources
- Report overview: Accenture Pulse of Change survey
- Upskilling for teams: AI courses by job function and AI Automation Certification
Bottom line: budgets are rising, confidence is high, and AI is moving into the core. The carriers that win will treat skills, governance, and process redesign as first-class work-not afterthoughts.
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