Talent shortages and AI fraud top UK insurer concerns in 2026
Gallagher Bassett's 2026 whitepaper points to a blunt reality for UK carriers: capacity is being squeezed by specialist talent gaps while AI is reshaping both efficiency and fraud risk. The study draws on responses from 250 insurance leaders across the UK, Australia and North America.
More than 70% of UK respondents say specialist talent shortages are limiting operational capacity, with claims roles the hardest to fill. Nearly 60% report rising claim costs driven by social inflation, more litigation and higher medical expenses per claim.
Key findings at a glance
- 70%+ say specialist talent shortages are limiting capacity; claims roles are hardest to fill.
- ~60% report higher claims costs from social inflation, litigation and medical cost per claim.
- 73% are using generative AI in claims; 35%+ report more suspicious claims tied to AI-generated documents.
"UK insurers are saying claims roles are the hardest to fill. At the same time, claims are becoming more complex. This combination of challenges means workforce pressure is now a direct driver of cost, not just a people issue," says Charlotte Harrison-May, Gallagher Bassett EME&A's head of carrier and market relationships.
Harrison-May adds: "AI is delivering efficiency at scale, but it's also changing the risk landscape. Insurers are committed to good governance, validation and transparency, but want to manage these mitigation strategies without blowing out the cost of claims."
Why this matters for carriers
Capacity gaps extend cycle times, raise LAE and widen indemnity leakage-especially as claim complexity climbs. Affordability pressure forces sharper pricing, tighter underwriting and better risk selection. Meanwhile, AI-aided documentation makes fraud harder to spot with legacy controls.
Immediate actions to consider
- Stabilise claims capacity: cross-train adjusters for high-frequency cohorts, use flexible staffing pools, co-source surge/complex volumes and expand remote hiring where licensing allows.
- Accelerate triage and throughput: deploy AI-assisted FNOL and routing, set clear straight-through processing rules, and keep human review for edge cases and high-severity signals.
- Upgrade fraud controls for AI: add document forensics (metadata checks, compression analysis), image/audio analysis and provenance/watermark verification; strengthen SIU workflows and data sharing.
- Tighten AI governance: define LLM use policies, protect PII, log prompts/responses, maintain audit trails and run regular red-team tests; vet vendors for security, model updates and guardrails.
- Pricing and underwriting discipline: refine guidelines, enrich with third-party data, pressure-test social inflation scenarios and feed real-time claims intelligence back into pricing.
- Track the right metrics: average time to settle, STP rate, LAE ratio, indemnity leakage, SIU hit rate, false-positive rate and claim cost trend versus medical CPI.
What to watch through 2026
- More sophisticated AI-generated evidence: fabricated invoices, altered medical records, synthetic identities and staged losses augmented with deepfakes.
- Growing regulatory focus on AI explainability, data protection and fairness across claims and underwriting workflows.
- Persistent cost pressure from repair supply chains and medical inflation, keeping reserve adequacy and pricing feedback loops under scrutiny.
Resources
- AI for Insurance
- AI for Human Resources
- ICO guidance on AI and data protection
- Insurance Fraud Bureau (IFB)
Full report: The Carrier Perspective: 2026 Claims Insights.
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