Insurers Split Over Who Should Own AI-Driven Work, Research Shows

A survey of 150 insurance leaders found that 83% back AI for repeatable operational tasks while 86% insist people must retain authority over consequential decisions, according to mea Platform.
By: | September 17, 2026
AI adoption

Insurance leaders are drawing a hard line between execution and judgment as they scale artificial intelligence across underwriting, claims and broking operations, according to a research report from mea Platform, an AI-power insurance automation provider.

The survey of 150 insurance sector decision-makers, commissioned by mea and conducted by Information Services Group, found 83% of respondents support using AI for repeatable operational work, while 86% believe people must retain authority over consequential decisions. According to the report, the finding points to a need for insurers to define the boundary between AI execution and human judgment before scaling further, distinguishing tasks like extracting a policy term from decisions like binding a non-standard risk.

The report recommends a four-owner operating model in which AI executes repeatable work, people hold judgment and accountability, global capability centers build enterprise capability, and outside partners deliver contracted services, with the institution retaining accountability for outcomes throughout.

Trust Depends on Governance, Not Just Domain Knowledge

Trust in AI systems among insurers is highly conditional, the report said. Three-quarters of respondents said they most trust insurance-specific or governed-hybrid AI approaches, while only 6% said they trust general-purpose models alone.

The report said domain knowledge does not substitute for governance, and outlined what “governed” should mean in practice: connecting AI workflows to controlled policy wording and underwriting appetite, separating what a system may read from what it may execute, ensuring human reviewers have sufficient time and authority to challenge outputs, and reassessing authority whenever policy wording, data or the underlying model changes.

The report said permission to operate with reduced oversight should follow demonstrated evidence of decision quality and appropriate referrals, not just improvements in speed or cost, and that execution should be restricted if performance drops below agreed thresholds.

Separately, ISG’s activity-level analysis of 20 insurance operations found the AI-human boundary varies sharply by task complexity. Complex and contentious claims showed the lowest end-to-end AI deployment among the activities studied, while repetitive tasks showed the highest.

Ambition Outpaces Execution, While Capacity Limits Growth

Nearly all insurers, 96%, have some form of AI-led operating model redesign on their agenda, the research found, with 37% reporting redesign underway and 21% reporting it is  planned; a further 27% are still evaluating. Yet the report said only about 13% of insurers currently operate at an advanced AI posture, even though 52% intend to reach that level, indicating a gap between stated ambition and delivered execution.

“Insurers know exactly where they want the line between AI and human judgment. Getting there is the part they have not solved. The gap between 96% with redesign on the agenda and the 13% that have reached an AI-centred operating model defines the next two years,” said Ashish Jhajharia, insurance SME and principal analyst with ISG.

Among insurers using business process outsourcing partners, just 12% reported broad or AI-first service deployment, while 78% said they are using production AI mainly for incremental efficiency gains or limited automation.

The research also linked operational capacity directly to growth. ISG estimated that roughly one in nine broker submissions is declined or left unquoted because of capacity constraints rather than risk appetite. Insurers reported productivity gains of 61% and faster cycle times of 51% from AI deployment to date, alongside an expected average cost reduction of 16% over 24 months, according to the report.

Provider Relationships Face a Reset

The research found existing outsourcing relationships under pressure. Among BPO users, 86% said they would renegotiate or completely rework contract terms if renewals were happening today, with 64% favoring renegotiation and 23% seeking a complete rework; only 8% would renew largely as-is, ISG found.

Existing BPO providers ranked last among six routes insurers expect to use to acquire AI capability, with internal build and new AI managed service providers ranking highest. Dedicated AI platforms ranked third overall, with the report noting a narrow gap against core system vendors and describing the results as pointing to a capability portfolio rather than an exclusive choice between platforms and incumbents. AI-led innovation fell short of expectations for 49% of BPO users, the largest shortfall among nine dimensions measured, followed by strategic value at 39%.

Board-level scrutiny is also rising, the report found: 81% of BPO users reported a formal request or informal board or CEO-level discussion about modeling AI-driven alternatives to existing BPO contracts. Separately, 63% of respondents agreed that integrating AI across multiple functions is a primary barrier to progress, while 47% ranked integration with existing technology and core systems among their top three barriers, according to ISG.

Obtain the full report here. &

The R&I Editorial Team can be reached at [email protected].

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