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From experimentation to execution: How insurers are moving beyond AI hype
Why AI success in insurance now depends on execution, integration, and measurable business impact
Why insurers are moving beyond AI experimentation toward execution
The insurance industry is entering a new phase of AI maturity—focused on integration, impact, and measurable return on investment.
Just a few years ago, executives needed convincing that artificial intelligence could transform insurance operations. Today, the conversation has shifted from why AI to how value is measured. This change reflects an industry that has moved beyond hype toward execution and performance.
In a recent KPMG survey of insurance executives, 59 percent expressed confidence that their organization is a leader in AI adoption compared to peers. Even more telling, 90 percent reported that their AI budgets have increased compared to the prior year. This sustained investment signals conviction—but also raises expectations for results.
As insurers accelerate AI adoption, they are increasingly confronting challenges that extend beyond technology, including legacy system fragmentation, workforce readiness, and governance. The real question is no longer whether to invest in AI, but how to execute at scale.
How insurers are shifting from AI use cases to functional transformation
Early AI efforts across insurance followed a familiar pattern. Organizations identified hundreds of potential use cases and pursued them individually. While that approach delivered quick wins, it rarely produced enterprise-wide impact.
Leading insurers are now adopting a functional lens—rethinking how AI can transform entire workflows instead of isolated tasks. The focus has shifted to understanding end-to-end processes and embedding AI across the value chain.
This transition is reshaping core insurance functions. In claims, AI compresses timelines while improving accuracy. In underwriting, it supports faster, more informed decisions by analyzing larger and more complex data sets. In finance, AI shifts teams from backward-looking reporting to forward-looking insight and continuous monitoring.
To achieve this level of execution, insurers are aligning business leaders, operations, actuarial, and technology teams from the outset—ensuring AI initiatives address real business needs and scale sustainably.
The real challenge is the ability to integrate and embed emerging technology into normal business operations. If you’re able to embed AI responsibly and strategically, it really shapes the future of your organization.
Raj Konduru
Consulting Sector Leader, Insurance, KPMG LLP
Where insurers are seeing the most tangible AI execution today
As insurers move from experimentation to execution, AI impact is becoming concentrated in a few core functions where it can be embedded directly into daily workflows. Rather than deploying standalone tools, organizations are redesigning how work gets done.
Key areas of execution include:
- Claims operations
AI accelerates intake, document analysis, and triage—helping reduce cycle times while improving consistency and accuracy across claim types. - Underwriting and risk assessment
AI supports faster evaluations by surfacing insights from broader data sources, augmenting underwriter expertise without replacing judgment. - Finance and performance monitoring
AI enables real-time visibility and continuous forecasting, allowing finance teams to move from retrospective reporting to proactive decision support.
Across these areas, insurers are measuring success less by the number of AI use cases deployed and more by operational outcomes delivered at scale.
Why empowering employees is critical to scaling AI in insurance
As AI becomes embedded in everyday workflows, employee adoption has become a decisive factor in execution success.
Many insurers are embracing an “AI as coworker” philosophy, using AI agents to automate data gathering, initial analysis, document generation, and anomaly detection. This allows employees to focus on higher-value work that requires judgment, expertise, and relationship management.
According to the survey, 45 percent of insurers have adopted an approach that empowers employees to use AI in their daily work, supported by training and clear guidance. This mindset recognizes that AI delivers value only when people trust it, understand it, and use it responsibly.
Execution accelerates when AI is designed around how employees actually work—not as a parallel toolset, but as part of the workflow itself.
When we introduce AI agents to take on data gathering and initial recommendations for use by critical business process owners, the impact can be dramatic. At scale, the ability to expedite tasks from hours to minutes—that’s the kind of transformation that delivers real value and enhanced customer experiences.
Sean Vicente
US Sector Leader, Insurance, KPMG LLP
What risks insurers must manage as AI execution accelerates
AI’s transformative potential also introduces new risks—particularly in a highly regulated industry.
As insurers scale AI adoption, they expand their cybersecurity footprint and introduce new governance considerations around data, models, and accountability. While 59 percent of executives believe their organization is equipped to manage AI-driven cyber risks, fewer report fully mature information lifecycle management programs for AI-generated data.
Successfully executing AI at scale requires trusted frameworks with clear guardrails around data access, security controls, and governance. For insurers, embedding trust from the start is essential to sustaining innovation while meeting regulatory expectations.
What distinguishes insurers that execute AI successfully at scale
While AI investment is widespread, execution maturity varies significantly across the industry. Leaders are separating themselves not through experimentation, but through disciplined execution.
Insurers executing effectively tend to share several characteristics:
- Focused execution over breadth
Rather than scaling disconnected pilots, leaders concentrate on initiatives that deliver functional impact—turning increased AI investment into measurable performance. - AI embedded into everyday work
AI is integrated into systems and processes employees already use, reinforcing adoption and supporting workforce enablement. - Governance built in, not bolted on
Risk, cybersecurity, and data management are considered from the outset, enabling teams to scale AI with confidence. - Outcome-driven measurement
Progress is evaluated through improvements in speed, accuracy, experience, and operational control—rather than the volume of models deployed.
This shift—from proving AI’s potential to realizing its performance—defines the next phase of AI maturity in insurance. Execution is now the differentiator.
How insurers can turn AI investment into measurable performance
Download the full article to explore:
- How insurers are moving from experimentation to execution
- Where AI is delivering the greatest functional impact
- How organizations empower employees while managing risk
- What it takes to govern and scale AI responsibly
The full article provides deeper insight into how insurers are translating AI investment into performance—and what execution excellence looks like in practice.
From experimentation to execution: Insurers are moving beyond AI hype
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From experimentation to execution: How insurers are moving beyond AI hype
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Meet our team
Sean Vicente
US Sector Leader, Insurance, KPMG LLP
Raj Konduru
Insurance Consulting Leader, KPMG US
Matthew McCorry
Principal, Growth & Strategy, KPMG US
Michael Messeih
Advisory Managing Director, KPMG US
Ravi Bhagat
Principal, Actuarial, KPMG US
Sean Vicente
US Sector Leader, Insurance, KPMG LLP
Raj Konduru
Insurance Consulting Leader, KPMG US
Matthew McCorry
Principal, Growth & Strategy, KPMG US
Michael Messeih
Advisory Managing Director, KPMG US
Ravi Bhagat
Principal, Actuarial, KPMG US