Most Companies See AI Benefits, But ROI Timeline Stretches Into 2028

Gallagher's latest survey reveals AI adoption is accelerating, yet skills gaps and governance shortfalls threaten to slow the realization of returns.
By: | February 24, 2026
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Three years after generative AI burst onto the business landscape, organizations have shifted from experimentation to operationalization — but they’re discovering the payoff takes longer than anticipated, according to Gallagher’s 2026 AI Adoption and Risk Survey.

AI implementation has reached a critical milestone. Sixty-three percent of organizations now have either fully operationalized or adopted AI across parts of their business — a dramatic jump from 45% in 2025 and 34% in 2023. The technology is primarily driving value in IT operations management, customer-facing functions like chatbots and personal assistants, and research and analytics.

Early results show promise on the productivity front, according to Gallagher. Eighty-six percent of businesses report positive impacts from AI on employee productivity, which rises to  91% in the U.S., and reaches 93% in Canada and Australia.

Additionally, 82% of respondents report they already see positive impacts on revenue, while 83% expect AI to boost revenue in the future.

Yet organizations are tempering their expectations about when these benefits will materialize financially. Nearly two-thirds of companies (63%) are actively measuring return on investment — and they’re projecting it will take an average of 28 months to recover their upfront costs and realize meaningful returns.

“Organizations measuring the ROI of AI deployment anticipate it will take an average of 28 months for the value of transformation to outweigh the upfront costs,” the report said, emphasizing that this extended timeline reflects the complexity of embedding the technology into operational workflows.

The Gap Between Ambition and Execution

Despite strong adoption rates, significant obstacles persist, according to Gallagher’s report. More than half of businesses cite skills gaps and recruitment challenges as primary barriers to accelerating AI implementation. Technical and infrastructure limitations compound the problem, as many organizations struggle to integrate new AI systems with legacy platforms while building scalable solutions for company-wide deployment.

AI governance remains weak, the report said. Less than 47% of organizations have adopted formal risk management frameworks for AI use, conducted ethical impact assessments, or developed AI-specific incident response plans.

This gap takes on added significance when considering the risks businesses face: 57% identify AI errors and hallucinations as top concerns, 56% worry about legal and reputational risks from misuse, and 55% are concerned about data protection and privacy violations.

“AI liabilities aren’t simple data breaches; they’re a black box of algorithmic risk where traditional breach response approaches fall short,” said John Farley, managing director of Cyber at Gallagher. “Managing these legal, operational and reputational exposures requires a multidisciplinary approach that addresses bias and blends oversight with data integration.”

Beyond technical risks, people-related challenges loom large, Gallagher noted. At least half of businesses anticipate job insecurity, strikes, reduced employee engagement and change fatigue stemming from AI adoption. Yet fewer than half of organizations have communicated their AI adoption strategy to their workforce — a communication gap that could deepen these concerns.

“You need to be building skills, confidence and trust to enable the workforce to be using AI on a day-to-day basis so that it is embedded into workflows,” said Sonya Poonian, director of AI Transformation, Employee Engagement and Communication Consulting practice at Gallagher. “Only then will you reach the inflection point where you can unlock that longer-term ROI.”

Preparing for the Next Phase

To move forward effectively, organizations must address AI governance and establish clearer accountability structures, Gallagher said. Currently, the IT department shoulders most responsibility for managing AI-related risks, according to nearly half of respondents, though personal accountability among departments actually using AI has grown in importance compared to roles like legal, compliance and HR functions.

The insurance industry is beginning to respond to emerging AI exposures, developing new policies, endorsements and bespoke coverage options — mirroring the market evolution that followed the rise of cyber liability issues years before. One in five insurance professionals surveyed by Gallagher said a client experienced AI-related losses in the past year, with cyber liability, product liability and employment practices liability classes most frequently impacted.

Yet, according to insurance industry respondents, most policies don’t explicitly address AI-related risks, leaving businesses potentially underprotected. Policy language remains vague about what constitutes an AI-related loss, potentially creating disputes between organizations and insurers when claims arise.

Step-by-step progress, however, continues. More than half of businesses are investing in training programs, implementing change management initiatives and building AI skills internally — signaling a commitment to bringing employees along on the digital transformation journey, the report noted.

“Embedding AI in the operating model means redesigning processes and role definitions and building scalable AI platforms, and very few organizations are at that stage yet,” said Ben Warren, managing director of People, Data, AI and Innovation at Gallagher.

View the full report here. &

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

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