AI early adopters gain edge as readiness gap widens

A global survey of executives has found a widening gap between organisations that have integrated artificial intelligence into their business models and those still in the early stages of adoption. The leading group is more likely to report strategic gains and stronger oversight of AI-related risks.

The study, produced by AICPA and CIMA with North Carolina State University's Enterprise Risk Management Initiative, drew responses from 1,735 executives across eight regions and eight industries. It assessed perceived business model impact, organisational readiness, and AI-related risk concerns.

Researchers identified 453 "early adopter" organisations reporting that AI was "mostly" or "extensively" affecting their business model. Within this cohort, 73% said AI was providing a strategic advantage, while 54% worried competitors might use AI more effectively.

Risk focus

Organisations with deeper AI integration also reported greater attention to AI risks. Among early adopters, 69% classified AI as a Top 10 risk or major risk concern, compared with 46% across the full sample.

Board and executive scrutiny also rose sharply. Among early adopters, 65% said AI risk was a focus of executive leadership, versus 30% overall.

Mark Beasley, Alan T. Dickson Distinguished Professor and Director of the ERM Initiative at North Carolina State, linked stronger adoption to investment in controls and organisational foundations.

"Executive teams and boards must recognise that AI's benefits and risks rise in tandem. Governance, talent, and infrastructure are critical, not optional," Beasley said. "This research underscores that organisations with a deliberate approach to readiness are already pulling ahead in measurable ways."

Readiness gaps

Outside the early adopter group, the survey pointed to capability constraints as a primary issue. Across the full sample, only 24% to 27% of respondents reported adequate AI-skilled talent, IT system readiness, or regulatory preparedness.

Smaller organisations reported the greatest shortfalls, with fewer than one in five saying they had the required talent or systems in place.

The study also compared readiness between the leading group and the wider population. It found "AI-Transformed" organisations were nearly twice as likely as the overall sample to report preparedness across key measures. In that group, 50% reported adequate talent, 48% said their IT systems were ready, and 51% reported regulatory readiness.

Tom Hood, Executive Vice President of Business Growth & Engagement at AICPA and CIMA, said the results show a growing separation between organisations building operational foundations and those still evaluating potential uses.

"AI is no longer a peripheral innovation, it's a strategic accelerant separating organisations that are building foundational capabilities from those still exploring its potential," Hood said. "The data shows a widening gap and early adopters are gaining competitive advantage while also taking AI risks more seriously. Leaders who invest in readiness today will shape the opportunity curve tomorrow."

Regional variation

Adoption patterns differed markedly by geography. Executives in South Africa, Central and South Asia, and East and Southeast Asia reported higher levels of AI-driven business model transformation, with 36% to 42% reporting strategic impact and advantage linked to AI.

North America and Europe reported lower levels, at 18% to 22%, which the study characterised as more cautious or incremental adoption. Higher-adoption regions also reported faster-changing risk profiles and more executive and board attention to AI risks.

Industry differences

The survey found industry structure and data intensity correlated with reported AI momentum. Mining recorded the highest reported impact, with 45% citing business model impact and 48% reporting strategic advantage.

Professional and Business Services and Transportation also reported faster adoption, which respondents linked to automation and analytics use cases. Financial Services stood out for competitive pressure: 33% said they worried competitors would outpace them in AI.

Construction and Wholesale and Retail were among the slower-moving sectors. The report linked this to fragmented operations and legacy infrastructure.

Changing risk landscape

Many respondents described AI risks as dynamic. Across the full sample, 26% said AI risks were changing "mostly" or "extensively," rising to 60% among AI-Transformed entities.

The fastest-evolving risk perceptions appeared in Financial Services and Services, which also reported higher levels of board engagement. The study flagged governance, model risk management, and cross-functional oversight as areas receiving increased attention as AI adoption moves from experimentation to broader operational use.

The survey was conducted in Fall 2025 across North America; Europe and the UK; South Africa; Central and Western Africa; the Middle East and North Africa; Central and South Asia; East and Southeast Asia; and Australia and New Zealand.