C-suite leaders deploy AI, but struggle to scale it

HTEC research based on a survey of 1,529 C-suite leaders found that AI deployment has reached 100% among respondents, while only 45% reported AI embedded across multiple functions and 25% said their organisation can scale AI rapidly.

The findings point to an execution gap between early deployments and sustained operational use. Respondents highlighted integration with existing systems, skills shortages and prioritisation issues as key constraints on progress.

Scaling gap

According to the survey, many organisations run AI in pilots or discrete initiatives rather than as a coordinated approach across operations. Respondents described uneven progress across functions and products, with efforts often concentrated in isolated areas.

Only a quarter of executives said their organisation can adopt and scale AI rapidly. A further 22% expected selective adoption with slower scaling. The survey found that 31% could experiment with AI but struggled to capture value, while 22% said they were already falling behind.

Executives also attached a time penalty to slow progress. They estimated that failing to act on AI and edge opportunities could set their organisations back by nearly two years.

Integration strain

Integration emerged as the most frequently cited barrier. Forty-three per cent of respondents said embedding AI into existing processes and legacy systems represented the top constraint.

The survey indicated that this stage often creates practical complications for ownership and delivery. Executives described initiatives that stall when AI systems meet older technology stacks and established workflows.

Skills shortages

The research reported that 99% of respondents see critical skills gaps across AI and machine learning, data engineering and cybersecurity. The data points to workforce constraints as a widespread issue rather than a sector-specific problem.

HTEC said the results align with its view of the market. It argued that organisations now face operational challenges rather than questions over whether AI can work in principle.

Priorities and ROI

Executives also pointed to decision-making constraints. The survey found that 39% struggle to prioritise capabilities.

The research linked that to internal capacity and AI literacy across leadership teams. It said organisations often lack the bandwidth to evaluate and scale multiple initiatives in parallel.

The report also indicated a growing preference for external support in delivery. It said executives increasingly plan to rely on specialised partners and third-party platforms as they address internal constraints and attempt to move projects into operational use.

Edge focus

The survey recorded strong familiarity with edge and embedded AI. It found that 92% of executives reported strong familiarity with edge capabilities and expressed confidence in deploying AI closer to where data is generated and decisions are made.

Respondents associated edge deployments with security, resilience, regulatory control and performance in constrained environments. The report described a shift from seeing edge AI as experimental to treating it as a standard part of deployment planning.

It also described a blended approach as a common strategy. The report said most leaders plan a mix of specialised partners, third-party platforms and selective in-house development.

Leadership view

HTEC said the findings reflect a move from experimentation towards operating model changes inside organisations.

"The next phase of AI is not about more pilots," said Lawrence Whittle, Chief Strategy Officer, HTEC. "It's about defining bold ambitions, redesigning end‐to‐end processes, and scaling AI through modular, enterprise‐wide roadmaps. Organisations that succeed will be those that treat AI as a core operating model-not a collection of projects."

The report was commissioned by HTEC and conducted by Censuswide. It drew on responses from executives in the US, UK, Germany, Spain, Saudi Arabia and the UAE across roles including CEO, CIO, CTO, CDO, CFO, COO, CPO and CSO, and across sectors including financial services, healthcare, automotive, telecommunications, retail and semiconductors.

HTEC said organisations are working on one- to three-year horizons for validating use cases, establishing enterprise roadmaps, upskilling and launching AI-linked revenue initiatives.