New Report: 100% Of Businesses Now Use AI, But Only 25% Can Actually Scale It

A global survey of 1,529 C suite executives says that 100% of organisations now use AI in at least one area, according to research commissioned by HTEC and carried out by Censuswide.

But there’s an issue. Only 45% of executives say AI is fully embedded across more than one business function or product. The rest describe activity locked into pilots, tests or narrow business units. The research says this leaves AI running in fragments rather than as a shared operating model.

The report describes this moment as a turning point. Adoption has finished. Execution has not. Leaders no longer question whether AI works. They question why success in one area fails to travel across the organisation.

Lawrence Whittle, chief strategy officer at HTEC, says the problem lies in how AI is treated inside businesses. “The next phase of AI is not about more pilots. 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.”

Executives also rate their own organisations highly across digital infrastructure, resilience and innovation. More than 78% describe performance as good or excellent across these areas. That confidence makes the lack of scale harder to explain and more uncomfortable to confront.

 

What Is Stopping Businesses From Scaling AI?

 

The survey identifies integration as the main thing slowing progress with 43% of executives say difficulty embedding AI into existing processes and legacy systems blocks further rollout. Systems built long before AI now limit how quickly new tools can work across departments.

Leadership issues also slow momentum as 42% report poor alignment on AI priorities across the executive team, while 39% cite uncertainty over which capabilities deserve attention. Without shared direction, AI projects struggle to gain traction outside the teams that launched them.

A massive 99% of executives say their organisation faces gaps in technical capability. Cybersecurity, AI engineering and data expertise top the list. These shortages lead to higher costs and slower delivery, according to respondents.

Alex Rumble, chief marketing officer at HTEC, links these barriers to how AI is treated at board level. “The real risk of not realising value from AI isn’t the technology itself. It is that often organisations are slow to operationalise and systematise associated processes. Many organisations view AI as an IT project rather than a necessary strategic business transformation.”
 

 
That thinking has financial consequences, because 44% of executives report higher costs around reliance on external suppliers. 41% say innovation went down as teams struggled to keep pace with new tools and techniques.

Geography also affects progress with 53% of executives in Saudi Arabia saying AI is fully embedded, compared with 39% in Spain. The report links this difference to newer IT estates and fewer legacy constraints rather than better technology alone.

 

How Do Leaders Think The Gap Will Affect Results?

 

Executives understand what slow progress could cost. On average, they estimate that failure to act on AI and edge opportunities would set their organisation back by almost two years.

Only 25% believe their organisation can adopt and scale AI quickly. Another 31% say they can experiment but struggle to turn that activity into business value. A further 22% say they are already falling behind.

Edge AI attracts high interest as a way to unlock stalled projects. Ninety two percent of executives say they are familiar with edge capabilities, and 97% express confidence in deploying AI closer to where data is created. Security, resilience and regulatory control lead the reasons for this direction.

Tim Sears, chief AI officer at HTEC, says execution depends on people and data over ambition. “Embedding AI into an organisation starts with people. Leaders must guide the business through practical steps so every employee understands how AI can improve their work and drive business value.”

Most executives now work to a 1-3 year timeline to validate use cases, upgrade skills and launch AI driven revenue streams. The report presents this window as narrow. Without better integration and leadership clarity, AI activity risks becoming expensive background noise rather than a source of growth.

The message from the research is quite blunt… AI use has reached 100%. Scaling it has not.