Despite enterprise buyers accelerating AI investments, a lack of clear evidence and credibility is slowing decision-making, increasing scrutiny and making the overall buying process more complex.

This is according to a study from The Hoffman Agency, which surveyed 450 senior technology decision-makers across the UK, US, France and Germany.

It found that AI-related investment is a major focus for enterprises, with data and AI infrastructure (45%), generative AI (44%), cloud infrastructure (40%), AI-enabled solutions (39%) and agentic AI (34%) among the technologies organisations have invested in over the past 12 months.

Buyers plan to increase spend on a range of AI technology over the next 12 months with top areas including generative AI (36%), agentic AI (34%), data and AI infrastructure (34%), cloud infrastructure (34%) and AI-enabled solutions (33%).

What’s driving AI investments?

Improving operational efficiency (32%), keeping pace with technology advances (30%), reducing costs (25%) and faster product development (25%) are key drivers. Those priorities are reflected in where new technology is being applied, with task automation (38%), workflow optimisation (35%), product development (34%), risk analysis (31%) and customer support (30%) the most common priority areas.

“Despite all the hype around a multitude of benefits, enterprise AI buyers are still heavily focused on productivity gains. While perhaps understandable in the current economic environment, the AI growth narrative has yet to land with many enterprises,” said report author Tom Broughton, VP and head of enterprise AI at the Hoffman Agency.

Friction and Scepticism

While overall investment levels are ramping up, purchasing AI-enabled solutions is becoming much more complex. Nearly two-thirds of buyers (64%) say AI-related tech face more scrutiny than other technology investments. More than three-quarters (78%) believe that many AI companies make claims that are difficult to verify or compare, while more than two-thirds (69%) say many AI companies sound similar and are difficult to differentiate.

Even more concerning for vendors is that many buyers feel so overwhelmed by the volume of AI products emerging that three in five (61%) are unsure which ones are genuinely credible.

When claims are difficult to verify, buyers say the decision process takes longer (46%), larger or more established suppliers are favoured (37%), procurement or compliance checks increase (32%) and more stakeholders become involved in evaluation (32%). More than a quarter (27%) delay the purchase decision and one in six (16%) abandon the purchase entirely.

“Buying enterprise AI solutions has become a full-body contact sport. Vendors are flooding the zone with unsubstantiated and incomparable claims,” continued Broughton. “The result? More scrutiny, more scepticism, and more friction that is dramatically slowing purchasing and adoption. Enterprise AI buyers are yearning for evidence and credible claims that can help them make decisions with confidence.”

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Comparing AI Claims

The strongest confidence builders for buyers are transparent explanations of how products work (46%), customer case studies with measurable outcomes (41%), proof of real-world deployment at scale (40%), demonstrated technical performance benchmarks (37%) and independent third-party validation (36%).

More than half (57%) of organisations use industry analysts to help identify and shortlist vendors. Media and independent sources also play an important role in discovery with one in four buyers (25%) turning to business technology media to discover new vendors.

LLMs are also becoming part of the buying journey, with one in six buyers (17%) using them to become aware of new vendors or solutions, and the same proportion (17%) citing them as influential when selecting between vendors.