Klarus suggests pilots have helped mid-market identify key to AI implementation

Nine-in-ten mid-market companies are now confident in their internal expertise across all areas of AI deployment, following extensive experimentation. The findings from Klarus suggest that firms believe AI expertise and governance boosts can provide the final piece of the puzzle for AI implementation.

So much time and money has been poured into AI adoption, but many firms have seen little to no return on those resources. A gruesome term, “pilotitis”, has even been coined to describe the fact that AI projects often fail to scale to a firm-wide basis – with research showing 40% of AI initiatives remain at the earliest stages of experimentation.

The latest study to grapple with this issue comes from Klarus, a specialist technology consultancy with a focus on AI. According to its paper, the long period of experimentation may finally have yielded some answers for firms; with mid-market companies in the UK and Ireland now blaming data quality and governance for holding many back from scaling beyond pilot stage.

A 43% chunk said that improving data quality would now be a priority for their AI roll outs over the coming 12 months. At the same time, 39% said building AI expertise, and 35% said governance and guardrails would be top of the agenda to make the technology finally work for them.

However, there is also a sense that patience may finally be running out in some quarters. A 49% portion intimated that the ROI of their AI deployments would also become a top priority now – suggesting that should this cluster of topics still not yield the kind of wild productivity boosts promised, that a reckoning may soon be on the cards.

It may not come to that, if the firms are to be believed. On average, 91% of mid-market companies are confident in their internal expertise across all areas of AI deployment, thanks to the extensive piloting information they have gleaned in the last three years.

When examining the piloting or AI deployment projects which outperformed expectation in recent years, a majority identified three key factors at play. While 59% said strong data quality had helped ensure success, 54% also agreed effective governance, and the ability to integrate into existing workflows were crucial.

The research also highlights the impact of AI on talent beyond automation and headcount reduction. While cost savings and productivity gains remain important expected outcomes, AI is also improving the quality of work. When asked the impact AI is mostly having on junior staff, 45% say it is enabling them to do their job better or quicker and 24% say it is creating new roles and opportunities.

Alper Gunaydin, CTO at Klarus, commented, “Mid-market companies have a real advantage because they can often move fast, particularly when it comes to technology transformation. We see this agility in action when companies are turning to AI and automation to address productivity and accelerate growth. However, our research shows that too many pilots stall because companies lack AI expertise, quality data and effective governance. Making that agility count requires clear priorities, strong foundations and access to senior expertise, all of which will help translate investment into tangible business outcomes and unlock growth without increasing the cost base.”