Poor data quality is biggest barrier to AI adoption

SOFIAH NICHOLE SALIVIO

News Editor

Dayshape has published research suggesting poor data quality is the biggest barrier to effective AI adoption for many UK professional services firms, with 34% of senior leaders identifying it as the main obstacle.

The survey of 200 UK senior leaders in professional services found that investment in new technology has become a major management priority. Some 61% of organisations said it is now a top business priority, while 50% of respondents said it is their main personal focus for the year ahead.

The findings point to a gap between the sector’s appetite for AI and the operational conditions needed to support it. Integration with existing systems was cited by 32% of leaders as a barrier to effective AI use, while 28% pointed to cost and investment requirements and 22% to a lack of internal capability.

That puts data issues ahead of problems that often dominate discussion around AI adoption, including budgets and skills. The figures suggest firms are finding the quality and consistency of their underlying information a more immediate challenge than buying software or assigning staff to manage it.

Current use

More than half of respondents, 54%, said their organisations already use AI for data analytics. Another 47% said it is used for data entry, while 41% use it for innovation.

AI is also spreading into operational planning. The survey found that 39% of firms use it for workforce optimisation, 34% for project and resource planning, and 29% for capacity modelling.

These figures indicate that AI is moving beyond isolated experiments into areas that affect staffing, utilisation and client work. In professional services businesses, where margins and delivery schedules often depend on accurate planning, weak data quality can directly affect how useful AI tools prove to be.

Expansion plans

Leaders also expect AI use to increase in business areas tied closely to forecasting and service delivery. About 32% said they plan to expand its use in client delivery tools, 32% in capacity modelling, 31% in project and resource planning, and 30% in workforce optimisation.

The emphasis on these functions suggests firms are not treating AI simply as a back-office tool. Instead, they are looking to deploy it more widely in decision-making and operational management, where inaccurate or fragmented data can limit the value of automated systems.

The study was conducted by OnePoll on behalf of Dayshape. According to the company’s background notes, it surveyed senior leaders at professional services firms in the UK and US with more than 750 employees. The UK findings released by Dayshape focused on responses from 200 senior leaders.

The data comes as professional services groups face pressure to improve productivity while managing hiring costs and shifting client demands. Many firms have invested in digital tools in recent years, but the survey suggests that connecting systems and improving data standards remain unresolved challenges.

Andrew Bone, Vice President of Product at Dayshape, said the value of AI depends heavily on the quality of the business information beneath it. He said firms would fall short if they treated AI deployment as a standalone initiative without addressing broader operational weaknesses.

“Many people in professional services firms already struggle with poor data quality, disjointed systems and internal silos, placing a huge drag on operational effectiveness. Similarly, AI initiatives will not meet expectations if they are layered on top of those foundations. The organisations seeing the most value are the ones focusing not just on adopting AI, but on strengthening their data and building the internal capability to use these tools effectively. The findings highlight a shift in how organisations need to approach AI adoption, with greater emphasis on readiness as well as investment,” said Bone.