‘Belief alone is not enough’ when it comes to AI adoption – skills, governance, and clear leadership are vital to success
While enterprises are upbeat about early AI gains, positive thinking isn’t enough to deliver long-term benefits
Businesses are starting to see benefits from AI, according to new research from Snowflake, but a range of barriers are hampering efforts to scale adoption.
In a poll of 500 UK business leaders, nearly half (45%) of respondents said AI is delivering early gains, with 23% specifically highlighting productivity improvements.
These early results are expected to spur continued investment in the technology, with the majority of organizations planning to ramp up funding over the 12 to 24 months.
Fabian Stephany, economist & departmental research lecturer at the Oxford Internet Institute (OII), said the findings are encouraging amid long-running questions over AI return on investment (ROI) and whether the technology is producing tangible business benefits.
“Since the introduction of generative AI, many observers have been asking when these gains would materialize, and the findings suggest that this moment may now be arriving,” he said.
“This is consistent with what research would predict: technological breakthroughs rarely translate immediately into productivity improvements, as organizations need time to adapt their workflows, governance structures, and capabilities.“
AI optimism only takes you so far
While the survey highlighted growing optimism over the long-term benefits of AI, Snowflake cautioned that enterprises are facing several key barriers when implementing the technology.
Notably, the primary obstacles flagged by respondents weren’t from a technology perspective, with just 19% acknowledging this as a problem.
Instead, enterprises are contending with “structural and operational” issues that prevent them from moving from pilot schemes to enterprise-wide implementation.
The top barriers highlighted in the report included:
- Lack of workforce skills
- Poor data quality
- Organizational silos
- “Unclear leadership or strategic direction”
Making the transition from early experimentation to full integration has become a recurring challenge for businesses over the last two years.
Research from Google Cloud in 2024, for example, claimed a significant number of firms were stuck in an “AI pilot purgatory”.
This problem has become exacerbated since the advent of agentic AI, with analysis from Dynatrace showing around half of projects on this front remain mired in the proof of concept (PoC) stage.
Snowflake found that responsibility for AI governance is frequently “fragmented”, which is adding insult to injury.
Executive leadership usually holds responsibility for investment, for example, yet many organizations have no clear governance owner. This is slowing decision-making and “limiting accountability”.
Jennifer Belissent, principal data strategist at Snowflake, said the study shows that “belief alone is not enough” when it comes to AI adoption.
“Productivity gains require clear ownership, strong data foundations, and alignment between AI initiatives and measurable business objectives,” she said.
“AI has the potential to be a real driver of UK productivity and economic growth. But unlocking that potential depends on getting the fundamentals right - governance, data and clear accountability.”
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