The rapid adoption of artificial intelligence in businesses across the UK and US is exposing a critical flaw, many organisations lack the foundational data strategies needed to ensure AI’s success. Research from Carruthers and Jackson reveals that over a quarter (26 per cent) of businesses have no formal data strategy, despite a significant increase in AI deployment.
The study, based on insights from nearly 200 data leaders, highlights a striking contradiction: only seven per cent of businesses now operate without AI, a sharp drop from 26 per cent a year ago, yet 39 per cent admit to having little to no data governance framework in place. This disconnect is creating what industry experts are calling an ‘AI Paradox’, where AI adoption outpaces the necessary infrastructure to support it, leading to inefficiencies, inaccuracies, and heightened security risks.
Caroline Carruthers, Co-Founder and Chief Executive of Carruthers and Jackson, warns that while AI tools are flooding into organisations, the data literacy of employees has remained stagnant. “An AI Paradox has been created, as the use of AI tools in organisations has surged in the last year, yet employees lack the data literacy to use them effectively, as their fundamental understanding of data remains largely unchanged from last year.”
Businesses are increasingly recognising the need for more tailored approaches to data governance. The report notes a shift away from broad, one-size-fits-all frameworks, with 37 per cent of organisations now adopting multiple governance structures designed to fit the needs of specific departments. However, this still leaves many companies without a clear structure, potentially undermining the effectiveness of AI investments.
Richard Bovey, Chief for Data at AND Digital, argues that without a solid data governance foundation, AI implementation risks becoming an expensive liability. “The benefits of AI are well-known, but a gap remains in the understanding and consideration of the risks it poses if implementation is rushed. Businesses need a strong data governance structure to overarch technology development, and that’s especially true when it comes to AI, not only facilitating greater accuracy and reliability within AI outputs but helping to mitigate potential privacy and security concerns.”
The study also raises ethical concerns, as 44 per cent of organisations have seen an increase in discussions around AI ethics, yet only 13 per cent have formalised these into structured policies. This lack of clear ethical guidelines leaves businesses exposed to potential regulatory scrutiny, reputational damage, and legal risks as AI-driven decisions increasingly influence operations.
Another major hurdle is data literacy. The report found that 57 per cent of businesses acknowledge a skills gap, with most employees lacking the necessary understanding to work effectively with AI. Despite this, 53 per cent of organisations have increased their AI usage, further widening the gap between technological adoption and workforce capability.
Bovey believes businesses need to take a more integrated approach to data and innovation. “Without the data basics in place, even the best AI technology will fall short in delivering meaningful ROI for a business, so it’s important that organisations take a data AND innovation approach to project delivery. Weaving data governance principles across the development and integration process, supported by data skills, will greatly increase the likelihood of success for AI systems, providing a platform for them to be a business enabler rather than a costly mistake.”
As businesses continue their push towards AI-driven efficiencies, the lack of structured data strategies and governance frameworks remains a critical barrier to success. Unless organisations prioritise data infrastructure alongside AI adoption, they risk turning what should be a transformative technology into an expensive and ineffective investment.
