New research released by Mesh-AI reveals that 79% of enterprises surveyed saw positive business outcomes when using AI. However, a lack of understanding of how to apply the technology is the number one business barrier to AI adoption according to nearly 1 in 4 respondents (23%).  

The new report, The State of AI in the Enterprise, explores the pace of AI adoption across UK enterprises, challenges faced and how many are harnessing its transformative power. The research aims to cut through the hype, providing a trusted source of insights into how large organisations approach AI. 

As businesses navigate challenges such as evolving regulations, high inflation and rising fraud rates, there is a strong appetite to innovate and tackle these issues through AI investments. Eliminating inefficiencies and reducing costs was the top cited driver of AI adoption (32%), followed by enhancing the customer experience (21%) and improving business decisions (17%). 

However, despite clear eagerness to leverage AI - with 90% of enterprises stating that it is important to their business model - just 15% of organisations have a clearly defined and well-understood AI strategy in place. The research also exposed that the top technical challenges to AI adoption are poor data quality (40%) and accessibility (38%). 

Michael Chalmers, CEO, Mesh-AI, says: “Enterprises evidently recognise the value of AI for their business model and the potential benefits are well known. As a result, there is a strong desire across the enterprise world to harness the technology. However, our research shows that most have not yet fully figured out how to adopt AI in a strategic way and the overall understanding of AI’s technical concepts are lacking.  

While AI certainly has the potential to drive incredible business results, there is a long way to go. It’s crucial that organisations first develop a solid AI strategy that clearly aligns with wider business goals and put the right data foundations in place, if they want to apply the technology to solve business problems effectively.”