UK slow in AI maturity race

The UK appears to be losing ground in the artificial intelligence (AI) race, a new study has concluded.

The results in Rackspace Technology’s How are organizations succeeding at AI and machine learning? report, based on the responses of 1,870 IT decision makers, reported that few UK organisations have deployed AI or machine learning (ML).

The survey found that just one in 10 organisations can boast mature capabilities, compared with one in six (17%) worldwide. The vast majority (90%) of IT decision makers say they are either at the early stages of exploring the technology’s potential (54%) or still requiring significant organisational work to implement an AI/ML (36%).

More than one-third (35%) of UK respondents report AI research and development initiatives have been tested and abandoned or failed. Rackspace said the failures underscore the complexities of building and running a productive AI and ML programme. The top causes for failure include lack of data quality (36%), lack of expertise in the organisation (34%), poorly conceived strategy (31%) and a lack of an integrated development environment (27%). 

However, the survey found that UK organisations see AI and ML potential in a variety of business units, including IT (37%), finance (31%), operations (29%) and marketing (25%). The IT leaders whose organisations have successfully implemented AI and ML programmes say such initiatives increased productivity (30%) and improved customer satisfaction (30%).

The study estimated that companies are spending an average of $1.06m per year on AI and machine learning initiatives. This investment in AI is budgeted across the organisation on current and planned projects to grow revenue, drive innovation, increase productivity and enhance user experience.

Among the major organisational challenges in implementing AI and machine learning is talent acquisition. More than a quarter (27%) of the IT decision makers who took part in the survey felt that lack of skills and difficulty in hiring AI experts was a factor slowing the deployment of AI-led initiatives in their organisations.

Costs (26%), security (24%) and infrastructure (24%) were identified by about a quarter of respondents as the top obstacles, but human issues, such as fear of job loss (19%) and executive buy-in (17%), also impact the journey. Strategic concerns, such as identifying use cases (23%), aligning strategies (23%) and defining a business case (18%), reiterate the importance of starting with a strong plan when embarking on AI and ML programmes.

“Countries across EMEA, including the UK, are lagging behind in AI and ML implementation, which can be hindering their competitive edge and innovation,” said Simon Bennett, chief technology officer for Europe, the Middle East and Africa, at Rackspace Technology.

“Globally we’re seeing IT decision makers turn to these technologies to improve efficiency and customer satisfaction,” he added. “Working with a trusted third-party provider, organisations can enhance their AI/ML projects moving beyond the R&D stage and into initiatives with long-term impacts.”