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UK lags behind Asian economies on enterprise AI adoption

40% of UK companies embracing AI have boosted their investments

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40% of the enterprises already working with AI.
37% of IT professionals at large UK organisations have actively deployed AI.
Only 32% are currently training or reskilling employees to work together with AI tools.

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More than a third of UK organisations with over 1,000 employees are actively using AI – placing the UK behind leading Asian economies – according to new research.

Findings from the “IBM Global AI Adoption Index 2023,” conducted by Morning Consult on behalf of IBM, revealed that early adopters are leading the way, with 40% of the enterprises already working with AI intending to increase investment in the technology. On-going challenges for AI adoption include; hiring employees with the right skill sets, high costs, and data complexity which continue to inhibit businesses from adopting AI.

The survey revealed that; 37% of IT professionals at large UK organisations have actively deployed AI while 41% are exploring using the technology.  Additionally, 32% of UK IT professionals at enterprises report that their company is actively implementing generative AI and another 46% are exploring it.

The UK stands mid-ranking in global AI adoption (37%) at the enterprise level. Organisations in India (59%), China (50%), Singapore (53%), and the UAE (58%) are leading the way in the active use of AI, compared with lagging markets like Spain (28%), Australia (29%), and France (26%).

Two in five UK companies actively deploying or exploring AI have benefited from accelerating their rollout or investments in the past 24 months. However, UK enterprises lag other markets in AI acceleration (40%), China (85%), India (74%), and the UAE (72%) are the markets most likely to be accelerating AI rollout, while businesses in the UK (40%), Australia (38%) and Canada (35%) were the least likely to accelerate the rollout.

Enterprises which have overcome barriers and deployed or explored AI are already seeing the benefits and accelerating investments.

Research and development (43%) and augmenting human tasks with digital labour (39%) are the top AI investments at organisations exploring or deploying AI. Advances in AI tools that make them more accessible (51%), the need to reduce costs and automate key processes (37%), and the increasing amount of AI embedded into standard off-the-shelf business applications (36%) are the top factors driving AI adoption.

For UK IT professionals, the most important changes to AI in recent years are the increased prevalence of data, AI, and automation skills (43%), and solutions that are easier to deploy (38%). The top barriers hindering successful AI adoption at enterprises both exploring or deploying AI are limited AI skills and expertise (38%), high price (31%), too much data complexity (29%), lack of tools for AI model development (24%), ethical concerns (22%), missing the use cases defined or the end user research needed to get started (19%), and AI projects that are too difficult to integrate and scale (19%). UK organisations do not have employees with the right skills in place to use new AI or automation tools (24%) and 19% cannot find new hires with the skills to address that gap.

Only 32% are currently training or reskilling employees to work together with AI tools. The need for trustworthy and governed AI is understood by UK IT professionals, but barriers are making it difficult for British companies to put into practice: IT professionals agree that consumers are more likely to choose services from companies with transparent and ethical.

Michael Conway, Partner and Data, AI & Transformation Leader, IBM Consulting UK & Ireland said: “Our latest research shows that enterprises which have overcome barriers and deployed or explored AI are already seeing the benefits and accelerating investments. These findings suggest that more accessible AI tools, the need to automate key processes, and AI being increasingly embedded into business applications are the major drivers of AI adoption at the enterprise level,”  

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