China and the UK are leading generative AI adoption across the world, according to a recent global study by SAS commissioned by Coleman Parkers Research Ltd.

Business decision makers in China report that 83% of their organisations are using the emerging technology. This is followed by the UK (70%), which is outpacing the US (65%) and Australia (63%).

But this is not the full story. Organisations in the US are ahead in terms of maturity and having fully implemented GenAI technologies at 24% compared to China’s 19% and the UK’s 11%.

What does this mean in terms of the global economic impact on AI and GenAI? In a 2023 report, McKinsey estimated GenAI could add the equivalent of $2.6 trillion to $4.4 trillion annually across a variety of use cases.

That’s comparable to the entire GDP of the UK in 2021. This impact would increase the overall influence of AI by 15% to 40%.

Considering these economic implications, SAS and Coleman Parkes targeted 1,600 decision makers across key global markets. Respondents work in a range of industries including banking, insurance, the public sector, life sciences, healthcare, telecommunications, manufacturing, retail, energy and utilities, and professional services.

The smallest organisation surveyed employed a workforce of 500-999 people, and the largest employed more than 10,000.

“While China may lead in GenAI adoption rates, higher adoption doesn’t necessarily equate to effective implementation or better returns,” said Stephen Saw, Managing Director at Coleman Parkes. “In fact, the US nudges ahead in the race with 24% of organisations having fully implemented GenAI compared to 19% in China.”

When it comes to regions fully using and implementing generative AI into their organisation’s processes, North America leads with 20%. This is followed by Asian Pacific and Asturalia (APAC) at 10%, and Latin America at 8%. Northern Europe and South West and Eastern Europe round out the back with 7% in each.

The regions that have implemented GenAI use policies do not match this pattern – APAC leads (71%), followed by North America (63%), SW and Eastern Europe (60%), Norther Europe (58%), and Latin America (52%).

Further, early adopters are continually finding roadblocks and obstacles in using and implementing GenAI across their services and tech stack.

The top challenge organisations face when implementing GenAI is the lack of a clear strategy. Only 9% of leaders responding to the survey indicate they are extremely familiar with their organisation’s adoption of GenAI. Of respondents whose organisations have fully implemented GenAI, only 25% say they are extremely familiar with their organisatons GenAI adoption strategy.

Even those decision makers responsible for technology investment decisions aren’t familiar with AI – including those at organisations that are ahead of the adoption curve.

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Nine out of ten senior technology decision makers overall admit they don’t fully understand GenAI and its potential to affect business processes. At 45%, CIOs lead the way with executives who say they understand their organisation’s AI adoption strategy, but only 36% of CTO say they are fully in the know.

Despite this understanding gap, most organisations (75%) say they have set aside budgets to invest in GenAI in the next financial year.

Organisations also face challenges in acquiring enough data to fine tune large language models (LLMs). They also realise – once they are deep into deployment – they lack the appropriate tools to successfully implement AI. Organisations’ IT leaders are mostly concerned about data privacy (76%) and data security (75%).

Further, only a tenth of organisations say they are fully prepared to comply with coming AI regulations. One third of organisations that have fully implemented believe they can comply with regulations.

Only 7% are providing a high level of training on GenAI governance. Plus, only 5% have a reliable system in place to measure bias and privacy risks in LLMs.

Although there are obstacles, some early adopters have experienced meaningful benefits already: 89% report improved employee experience and satisfaction; 82% say they’re saving operational costs; and 82% state customer retention is higher.