Organisations around the world are enthusiastically using and investing in the technology, and China is leading in the use of generative AI, according to a recent global study SAS commissioned with Coleman Parkes Research.
The study, conducted earlier this year, surveyed 1,600 respondents who make decisions on generative AI strategy or data analytics across the Americas, Europe and the Asia-Pacific regions.
Respondents in China report that 83% of their organisations are using the technology. That’s more than in the United Kingdom (70%), the United States (65%) and Australia (63%).
However, organisations in the United States are ahead in terms of maturity and having fully implemented generative AI technologies at 24% compared to China’s 19%, and the United Kingdom’s 11%.
“While China may lead in Generative AI adoption rates, higher adoption doesn’t necessarily equate to effective implementation or better returns,” said Stephen Saw, managing director at Coleman Parkes.
Results indicate that signal different regions are on board and starting to adopt generative AI in meaningful ways but at different rates.
“With any new technology, organisations must navigate a discovery phase, separating hype from reality, to understand the complexity of real-world implementations in the enterprise. We have reached this moment with generative AI,” said Bryan Harris, EVP and CTO at SAS.
“As we exit the hype cycle, it is now about purposefully implementing and delivering repeatable and trusted business results from generative AI,” said Harris.
When split into industry segments, the data shows banking and insurance leading other industries in terms of incorporating generative AI into daily business operations across a variety of metrics.
Ranked in terms of fully implementing generative AI and fully implementing it into regular business processes, the industries were banking (17%), telco (15%), insurance (11%), life sciences (11%), professional services (11%), retail (10%), public sector (9%), health (9%), manufacturing (7%), and energy and utilities (6%).
Departments inside organisations that are using or planning to use generative AI were ranked as follows — sales (86%), marketing (85%), IT (81%), finance (75%), and production (75%).
Results also show that early adopters are finding plenty of obstacles in using and implementing generative AI. First on the list 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 generative AI. Of respondents whose organisations have fully implemented generative AI, only 25% say they are extremely familiar with their 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.
Nine out of 10 senior technology decision makers overall admit they don’t fully understand generative AI and its potential to affect business processes.
At 45%, CIOs lead the way with executives who understand their organisation’s AI adoption strategy. But only 36% of CTOs say they’re fully in the know.
Yet, despite this understanding gap, most organisations (75%) say they have set aside budgets to invest in generative AI in the next financial year.
Other challenges organisations face include data and regulation.
Organisations’ IT leaders are mostly concerned about data privacy (76%) and data security (75%).
Only a tenth of organisations say they are fully prepared to comply with coming AI regulations. One-third that have fully implemented believe they can comply with regulations.
Only 7% are providing a high level of training on generative AI governance. And 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.
