KUALA LUMPUR (July 10, 2024) – Generative AI is here to stay. Organizations around the world are enthusiastically using and investing in the technology. But what regions and countries are leading in the use of GenAI? China is in the lead according to a recent global study SAS commissioned with Coleman Parkes Research Ltd. China business decision makers report that 83% of their organizations are using the technology. That’s more than in the United Kingdom (70%), the United States (65%) and Australia (63%). But organizations in the United States are ahead in terms of maturity and having fully implemented GenAI technologies at 24% compared to China’s 19%, and the United Kingdom’s 11%.
What does this mean in terms of the global economic impact of 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 United Kingdom in 2021. This impact would increase the overall influence of artificial intelligence 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, health care, telecommunications, manufacturing, retail, energy and utilities, and professional services. The smallest organizations surveyed employed a workforce of 500 – 999 people, and the largest employed more than 10,000.
Learn more in the full research report and an interactive data dashboard.
“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 organizations having fully implemented GenAI compared to 19% in China.”
Global regions charge ahead with GenAI
Highlights from the global survey results include indicators that signal different regions are on board and starting to adopt GenAI in meaningful ways but at different rates.
“With any new technology, organizations 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, Executive Vice President and CTO at SAS. “As we exit the hype cycle, it is now about purposefully implementing and delivering repeatable and trusted business results from GenAI.”
Where do regions rank in fully using and implementing generative AI into their organization’s processes?
- North America: 20%
- APAC: 10%
- LATAM: 8%
- Northern Europe: 7%
- South West and Eastern Europe: 7%
Which regions have implemented GenAI use policies?
- APAC: 71%
- North America: 63%
- South West and Eastern Europe: 60%
- Northern Europe: 58%
- LATAM: 52%
To what extent do those planning to invest in GenAI in the next financial year have a dedicated budget?
- APAC: 94%
- Northern Europe: 91%
- South West and Eastern Europe: 91%
- North America: 89%
- LATAM: 84%
Note: North America comprise the United States and Canada; LATAM includes Brazil and Mexico; Northern Europe includes United Kingdom/Ireland, Sweden, Norway, Finland, Denmark; South West and Eastern Europe is France, Germany, Italy, Benelux, Spain and Poland; and APAC encompasses Australia, China, Japan and the United Arab Emirates/Saudi Arabia.
Industries and functional divisions embrace GenAI at varying rates
Sabine VanderLinden, CEO and Venture Partner, Alchemy Crew, sees much potential for industries investing in GenAI. “The future of business is being reshaped by generative AI,” she said. “Indeed, the integration of GenAI into business processes – from dynamic profiling in marketing to precision claims insurance – offers unparalleled opportunities for efficiency, personalization, and strategic foresight. Embracing this technology is essential for staying ahead in a highly uncertain and unpredictable competitive market.”
When split into industry segments, the data shows banking and insurance leading other industries in terms of incorporating GenAI AI into daily business operations across a variety of metrics. Highlights from those findings are below.
How do specific industries rank in terms of fully implementing GenAI and fully implementing it into regular business processes?
- Banking: 17%
- Telco: 15%
- Insurance: 11%
- Life sciences: 11%
- Professional services: 11%
- Retail: 10%
- Public sector: 9%
- Health: 9%
- Manufacturing: 7%
- Energy and utilities: 6%
Which industries indicate they already use GenAI daily to some extent?
- Telco: 29%
- Retail: 27%
- Banking: 23%
- Professional services: 23%
- Insurance: 22%
- Life sciences: 19%
- Health care: 17%
- Energy and utilities: 17%
- Manufacturing: 16%
- Public sector: 13%
Which departments inside organizations are using or planning to use GenAI?
- Sales: 86%
- Marketing: 85%
- IT: 81%
- Finance: 75%
- Production: 75%
Early adopters are finding plenty of obstacles in using and implementing GenAI
No. 1 on the list of challenges organizations face in putting GenAI to routine use is the lack of a clear GenAI strategy.
Only 9% of leaders responding to the survey indicate they are extremely familiar with their organization’s adoption of GenAI. Of respondents whose organizations that have fully implemented GenAI, only 25% say they are extremely familiar with their organization’s GenAI adoption strategy. Even those decision makers responsible for technology investment decisions aren’t familiar with AI – including those at organizations that are ahead of the adoption curve.
Nine out of 10 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 understand their organization’s AI adoption strategy. But only 36% of Chief Technology Officers (CTOs) say they’re fully in the know.
Yet despite this understanding gap, most organizations (75%) say they have set aside budgets to invest in GenAI in the next financial year.
Other challenges organizations face include:
- Data
As organizations adopt GenAI, they realize they have insufficient data to fine tune large language models (LLMs). They also realize – once they’re deep into deployment – they lack the appropriate tools to successfully implement AI. Organizations’ IT leaders are mostly concerned about data privacy (76%) and data security (75%).
- Regulation
Only a tenth of organizations say they are fully prepared to comply with coming AI regulations. One third of organizations that have fully implemented believe they can comply with regulations. Only 7% are providing a high level of training on GenAI 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.
