Leaders note that there is concern about a lack of understanding, business strategy, as well as a lack of data and readiness for regulation; data privacy, security and governance are primary challenges
Generative artificial intelligence (GenAI) is a reality that will not go away. Organizations around the world are enthusiastically using the technology and investing in it, but which regions and countries are leading the way in using GenAI? China leads in that domain, according to a recent global study commissioned by SAS with Coleman Parkes Research Ltd. Chinese business decision makers reported that 83% of their organizations use GenAI, higher than the UK (70%), US (65%) and Australia (63%). However, organizations in the US are the leaders when it comes to maturity, and have fully implemented GenAI technologies (24%) compared to 19% in China and 11% in the UK.
What does this mean in terms of the global economic impact of AI and GenAI? In a 2023 report, McKinsey estimates that GenAI could add between $2.6 billion and $4.4 billion in value per year across various use cases. This is comparable to the entire GDP of the United Kingdom in 2021. That impact would increase the overall effect of artificial intelligence by 15% to 40%.
Considering these economic implications, SAS and Coleman Parkes conducted a survey on a sample of 1,600 decision makers in key world markets. Respondents work in a variety of industries, including banking, insurance, public sector, life sciences, healthcare, telecommunications, manufacturing, retail, energy and utilities, and professional services. The smallest organizations that participated in the research employed on average between 500 and 999 people, and the largest more than 10,000.
Learn more at complete research report i interactive data dashboard.
World regions thrive with GenAI
Some global survey results include indicators that different regions have started to deploy and are beginning to adopt GenAI in meaningful ways, but at different speeds.
“With any new technology, organizations must navigate the research and discovery phase, and separate the hype from the reality, to understand the complexities of real-world, enterprise-level implementation.” That’s exactly where we’ve come with GenAI,” says Brian Harris, Executive Vice President and CTO at SAS, who adds, “As we emerge from turbulent cycles, we need to apply GenAI purposefully and achieve repeatable and reliable business results with that technology.”
What is the order of the region when it comes to the full use and application of generative AI in the processes of their organizations?
- North America: 20%
- Asia and the Pacific: 10%
- Latin America: 8%
- Europe: 7%
Which regions have implemented GenAI usage policies?
- Asia and the Pacific: 71%
- North America: 63%
- Europe: 59%
- Latin America: 52%
To what extent do those planning to invest in GenAI in the next financial year have a dedicated budget?
- Asia Pacific: 94%
- Europe: 91%
- North America: 89%
- Latin America: 84%
Note: North America includes the United States and Canada; Latin America includes Brazil and Mexico; Europe includes the United Kingdom/Ireland, Sweden, Norway, Finland and Denmark; France, Germany, Italy, Benelux, Spain and Poland; and Asia Pacific includes Australia, China, Japan and the United Arab Emirates/Saudi Arabia.
Industries and functional sectors are adopting GenAI at different rates
Sabine VanderLinden, CEO and investment partner at Alchemy Crew sees great potential for industries investing in GenAI. “The future of business is being reshaped by GenAI,” she says, adding, “Indeed, the integration of GenAI into business processes—from dynamic marketing profiling to accurate claims underwriting—offers unparalleled opportunities for efficiency, personalization, and strategic forecasting. Embracing this technology is essential for businesses that want to keep pace in a highly uncertain, unpredictable and competitive market.”
When it comes to industry segments, the data shows that banking and insurance lead other industries in terms of integrating GenAI AI into daily business according to various measures. Below are some highlights.
What is the order of specific industries in terms of the full application of GenAI – and its full application in regular business processes?
- Banking: 17%
- Telecommunications: 15%
- Insurance: 11%
- Living Systems Sciences: 11%
- Professional services: 11%
- Retail: 10%
- Public sector: 9%
- Health: 9%
- Production: 7%
- Energy and utilities: 6%
Which industries indicate that they already use GenAI to some extent on a daily basis?
- Telecommunications: 29%
- Retail: 27%
- Banking: 23%
- Professional services: 23%
- Insurance: 22%
- Life Sciences: 19%
- Health care: 17%
- Energy and utilities: 17%
- Production: 16%
- Public sector: 13%
Which departments/services within organizations use or plan to use GenAI?
- Sales: 86%
- Marketing: 85%
- IT: 81%
- Finance: 75%
- Production: 75%
The so-called “early adopters” encounter many obstacles in the use and implementation of GenAI
First on the list of challenges that organizations face in the regular use of GenAI is the lack of a clear GenAI strategy.
Only 9% of the leaders who responded to the survey indicated that they were extremely familiar with the adoption of GenAI in their organization. Among respondents whose organizations have fully implemented GenAI, only 25% say they are extremely familiar with their organization’s GenAI adoption strategy. Even the decision makers tasked with making technology investment decisions are unfamiliar with AI – including those at organizations at the forefront of technology adoption.
Ninety percent of senior technology decision makers overall admit they do not fully understand GenAI and its potential to impact business processes. At 45%, CIOs lead the way among executives who understand their organization’s AI adoption strategy. But only 36% of CTOs say they are fully aware of such a strategy.
Yet despite this gap in understanding, most organizations (75%) say they have budgeted for investment in GenAI in the next financial year.
Other challenges that organizations face are, among others:
As organizations gradually adopt GenAI, they realize they don’t have enough data to “fine tune” large language models (LLMs). They also realize, when they get deeper into the implementation, that they lack the proper tools to successfully implement AI. IT staff of organizations mostly care about data privacy (76%) and data security (75%).
Only 10% of organizations say they are fully prepared to comply with upcoming AI regulations. A third of organizations that have fully implemented AI believe they can comply with regulations. Only 7% provide a high level of training on GenAI management. And only 5% have a reliable system for measuring system errors and privacy risks in LLMs.
Although there are obstacles, some “early adopters” have already realized significant benefits: 89% cite improved employee experience and satisfaction; 82% say they have saved on business costs; and 82% say customer retention is higher.
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