While the world buzzes about the transformative power of artificial intelligence, a closer look reveals diverging paths in its adoption. The US is a research powerhouse, home to the generative AI breakthroughs. However, a different narrative is unfolding elsewhere, particularly in how these advancements are being integrated into the broader economy. Innovation doesn’t follow a single path. How AI evolves - and how we choose to integrate it - will shape industries, communities, and opportunities in unique ways.
Customer experience (CX) design has been at the forefront of this change. Almost every executive managing a CX or customer service process has had to fundamentally rethink how their part of the business operates. AI has become an essential tool in building a bridge between brands and customers. Although the most rapid change has only taken place in the past two years, innovation has taken place in a number of ways:
Generative AI chatbots: most customer service chatbots have been terrible in the past, but generative AI has provided a technology that allows them to genuinely be useful. However, they do not work out of the box, and many brands have made the mistake of overestimating what their bots can achieve - they need training, and they can’t handle every situation.
Agent onboarding and training: the use of automated tests, training, and simulation systems is making it much easier to get people ready for action in the customer service environment and then to continue supporting them with real-time coaching.
Agent support: many repetitive or manual tasks have been handed to AI, such as categorizing calls or taking notes so a call can be summarized. 'Next Best Action’ systems are listening to calls and helping agents by prompting the next best course of action - which the human agent can accept or ignore.
It is clear that across the entire connection between brands and customers, AI is reshaping the landscape - in customer-facing tools and inside the organization. However, companies are made up of a multitude of vertical and horizontal services that all contribute to the overall function of the business, whatever the industry. It should be possible to apply AI in all these different components of the business in a way that drives both productivity and innovation.
This is where I think that something interesting is happening in the world today. Most of the finance and activity related to AI research appears to be based in the USA. All the well-known language models and consumer-facing AI systems are from companies such as OpenAI, Amazon, Meta, or Google.
The US Department of Defense has dramatically increased their spending on AI systems over 2022 and 2023 - hundreds of new contracts each year have AI in the title. The US government and private sector are investing hundreds of millions of dollars - if not more - into R&D in this area. But look at the US Census Bureau Business Trends Outlook Survey - a sample of . It’s worth quoting the survey where they comment on AI adoption by American companies:
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1.2 million different US businesses
‘The highest adoption rate was 7.2% for firms with 250 or more employees, while the second-highest adoption rate was 5.5% for firms with one to four employees. Medium-sized firms, ranging from 5 to 249 employees, had lower adoption rates.’
Initially, I suspected that this data must be old. It’s from the Census Bureau, so it was probably from a survey undertaken years ago. However, the last update to the dataset was on May 8, 2025. This is up-to-the-minute data on a large set of American companies. The US is a powerhouse of AI research and innovation, but are American companies changing their business model and innovating because of the tools that are becoming available?
If we contrast this with China then there is a very different picture. Most of us based outside China only really know about DeepSeek when asked about AI in China. That’s the main Chinese AI tool that has really hit the headlines globally. OpenAI has accused DeepSeek of inappropriately copying ChatGPT. These are open accusations that I’m not going to offer my own opinion on here, but the really important point is not whether DeepSeek was original research or not. This is how DeepSeek - and AI more generally - is applied in China.
The Chinese government has taken the view that AI is a critical driver of economic growth and encouraged companies to investigate how they can improve productivity as well as developing new business models with AI. Government agencies and the private sector have all been rushing to develop new ideas using DeepSeek.
‘The government, companies, and investors in China share a common belief that China’s AI opportunity lies more in AI applications - services built on top of AI - rather than solely trying to make models larger to improve performance,’ Tilly Zhang, a technology analyst at Beijing-based research firm Gavekal Dragonomics, told Rest of World. This is a striking difference from the US experience. American companies are focused on developing and improving AI models, but Chinese companies are focusing on the application of AI to their government and corporate services. A SAS Institute survey in 2024 found that 83% of all Chinese companies are already using generative AI.
Although DeepSeek is the best-known Chinese system, there is a broader ecosystem of companies, such as Baidu, Tencent, and Alibaba, that are both investing in AI development and the application of AI to their existing business model. The CEO of Alibaba, Eddie Wu, said in February 2025 that his company plans to “aggressively invest” in the pursuit of AI that is equal to, or more advanced than, human intelligence.
These statistics are difficult to compare. There is no single study that is comparing different nations using the same survey, so it’s easy to point at one study or another when arguing about AI adoption by industry. But it cannot be denied that there is an excitement across Chinese businesses about AI that goes far beyond the technology sector alone - every business appears to be exploring how to redesign their company from the ground up. This is the key point. The US has been leading in AI research for many years, but what happens if American companies just don’t adopt the technology, or are slow to adopt it? Will consumers care?
Sometimes, there is a technological possibility that is delayed because consumers are not interested. Autonomous vehicles is a recent example. If more consumers were more excited about the prospect of driverless taxis, then they would probably already be in every major city. They are rolling out gradually, but are often mired in questions about who is liable when there is an accident.
The American companies undertaking world-leading AI research need to help more general non-tech industries understand the opportunities that AI presents. At present, it feels like productivity and efficiency gains are the main focus in the boardroom. A wide variety of industries could take a lesson from CX leaders to explore ideas such as:
Reframing AI as a revenue generator, not just a cost saver
AI creating entirely new business models or services
Embedding AI to constantly monitor for competitive risk
AI can constantly monitor for data security risks
Existing real world case studies - such as retailers using dynamic pricing or manufacturers using predictive maintenance
Connect AI possibilities to the long-term vision of the business - thinking several years into the future
Using AI innovation to attract the best talent to your business
Chinese companies have been encouraged to rapidly adopt AI, but the US still has the leading-edge research that is developing the global future for AI. The tech sector just needs to work harder to ensure there is a more general adoption of AI as a tool that can transform any business
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