Since the launch of ChatGPT in 2022, the world has been captivated by the power of generative Artificial Intelligence (AI). What was once a topic for tech conferences has become a fixture in business. AI has surpassed more than a market trend to become a global paradigm shift. Companies are pivoting to integrate AI into their operations, and nations are strategically drafting policies to secure their place in this new order.
As the head of the global SAP Labs Network, I watch closely as nations around the world innovate. In an evolving landscape, two titans are taking the lead in shaping the trajectory of AI: the United States and China. The U.S. continues to lead in foundational research and private-sector dynamism, China’s model offers a different playbook for rapid, state-guided advancement.
Decoding China’s AI Ascent
It wasn’t a single policy or breakthrough that allowed China’s AI ecosystem to advance quickly in so many fields. It was a concerted, multi-faceted strategy built on three core pillars.
- A Strategic Policy Engine: China’s government encourages and directs AI. The Next Generation Artificial Intelligence Development Plan of 2017 was a declaration of intent, setting a clear ambition for China to achieve global AI leadership by 2030. This top-down vision provides clear direction and mobilizes substantial funding, creating a powerful tailwind for both research and commercialization.
- A Powerful Infrastructure Backbone: AI needs data and immense computing power to thrive. Recognizing this, China made massive investments in its digital infrastructure. The rollout of the world’s largest 5G network in 2019 wasn’t just about faster phones but about creating a high-speed, low-latency foundation for the Internet of Things, smart cities, and autonomous systems, all powered by AI. Today, China has 4.4 million 5G base stations installed, nearly half of all stations globally and about 10 times of the number for all of EU or India.
- A Hyper-Focused Innovation Ecosystem: The Chinese government’s vision is brought to life through an ecosystem of tech hubs and domestic champions. The creation of an AI National Team spurred the hypergrowth of companies that are now global contenders, from established giants to newer players like DeepSeek. A defining characteristic of this ecosystem is its focus on real-world industry applications. China is now leading in granted AI patents, and we can see how IP creation translates into real-life applications – from intelligent manufacturing to recent breakthroughs in humanoid robotics.
Of course, this journey isn’t without its obstacles. China faces significant challenges, including US-led export controls on advanced semiconductors, the scepticism of the global AI talent pool to settle and work in China, and issues with data fragmentation. However, the country is actively implementing measures to build self-sufficiency and streamline data access. To ensure sustainable growth, the government has also made significant efforts in AI security governance and data supervision, culminating in the recent AI Plus Initiative, which lays out a clear development pathway to 2035.
China continues to push for global AI leadership by a mix of state-led initiatives and funding, a stringent regulatory framework development and by setting top-down long-term priorities. The future will tell how effective that strategy will overcome issues with regulatory flexibility, talent attraction and global trust in its AI systems.
Canada’s AI Landscape: A Pioneer’s Paradox
Canada holds a proud and unique position in the history of AI. It was the first country in the world to establish a national AI strategy, a testament to its foresight and pioneering spirit. This has translated into tangible strengths in strong governance and ethics, robust private investments, and data availability.
Canada consistently ranks high globally for its thoughtful approach to AI governance and ethics. The country excels in attracting private investment, fueling a dynamic startup scene. And Canada has created a solid framework for data access supports research and development.
However, a paradox has emerged. Despite this strong foundation, Canada faces challenges in broad-based AI training and public AI literacy. There are widespread concerns among citizens about the potential negative outcomes of AI, which can create a hesitant environment for adoption. While China embraces hyper-adoption, Canada grapples with apprehension.
Practical Steps for Canada’s AI Future: From Prudence to Action
Canada can adapt aspects of China’s framework while preserving its vital private-sector dynamism and democratic values. It can learn from China’s model and strategic execution. Canada can take three immediate actions to accelerate its AI deployment.
- Embrace Openness, Guided by Prudence: Canada’s cautious and ethical approach to AI is a global asset. This prudence must be paired with a greater spirit of openness and ambition. For example, the country could move the national conversation from “What are the risks?” to “How can we mitigate risks while seizing opportunities?” Choosing collaboration over apprehension is a strategic imperative worthy of deeper exploration.
- Foster Cross-Sector Partnerships for Application: China’s success is a powerful lesson in the synergy between state, industry, and academia. Canada can energize its own ecosystem by creating stronger incentives for cross-sector partnerships focused specifically on industrial application and commercialization. The brilliant research coming out of Canada’s universities could be connected with the tangible needs of manufacturing, natural resources, and healthcare sectors. Government-backed R&D and corporate innovation aren’t mutually exclusive. The right balance will accelerate commercialization.
- Answering the Call and Finding Canada’s Blue Ocean: This brings me to a final, open question for you—the innovators, policymakers, and business leaders of Canada. The time for passive observation is over. What steps can the great minds in Canada take to assess the current landscape and identify new opportunities – to find Canada’s own Blue Ocean?
China’s unified national top-down AI vision and its relentless focus on large-scale application can not to be copied elsewhere. Every nation should forge its own path—one that reflects its distinct priorities, societal values, and legal system. For example, Canada has a different but equally powerful set of ingredients: pioneering research, a strong ethical compass, and a dynamic private sector. By combining these strengths with a bold strategy refresh for adoption and collaboration, Canada can not only participate in the AI future but help lead it.
