Technology Diffusion

Canada may reach its AI adoption target and still miss its promised productivity gains. Delivering those gains will require deep adoption by large firms, supported by regulatory certainty and stronger tax treatment for AI deployment.

Building factories is not the same as achieving lasting industrial strength. Korea should design its “Three Megaprojects” as reference factories that give suppliers the testing, qualification, and commercial track records needed to win customers around the world.

Canada’s new AI strategy sets the right goal but focuses on the wrong problem: lowering costs when most firms struggle to identify valuable uses for AI. Ottawa should help businesses find and implement the right tools, not simply subsidize their purchase.

Korea should use its AI-memory windfall to finance the shared capabilities, research infrastructure, and commercialization pathways needed to create the next boom. The Future Response Fund should address enduring commercialization gaps, not create permanent spending commitments.

Canada funds university research but gives universities too little reason to turn that into Canadian firms, patents, and industrial capacity. To better align their incentives with national goals, funding should flow in part on standardized commercialization outcomes, with universities left to decide how to deliver them.

The right goal for Korea is not an AI tax, but an AI diffusion strategy paired with sound tax reform. The government should help firms adopt AI, help workers transition, and make sure productivity gains are broadly shared, without making the use of AI itself more expensive.

In the AI economy, competitive advantage will depend less on memorizing information and more on the ability to question intelligent systems, identify errors, and refine outputs. Korea’s education system should adapt to prepare students for workplaces where managing AI-generated mistakes is more valuable than speed of recall.

As Korea moves toward its goal of commercializing Level 4 autonomous driving by 2027, the central constraint may not be technological readiness but whether the government reforms the mobility market in advance. Without regulatory changes, Korea risks deploying advanced autonomous vehicles within a closed, taxi-centered system.

Opposition to AI automation at the Canada Revenue Agency misses the point. Smarter systems can improve targeting, boost compliance, and deliver better results with fewer resources than a labour-intensive enforcement model.

As Korea’s labor debate moves into digital policy, unions risk harming workers in the next generation of industries by prioritizing protections for existing jobs over preparing workers for technological transition.