2024-10-13-麦肯锡-是时候下注了_欧洲的人工智能机会（英）_15页_773kb

Summary of "Time to place our bets: Europe's AI opportunity"

Core Content

This report by QuantumBlack, AI by McKinsey, evaluates Europe's position in the emerging generative AI (gen AI) economy. It outlines a three-lens approach—adoption, creation, and energy—to assess Europe's competitiveness and provides strategic recommendations for leveraging gen AI's potential.

Main Points

1. Adoption of Gen AI

• Europe lags behind the US in AI and IT spending by 45–70% across sectors.
• Gen AI adoption is where most of the economic value lies, and Europe is missing out on significant productivity gains.
• McKinsey estimates that gen AI could boost European labor productivity by up to 3% annually through 2030.
• Current adoption rates show that only 30% of European companies have adopted gen AI in at least one business function, compared with 40% in the US.
• Reskilling and upskilling the workforce is critical to support gen AI adoption. Europe would need to reskill 12 million workers by 2030.
• Workforce skills will shift, with increased demand for technological skills and decreased demand for basic cognitive skills.

2. Creation of Gen AI Technologies

• Europe is competitive in four segments of the gen AI value chain:
  • AI semiconductor equipment (80–90% market share in extreme ultraviolet lithography)
  • AI applications (home to several unicorns like DeepL, Synthesia, and Wayve)
  • AI services (15% global market share)
  • AI semiconductor design (15% market share in integrated design-manufacturing)
• However, Europe is underrepresented in four other segments:
  • Raw materials (<5% market share)
  • AI semiconductor design (<2%)
  • AI semiconductor manufacturing (<1%)
  • Cloud infrastructure and supercomputers (<5%)
• US leads in most areas, particularly in foundation models (61 notable models vs. 25 in Europe) and cloud infrastructure.
• Europe's challenge lies in the lack of investment and market share in these critical segments, which could limit its ability to innovate and capture value.

3. Energy for Gen AI

• Gen AI is expected to increase electricity demand in Europe by 5% by 2030, equivalent to 180 terawatt-hours.
• Data centers are major energy consumers, with a single hyperscaler's data center using as much power as 80,000 households.
• European electricity prices are higher than in the US, making data centers less competitive for hosting gen AI applications.
• Europe has a strong position in clean energy, with 61% of low-carbon sources in its electricity mix, compared with 40% in the US and 34% in China.
• The aging power grid (45–50 years old) poses challenges for efficient electricity distribution.

Key Recommendations

For Adoption

• Reskill and upskill the workforce to meet the demand for technological skills.
• Encourage partnerships between universities and businesses to align education with industry needs.
• Support reskilling mechanisms and ensure access to training programs.
• Accelerate AI use across industries by increasing awareness and integration.

For Creation

• Increase public and private investment in AI, particularly in gen AI.
• Leverage existing investment vehicles like the InvestEU Fund to build AI infrastructure.
• Boost private capital through pension funds and insurers by simplifying regulations and increasing allocations.
• Focus on emerging semiconductor technologies like quantum and neuromorphic computing to leapfrog the US.
• Promote innovation in AI applications and services to capture more market share.

For Energy

• Invest in energy infrastructure to meet rising demand from data centers.
• Improve energy price competitiveness through policy reforms and market mechanisms.
• Enhance the efficiency of the power grid to support the growing AI workload.
• Utilize Europe's clean energy advantage to reduce the environmental impact of AI growth.

Strategic Importance

• Gen AI's potential for Europe is substantial, with an estimated $575.1 billion added to the European economy by 2030.
• Europe's strategic autonomy is at risk due to its reliance on US-based cloud providers and semiconductor manufacturing.
• A holistic approach that integrates adoption, creation, and energy is necessary for Europe to fully capitalize on gen AI's opportunities.

Conclusion

Europe has the potential to become a major player in the gen AI economy, but it must address significant gaps in investment, talent, and infrastructure. By focusing on a three-lens strategy, Europe can unlock the full economic value of gen AI and position itself as a leader in the next wave of technological innovation.