罗兰贝格-人工智能：欧洲初创企业的一个策略（英文）-2018.7-32页

Summary of "Artificial Intelligence - A Strategy for European Startups"

Core Content

This report provides an analysis of the global and European AI startup landscape, highlighting the need for a unified European strategy to foster AI innovation and competitiveness. It outlines the current state of AI development, identifies key challenges, and presents recommendations for policymakers to support the growth of European AI startups.

Main Findings

• Global AI Startup Landscape:
  The United States leads with 40% of all AI startups (1,393), followed by China (11%) and Israel (10%). Europe ranks second with 22% of AI startups (769), but no single country reaches critical mass.

• Sector Representation:
  B2B services dominate the AI startup sector globally and in Europe (70% in Europe, 64% worldwide). However, major European industries such as energy, automotive, real estate, agriculture, and public administration are underrepresented in AI startups.

• Technology Focus:
  Core AI (research-driven) accounts for 10% of European startups, matching the global average. Applied AI technologies like robotics, IoT, and self-driving cars are also underrepresented in Europe compared to global expectations.

• Ecosystem Challenges:
  Europe lacks a unified AI strategy and faces fragmentation in talent, capital, and research. Unlike the US and China, which have strong digital infrastructure and government support, Europe has not yet created a cohesive AI ecosystem.

Key Challenges for Europe

1. Fragmentation:
   Europe is composed of 28 countries, none of which individually have a significant presence in the global AI startup scene.

2. Industry and Technology Lag:
   Traditional European industries are not adequately represented in the AI startup ecosystem, raising concerns about their ability to adapt to future technological shifts.

3. Limited Investment and Support:
   European AI startups face challenges in accessing sufficient funding and tailored support mechanisms. The investment culture in Europe is more cautious than in North America.

Recommendations for Europe

1. Create YES! (Young European Startup) Status

• Objective: To create a pan-European framework that supports the growth of AI startups.
• Actions:
  • Define a distinct "YES!" status that recognizes the unique needs of AI startups.
  • Align fiscal and social arrangements across the EU to favor AI development.
  • Standardize share distribution mechanisms, inspired by the French BSPCE system.
  • Establish a unified fiscal regime for startups, potentially through Eurozone cooperation.

2. Invest YES!

• Objective: To enable AI startups to scale up and remain competitive within Europe.
• Actions:
  • Increase investment in AI startups, especially in the early stages.
  • Support startups with dedicated funding, incubation, and communication programs.
  • Provide access to EU and national funding through mechanisms like the European Tech Pass.
  • Facilitate internationalization and attract foreign talent with visa support.

3. Create One-Stop Shops in a European Network of Incubators and Accelerators

• Objective: To streamline regulatory and support information for AI startups across Europe.
• Actions:
  • Establish "one-stop shops" in every EU country, providing information on tax, labor, IP, consumer protection, and data privacy.
  • Finance these shops through the European Regional Development Fund (ERDF).
  • Locate them within selected incubators and accelerators, forming a "European Tech Network."
  • Ensure each Member State commits to setting up such shops within their national incubator systems.

Conclusion

Europe has the potential to become a third major player in the global AI race, but it must act decisively to overcome its current fragmentation and underrepresentation in key industries and technologies. A unified AI strategy, supported by tailored funding mechanisms and a robust ecosystem, is essential for Europe to foster innovation, attract investment, and maintain a competitive edge against the US and China.