2017年-数据局_普华永道：抓住机遇2017夏季达沃斯论坛报告_28页_947kb

Sizing the Prize: AI's Value for Business and How to Capitalise

Core Content

This report explores the transformative potential of artificial intelligence (AI) for global economies and businesses, highlighting the opportunities and challenges associated with its adoption. It outlines the economic impact of AI, identifies the sectors and regions with the greatest potential, and discusses the strategic implications for enterprises.

Main Points

• Global Economic Impact:
  AI is expected to contribute up to $15.7 trillion to global GDP by 2030, representing a +14% boost. This includes $6.6 trillion from productivity gains and $9.1 trillion from increased consumer demand due to AI-enhanced products and services.

• Regional Impact:

  • China is projected to see the largest GDP boost (up to +26%), driven by its manufacturing-centric economy and high rate of capital reinvestment.
  • North America is expected to experience significant gains as well, but likely at a slightly slower pace than China due to its more advanced technological infrastructure.
  • Both regions are likely to lead in AI adoption, but emerging markets could leapfrog more developed economies in the long term.

• Sector Impact:
  The biggest gains will occur in retail, financial services, and healthcare, where AI can increase productivity, improve product quality, and enhance personalisation.

• AI Types and Capabilities:
  AI can be categorised into four types:

  • Automated Intelligence: Automating tasks, both manual and cognitive.
  • Assisted Intelligence: Enhancing human performance through AI tools.
  • Augmented Intelligence: Supporting better decision-making.
  • Autonomous Intelligence: Enabling machines to make decisions without human intervention.

• Economic Model:
  The report uses a dynamic economic model based on the Global Trade Analysis Project (GTAP) database to estimate AI's impact on the global economy. It is important to note that the results reflect the potential size of the economic prize, not direct growth predictions.

• Job Market Impact:
  While AI may displace some jobs, it will also create new employment opportunities, particularly in areas such as data management, AI development, and regulation.

• Consumer Demand and Productivity:
  AI will initially boost productivity by automating and augmenting existing processes. Over time, it will drive increased consumer demand through improved product quality and personalisation, leading to a virtuous cycle of innovation and growth.

Key Sectors and Use Cases

Healthcare

• High Potential Use Cases:
  • Diagnosis support: AI can detect small variations in health data and compare them with similar cases, leading to faster and more accurate diagnoses.
  • Pandemic tracking: Early identification and containment of diseases.
  • Imaging diagnostics: Radiology and pathology can be enhanced with AI tools.
• Consumer Benefits:
  • Faster and more accurate diagnosis.
  • Personalised treatment plans.
  • Long-term breakthroughs in intelligent implants.
• Time Saved:
  • More effective prevention reduces illness and hospitalisation.
  • Faster detection allows for earlier intervention.
• Timing:
  • Ready to go: Medical insurance and smarter scheduling.
  • Medium-term: Data-driven diagnostics and virtual drug development.
  • Longer-term: Robot doctors for diagnosis and treatment.
• Barriers:
  • Privacy concerns with sensitive health data.
  • Need for further technological development and regulatory acceptance.

Automotive

• High Potential Use Cases:
  • Autonomous fleets: Ride-sharing services can benefit from on-demand vehicle access.
  • Semi-autonomous features: Driver assist technologies.
  • Predictive maintenance: Engine monitoring and autonomous maintenance.
• Consumer Benefits:
  • Increased flexibility and convenience with on-demand mobility.
  • Time saved from not having to drive manually.
• Time Saved:
  • The average American spends nearly 300 hours a year driving.
• Timing:
  • Ready to go: Automated driver assistance systems.
  • Medium-term: On-demand parts manufacturing and maintenance.
  • Longer-term: Predictive and autonomous maintenance.
• Barriers:
  • Technology development challenges, such as safe operation in extreme weather.
  • Need to gain consumer trust and regulatory approval.

Financial Services

• High Potential Use Cases:
  • Personalised financial planning: Tailoring solutions to individual needs.
  • Fraud detection and anti-money laundering: Enhancing security and compliance.
  • Process automation: Both back-office and customer-facing operations.
• Consumer Benefits:
  • More customised and holistic financial solutions.
  • Adaptability to changing consumer needs.
• Timing:
  • Ready to go: Robo-advice, automated insurance underwriting, and robotic process automation.
• Barriers:
  • Integration challenges and regulatory compliance.

Strategic Implications

• Investment Timing:
  Businesses should target AI investments based on the potential impact and timing of adoption. Some areas are already ready for implementation, while others require further development and consumer trust.

• Competitive Advantage:
  Early adopters of AI will gain a significant edge over competitors, particularly in sectors where AI can enhance personalisation and improve efficiency.

• Risk and Sensitivity Testing:
  The report acknowledges that the speed of AI adoption and product quality changes could affect the distribution of global growth. Future assessments will explore these scenarios in detail.

• Collaboration and Innovation:
  As AI becomes more integrated into business operations, collaboration between humans and machines will drive new innovations and business models.

Conclusion

AI is a game changer with the potential to significantly boost global GDP and reshape industries. Businesses must act strategically to capitalise on AI opportunities, invest in the right technologies, and secure talent and data access. The AI Impact Index provides a framework for identifying where and when to invest, and the report highlights the importance of responsible and transparent AI development to maintain stakeholder confidence.