2024-12-16-毕马威-毕马威全球财务智能化调研报告（英）_24页_3mb

KPMG Global AI in Finance Report Summary

Core Content

The KPMG Global AI in Finance Report highlights the rapid transformation of finance functions through the integration of artificial intelligence (AI), emphasizing its impact on financial reporting, efficiency, and ROI. The report outlines the current state of AI adoption, the challenges faced, and the strategic steps needed to fully leverage AI in finance.

Key Findings

• AI Adoption Growth: In April 2024, 73% of companies across 10 major economies were using AI in financial reporting, with 100% expecting to do so within three years. By September 2024, the scope had expanded to include the entire finance function, including accounting, risk management, treasury, and tax operations.

• Global Reach: AI is becoming a global phenomenon, with adoption rates in emerging economies catching up to those in major markets. The gap is not substantial, indicating a worldwide shift.

• ROI and Benefits: AI is delivering significant ROI, with 57% of AI leaders reporting that ROI is exceeding expectations. Even among early adopters, nearly 30% are seeing better-than-expected returns. The benefits include faster, more accurate processes, reduced human error, and better decision-making through predictive analysis and real-time insights.

• Maturity Framework: KPMG developed an AI maturity framework based on survey responses, categorizing companies into three groups:

  • Beginners: 18% of respondents
  • Implementers: 58% of respondents
  • Leaders: 24% of respondents

• AI Use Cases: Leaders have more diverse use cases for AI, averaging six, compared to 3.6 for others. Key use cases include:

  • Research and data analysis (85% vs 46%)
  • Fraud detection and prevention (81% vs 46%)
  • Predictive analysis and planning (78% vs 45%)
  • Generative AI for document creation (75% vs 33%)
  • Risk management and cybersecurity (62% vs 27%)

• AI Investment Trends: Companies are investing in a range of AI technologies, with a growing focus on sophisticated tools like machine learning and generative AI. On average, companies are allocating about 8.5% of their IT budgets to AI, expected to rise to 13.5% in three years.

AI Leaders: Driving ROI and Innovation

• Leaders in AI Adoption: AI leaders are more advanced in AI usage and have a broader range of applications. They are more likely to:

  • Use Gen AI for dynamic reporting and scenario generation
  • Invest significantly in AI-related activities (nearly twice as much as others)
  • Establish governance frameworks and seek third-party assurance for AI processes
  • Implement AI in areas like risk management, tax compliance, and data entry

• Strategic Initiatives: Leaders are creating Centers of Excellence and fostering a culture of innovation. They prioritize AI governance, transparency, and ethical use, which helps build trust and ensures responsible AI implementation.

Barriers and Concerns

• Common Challenges:

  • Data Security: AI systems handling sensitive financial data are at higher risk of breaches.
  • Integration Complexity: Merging AI with cloud services and APIs can create vulnerabilities.
  • Skill Gaps: Over half of executives cite a lack of AI skills and talent as a barrier to adoption.
  • Cost Constraints: Many companies lack the budget or IT infrastructure to support AI initiatives.

• Gen AI Specific Risks:

  • Cybersecurity and Data Privacy: Gen AI's ability to process large datasets raises concerns about data breaches and misuse.
  • Bias and Misinformation: Gen AI may produce inaccurate or biased results due to its reliance on data patterns without full understanding of context.
  • Sustainability Impact: AI's high energy consumption is a growing concern, though it also offers opportunities for sustainability improvements.

Blind Spots in AI Adoption

• Overlooked Issues:
  • Transparency and Explainability: Companies tend to focus on privacy and data integrity but neglect the importance of explainability and accountability.
  • Sustainability: While AI can help reduce carbon footprints, it is also energy-intensive and needs careful management.

Shifts in Financial Reporting

• Rapid Progress: Financial reporting has seen significant AI adoption in the last six months, especially in Canada, Australia, and Japan.
• Regional Variations:
  • Major Markets: North America, Europe, and Asia-Pacific are leading in AI adoption.
  • Emerging Markets: Countries like China and India are ahead, while others in the Middle East, Africa, and Latin America lag behind.
• Gen AI in Reporting: Gen AI is becoming essential, with 56% of companies planning to use it for reporting in the future. Leaders are expected to use it widely in three years, with 95% planning to do so.

Role of Auditors

• Evolving Auditor Role: Auditors are expected to support companies in AI-related governance, risk management, and assurance.
• AI in Auditing: Auditors are using AI to enhance their own processes, offering smarter, real-time, and insight-driven audit experiences.
• Assurance Needs: Leaders are more likely to seek third-party assurance for AI processes, with over half gaining assurance on AI controls.

Key Recommendations

• Invest in AI: Companies should allocate more resources to AI initiatives, especially in the form of enterprise-wide investments.
• Develop AI Skills: Building internal and external AI capabilities is crucial for successful adoption.
• Prioritize Governance: Implementing robust AI governance frameworks ensures responsible and ethical use.
• Focus on Transparency: Addressing AI transparency and explainability will help build stakeholder trust.
• Enhance Sustainability Practices: AI should be integrated with sustainability goals to minimize its environmental impact.
• Leverage Gen AI: Companies should explore the potential of generative AI in financial reporting and other areas of finance.

Conclusion

AI is rapidly transforming the finance function, offering significant benefits in efficiency, accuracy, and decision-making. While challenges remain, the ROI and strategic advantages are compelling, and AI leaders are setting the pace for the future. Auditors play a critical role in supporting this transformation by providing governance, assurance, and transparency. As AI continues to evolve, organizations must prepare for its full potential by investing in skills, infrastructure, and ethical practices.