2025年新时代财务管理_AI与新兴技术赋能财务与会计变革报告（英文版）-德勤_IMA_32页_3mb

Next-gen Controllership: AI and Emerging Technology Transformations

Deloitte's Center for Controllership and IMA conducted global research, surveying over 900 professionals, to explore AI and emerging technologies' impact on finance and controllership.

1. AI and Finance

• AI Overview: AI, from traditional systems to Generative AI (GenAI), enables enhanced analytics, automation, and strategic insights.
• Key Findings:
  • 73% anticipate AI implementation doubling in controllership over three–five years; automation enablement and data analysis lead benefits.
  • Top GenAI use cases: automating financial tasks (e.g., journal entries); improving close processes.
  • Challenges: system integration (19%), skill shortages, data quality, funding, and governance.
• Implementation: Requires cross-functional involvement, clear roles, and long-term risk governance. A strong AI risk management framework (e.g., Deloitte’s Trustworthy AI) centers on safety, privacy, accountability, transparency.
• Future Trends: AI convergence with process automation, data analytics, and cloud systems (e.g., Snowflake, Azure).

2. Beyond AI: Emerging Tech

• Data Location & Management: Cloud-based tools (AWS, SAP) and data mesh approaches are rising, reducing reliance on legacy ERP.
• Process Automation: Tools like PowerBI, SQL, and RPA streamline financial workflows; Deloitte sees AI’s role in hyper-personalizing automations.
• Data Analytics: AI-integrated tools (e.g., Tableau, PowerBI) for predictive analytics and GenAI-driven automated visualizations.

3. Controllership Evolution

• Role Shift: From “guardian” to strategic enabler, requiring controllers to engage deeply in tech planning.
• Skills Demand: Critical thinking (68%) > self-sufficiency (58%) > technology (17%). Training priority: data analytics (25%) and AI literacy (22%).
• Impact: AI reduces monotony (automation), enhances decision-making (predictive analytics), and unlocks new business opportunities (GenAI tools).

4. Action Framework

• Thrive in Transformation:
  • Leadership Involvement: Finance leaders must drive strategy while IT partners on implementation.
  • Roadmap Steps: Explore, design, build, test, deploy, with continuous monitoring and governance.
  • AI Integration: Embed safety, transparency, and accountability into AI workflows to build trust and regulatory compliance.
• Key Takeaways: Controllers must champion tech adoption, prioritize human skills, and mitigate AI risks to secure competitive advantage.

Conclusion: Technology convergence (AI, automation, analytics) reshapes controllership, demanding proactive leadership, enhanced skills, and trustworthy AI frameworks for sustainable success.