Generative AI (Gen AI) is no longer a fleeting trend for finance teams.As companies like Amazon demonstrate, the technology is driving real-world transformations in productivity, compliance, and operational efficiency.A McKinsey report highlights that AI could unlock $4.4 trillion in productivity growth, but its success hinges on leadership and strategic integration .
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mckinsey.comMeanwhile, finance teams are grappling with outdated systems, with 90% still relying on spreadsheets for core operations, despite their limitations in handling modern payment complexities .
The finance sector is at a crossroads.Traditional tools like spreadsheets are ill-equipped to manage the surge in transaction volumes and regulatory demands, particularly under frameworks like DORA.Agentic AI, which combines reasoning with automation, is emerging as a critical solution.These systems can handle up to 95% of reconciliation tasks autonomously, freeing teams to focus on strategic work."The biggest barrier to success is leadership," notes the McKinsey report, emphasizing the need for bold AI adoption .
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mckinsey.comAmazon exemplifies this shift.As one of the first companies to harness AI's potential, Amazon has integrated generative tools into its supply chain, customer service, and financial operations.Its use of AI for demand forecasting and logistics optimization has reduced costs and improved efficiency, proving that AI can deliver measurable ROI."AI is like the internet many years ago," says the McKinsey report, "the risk for business leaders is not thinking too small" .
Microsoft's Copilot has become a case study in AI's transformative power.Early users report a 29% faster task completion rate, with 77% stating they wouldn't return to pre-Copilot workflows.In finance, this translates to quicker reconciliation, enhanced data analysis, and reduced manual errors.For example, Copilot users save 14 minutes daily on routine tasks, with 53% of time savings reinvested into high-impact work .
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microsoft.comThe finance industry is also adopting agentic AI to tackle compliance and risk management.AutoRek's whitepaper shows that AI-powered platforms leave auditable trails of activity, crucial for DORA compliance.These systems can detect anomalies in real-time, optimize cash forecasting, and provide predictive dashboards for emerging threats."Agentic AI closes the gap between operational demands and resource constraints," notes the report, enabling teams to meet rising transaction volumes without proportional headcount increases .
The shift to AI-driven workflows requires more than technology—it demands a cultural transformation.Finance leaders must act as "agent bosses," designing roles for AI agents and rethinking workflows.Microsoft's "work backwards" approach, which prioritizes customer needs in AI development, offers a blueprint for this.Similarly, THL's portfolio companies are fostering "copilot cultures" where employees across all levels experiment with AI tools to solve unique problems .
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thl.comAmazon's success underscores the importance of leadership in AI adoption.By investing in AI infrastructure and empowering teams to innovate, Amazon has maintained its competitive edge.As the McKinsey report warns, "the history of major economic shifts shows that such moments can define the rise and fall of companies." For finance teams, the lesson is clear: Gen AI is not a fad—it's a necessity for survival and growth.
Conclusion
From Amazon's logistics to Microsoft's Copilot, the finance sector is witnessing a paradigm shift.Agentic AI and generative tools are no longer optional; they are essential for navigating modern challenges.As McKinsey concludes, "the risk for business leaders is not thinking too small." The future belongs to those who embrace AI as a strategic lever, not just a technological novelty.