Despite widespread optimism about the transformative potential of agentic AI, a significant hurdle to its widespread adoption in the finance and accounting sectors has emerged: a lack of trust. While a recent Deloitte Center for Controllership™ poll reveals that over 80% of professionals believe AI-powered tools will become standard within five years, only a fraction of organizations are currently deploying agentic AI.
Agentic AI, which can autonomously complete tasks and make decisions without constant human oversight, promises unprecedented efficiency, enhanced data analysis, and improved accuracy. Early adopters are seeing benefits like reduced loan processing costs by 80% and 50% faster payment processing, highlighting the technology’s immense potential. However, the path from pilot to production is proving to be complex, with trust identified as the top barrier, cited by 21.3% of polled professionals.
The concerns surrounding trust are multi-faceted. Professionals worry about the reliability and transparency of autonomous decision-making, particularly when it involves sensitive financial data and critical operations. There’s a prevailing sentiment that while agentic AI can make decisions within a defined framework, human judgment remains indispensable for complex scenarios. “Trust is the cornerstone of any successful AI implementation in finance and accounting,” states Court Watson, a Controllership & Treasury Transformation leader at Deloitte & Touche LLP. “While the potential benefits of agentic AI are immense, agentic tools are not perfect and require special safeguards to make them more trustworthy.”
Beyond trust in the technology itself, other significant challenges include the integration of AI into existing, often antiquated, systems (20.1%) and a dearth of skilled personnel to operate and manage these advanced AI agents (13.5%). The evolving regulatory landscape also presents a quandary, with a lack of specific guidance for autonomous financial agents creating uncertainty and caution among institutions.
To bridge this trust gap, experts emphasize the need for a complete approach. This includes building trust into AI tools from inception, establishing clear policies and controls throughout the AI lifecycle, and defining roles and responsibilities for human oversight. Transparency, explainability, fairness, and robust security measures are paramount. As financial institutions navigate this new era, the focus is not just on technological capability, but on fostering a culture of trust and responsible AI deployment to unlock the full potential of agentic AI.
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