We recently brought together more than thirty of the Bay Area’s top finance leaders for an exclusive roundtable hosted by Pigment. I had the pleasure of co-hosting the session with Ajay Vashee (Pigment board member and former Dropbox CFO) and Michael Demyttenaere (Managing Partner at BCG).
We explored the current state of AI in finance, shared practical strategies for adoption, and discussed what lies ahead for the Office of the CFO.
Hype vs. reality
Across the board, attendees agreed: the promise of AI in finance is massive, but we are still early in the journey. Many teams are just beginning to explore generative AI, often associating AI with traditional machine learning (ML) tools. Legacy tools were repeatedly mentioned as falling short of expectations, reinforcing the need to show what modern AI is truly capable of.
By integrating cutting-edge generative AI innovations with machine learning capabilities, platforms like Pigment are uniquely positioned to transform how finance operates—unlocking new efficiencies, insights, and agility.
Preparing the ground for AI
AI represents the most advanced stage in the evolution of digital finance capabilities. But to unlock its full value, companies must first establish a strong foundation built on robust data infrastructure, sound governance, integrated, automated systems, and streamlined processes. Only with this digital groundwork in place can the transformative potential of AI truly be realized.
Yet, success with AI goes beyond sophisticated models and platforms. Equally critical is the human element of guiding finance teams through the change management journey. Building comfort with AI requires intentional effort. Initiatives like "prompt-a-thons" offer hands-on exposure to generative AI, fostering familiarity and confidence. More broadly, AI adoption requires a mindset shift: from skepticism to experimentation, from control to collaboration.
Today, most AI use cases in finance are still in pilot mode. The challenge is not just building the tech, but proving return on investment (ROI) and scaling across functions. Michael urged us to link AI to measurable outcomes and treat implementation like any major transformation initiative: with a clear business case, leadership buy-in, and ongoing tracking beyond the proof-of-concept phase.
Expanding the impact of AI across finance
Early use cases for AI in finance have largely focused on automating repetitive, manual tasks, particularly within accounting functions such as invoice processing and account reconciliation.
Financial Planning & Analysis (FP&A) is widely viewed as the next frontier. Here, AI can reduce bias in forecasts, support dynamic scenario planning, and enable a level of speed and insight that surpasses anything we have seen.
Looking ahead, the rise of agentic AI will further redefine the finance function. These proactive, autonomous agents (operating continuously and aligned to a defined mission) will be capable of optimizing investment strategies, refining balance sheet decisions, and simulating hundreds of scenarios in real time. With Agentic AI, finance teams will move from reactive to truly strategic, supported by always-on intelligence working on their behalf.
Final thoughts on the AI-enabled finance function
Across every table, the message was clear: this isn’t just about faster reports or cleaner data. It’s about reinvention. Every process, from accounting to planning to reporting, is being reimagined with AI at the core. Getting there requires bold leadership: not just adopting new tools, but transforming mindsets, upskilling teams, and reshaping how finance operates at every level.
