The AI-Driven Identity Crisis in Finance

How automation and AI are reshaping roles, responsibilities, and the very core of the finance profession.

The rise of artificial intelligence (AI) is transforming industries across the board, but in the finance sector, it’s sparking a full-blown identity crisis. Traditionally centered on manual processes, careful analysis, and repetitive accuracy, the finance function is now being redefined as automation takes over many foundational tasks. The result? Significant changes in roles, responsibilities, and even the identity of finance as a profession.

From Number Crunchers to Supervisors

One of the biggest shifts AI has caused in finance teams is the move away from manual work to a supervisory model. For instance, at Brex, AI now reconciles up to 95% of invoices with purchase orders—a task that previously required significant human effort. This shift has freed financial staff to focus on reviewing AI outputs, identifying trends, and providing strategic insights to the business.

Erik Zhou, Brex’s Chief Accounting Officer, likens AI to a junior team member in need of constant oversight. Unlike static tools like Excel, AI can "hallucinate" (generate incorrect answers) or "drift" (gradually decrease in accuracy), so human supervisors are necessary to ensure the outputs are logical and actionable. This transition from doing the work to overseeing it is making finance professionals more efficient, but it’s also redefining their roles entirely.

Challenges for Entry-Level Workers

For those just entering the workforce, this shift raises a critical question—how can new employees gain foundational experience if entry-level tasks are now handled by AI? At the 2025 Gartner CFO & Finance Executive Conference, attendees pondered this very issue. Experts like EY’s Deirdre Ryan noted how college accounting programs are starting to integrate AI training into curricula, but the industry remains uncertain about how entry-level workers can develop the hands-on expertise needed to supervise AI systems effectively.

On the bright side, some finance professionals entering the workforce already possess robust technology skills, including SQL, which enables them to bypass traditional tools like Excel altogether. However, these tech-savvy newcomers are the exception rather than the rule, especially in non-tech-savvy organizations that lack the resources or culture to prioritize advanced training.

The Growing Need for Upskilling

To bridge this gap, upskilling has become a key focus for organizations adapting to the demands of AI. Industry leaders like Unilever and EY have rolled out comprehensive training programs to prepare their employees for AI-enabled roles.

Unilever’s “Digital Foundations” program equips employees with skills in data analytics, visualization, and even digital business modeling. Meanwhile, EY utilizes its proprietary AI, EYQ, to help employees practice and refine their AI capabilities. For smaller organizations, simpler initiatives—like AI demo sessions or team challenges to solve business problems with AI—can also encourage workforce adaptation.

Amanda Joseph-Little, VP of Gartner’s finance practice, emphasizes the need to make most finance staff digitally literate while cultivating “citizen digital talent” capable of improving and customizing AI systems. These investments in upskilling could determine whether an organization thrives or falters in a rapidly changing financial landscape.

Blurred Lines Between Finance and IT

The integration of AI has also blurred the lines between finance and IT roles. Tasks like data modeling, Python coding, and even data integration are becoming essential elements of finance work. Gartner's Mallory Barg Bulman stresses that the traditional notion of “finance versus tech” no longer applies—technology innovations are now part and parcel of finance operations.

This merger of disciplines is more than just a practical change; it signals a deeper cultural shift. Finance is no longer about processing transactions or reconciling ledgers. It’s about leveraging financial data to create actionable insights, a transformation that demands adaptable talent and a forward-thinking mindset.

Reflections on the Future

Though AI is revolutionizing finance, the path forward isn’t without challenges. Regulatory frameworks will need to evolve as AI becomes an integral part of financial processes. For example, AI-assisted audits raise concerns about accountability, accuracy, and compliance with auditing standards.

Ultimately, while technology now dominates many aspects of finance, human expertise remains irreplaceable. Tools may handle the heavy lifting, but it takes human judgment to interpret findings, communicate insights, and make strategic decisions.

Finance leaders will need to balance their investments in technology with a commitment to developing talent. Internally, this means fostering skills in both AI supervision and business acumen; externally, it means recognizing the enduring value of professionals who can connect the dots between AI outputs and organizational goals.

The future of finance may be deeply intertwined with technology, but it’s the human element—the decision-makers, strategists, and supervisors—that ensures this brave new world stays grounded in accountability and value creation.