The Future of Finance: New Operating Models for the AI Era

Randy Werder,
June 12, 2025

Approximate read time: 5-6 minutes

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Throughout my career guiding finance transformations, I’ve seen one mistake repeated more often than any other: organizations pour millions into AI technologies but continue operating their finance functions exactly as they did before.

It’s like putting a Ferrari engine in a horse cart. The potential is there, but the surrounding structure simply can’t take advantage of it.

After working with dozens of companies at the forefront of finance transformation, we’ve identified five fundamental shifts that will define successful finance functions in the AI era. Organizations that embrace these shifts aren’t just getting incremental improvements -they’re seeing transformative results like 40% faster time-to-decision, 25% improved forecast accuracy, and 30% reductions in working capital.

Shift #1: From Process Stewardship to Decision Excellence

Traditional finance functions are organized around processes: accounting, planning, treasury, tax. But future finance functions will be organized around decision domains.

This isn’t just reorganizing boxes on an org chart, it’s a fundamental reframing of how finance creates value. Instead of asking “How do we make this process more efficient?” finance leaders will ask “How do we make these decisions better?”

We recently worked with a global consumer goods company that reorganized their finance function around three decision domains:

Investment Allocation: All activities related to where and how to invest capital

Operational Optimization: Activities focused on maximizing performance within current operations

Future Positioning: Longer-term decisions about markets, products, and capabilities

Each domain had dedicated finance leaders, cross-functional teams, and purpose-built analytics capabilities. The results? 30% faster decision cycles, 22% improved investment returns, and dramatically higher business partner satisfaction.

Why? Because this structure aligns finance capabilities directly to how value is created in the business. Process excellence becomes a means to an end – better decisions – rather than an end itself.

Shift #2: From Hierarchical to Networked Talent Models

The traditional finance hierarchy, a pyramid with clear reporting lines and specialized roles, simply can’t keep pace with the speed and complexity of modern business decisions.

Future finance functions will adopt more networked talent models that flex and reconfigure based on business needs, featuring:

Fluid Expertise: Specialists move between teams based on decision needs

Cross-Functional Integration: Finance professionals work in integrated business teams

Capability Hubs: Centers of excellence provide specialized capabilities that can be deployed as needed

A pharmaceutical company reorganized their 200-person finance team from 12 hierarchical departments into a network model with 60% of staff embedded in cross-functional business teams, 25% in capability hubs providing specialized expertise, and 15% in a lean core handling governance and strategy.

The result was a 40% reduction in decision latency and dramatic improvements in business partner satisfaction.

Shift #3: From Human-Only to Human-Machine Collaboration

Perhaps the most profound shift is how work gets done. In traditional finance functions, technology supports human processes. In future functions, humans and intelligent systems will form true partnerships.

This isn’t about replacing humans, it’s about redefining roles to leverage the strengths of both:

Machines excel at: Processing vast data sets, identifying patterns, maintaining consistency, eliminating bias, and executing repetitive tasks

Humans excel at: Understanding context, applying judgment, managing relationships, navigating ambiguity, and providing creative solutions

We worked with a financial services firm that redesigned their forecasting process as a human-machine collaboration. AI systems generated baseline forecasts and identified anomalies, while finance business partners focused on understanding those anomalies and applying business judgment. The AI then incorporated this judgment into future forecasts, creating a continuous learning loop.

The result was both better forecasts (35% improved accuracy) and more valuable finance partnerships. Business partners reported spending 70% less time explaining what happened and 60% more time on what to do about it.

Shift #4: From Periodic to Continuous Financial Management

Traditional finance operates in artificial cycles – monthly closes, quarterly forecasts, annual plans. These time boundaries made sense in an era of manual processes and limited computing power. They make little sense today.

A retail organization recently transformed their approach from periodic to continuous:

Daily sales, margin, and inventory data flowed automatically to decision-makers

AI systems continuously updated forecasts and identified performance deviations

Formal reviews occurred only when variances exceeded thresholds, not on fixed schedules

Resources shifted from producing periodic reports to analyzing emergent trends

This approach reduced decision latency from weeks to days or hours while actually decreasing the total effort involved in financial management.

Shift #5: From Process Automation to Decision Automation

The first wave of finance technology focused on automating manual processes – transaction processing, reconciliation, reporting. The next wave will focus on automating routine decisions.

This doesn’t mean removing humans from decision processes. Rather, it means elevating human involvement to decisions that truly require judgment while allowing systems to handle predictable, rule-based choices.

A manufacturing client implemented decision automation across their finance function:

Routine forecast adjustments below certain thresholds happened automatically

Standard pricing decisions for catalog items were system-determined

Basic investment approvals within defined parameters occurred without manual review

Exception handling processes brought humans in only when needed

This approach reduced decision volume by a stunning 60% while improving consistency and freeing finance professionals to focus on complex decisions where they could add the most value.

The Path Forward: Evolution, Not Revolution

Transforming your finance function isn’t an overnight process. It’s an evolution that typically unfolds over 2-3 years, with each step building on previous capabilities.

Here’s the pragmatic approach we recommend:

Phase 1: Establish the Foundation

Implement core data and analytics infrastructure

Develop integrated security framework for AI-processed financial data

Pilot new ways of working in select areas

Build AI literacy across the finance organization

Phase 2: Transform Critical Capabilities

Redesign key processes around human-machine collaboration

Implement initial decision automation in well-defined areas

Begin shifting organizational structure to support decision domains

Phase 3: Scale and Optimize

Expand new operating model across the finance function

Implement comprehensive decision automation framework

Refine talent models and performance metrics to support new ways of working

With every organization we’ve advised through this transformation we’ve emphasized that the technology itself, while critical, is ultimately just an enabler. The true transformation is organizational and cultural.

The Finance Function Reimagined

The future of finance isn’t about doing the same things better. It’s about doing better things – elevating finance from a scorekeeper to a strategic partner in value creation.

The finance leaders who will thrive in this new era are those who can envision a fundamentally different operating model and lead their organizations through the human, organizational and leadership challenges of transformation.

This is the most significant evolution in the finance function since the advent of enterprise systems in the 1990s. And for organizations willing to embrace these shifts, the rewards aren’t just incremental improvements but transformative changes in how finance creates value.