Finance functions are at a crossroads. The promise of autonomous finance—where AI and automation manage core processes with minimal human touch—is closer than ever. From robotic process automation in invoice management to AI-driven forecasting and decision-making, the building blocks are already here. Generative AI (GenAI) tools like ChatGPT, Claude, and Copilot have accelerated adoption, turning once-experimental use cases into mainstream possibilities.

GenAI is redefining what “autonomous” can mean. At the most basic level, it automates content creation tasks such as generating monthly account statements or customer communications from transaction data. At the next level, GenAI interprets patterns in financial and operational data, offering recommendations, predicting risks, or even executing routine decisions under pre-approved rules. The most advanced stage combines GenAI with agentic AI, enabling adaptive, multi-source decision-making—like monitoring regulatory updates, interpreting compliance impacts, and filing required documents with minimal human oversight. For finance leaders, this represents a seismic shift – moving from tools that simply process transactions faster to platforms that actively shape strategy and risk management in real time.

Yet, for all the potential, transformation isn’t simple. Many organizations remain stalled at the starting line, held back by a tangle of familiar roadblocks. The question isn’t whether autonomous finance is achievable; it’s whether companies can break free from legacy constraints and risk-averse thinking to seize the opportunity.

GenAI works in combination with agentic AI, enabling adaptive, multi-source decision-making. This includes monitoring regulatory changes, assessing compliance implications, and even initiating required filings with minimal human oversight.

• Leadership Reluctance and Governance Gaps: Risk sensitivity is deeply embedded in finance leadership with the weight of compliance and capital stewardship. But this responsibility often fuels excessive caution. Sixty percent of CFOs cite as the top barrier, while governance gaps—fragmented pilots, unclear ownership, and untested controls—further delay adoption. The result is hesitation to scale, even when pilots succeed.
• Legacy Systems and Data Deficiencies: With up to 70 percent of IT budgets consumed by outdated platforms, innovation funding is scarce. Legacy environments block integration and keep data trapped in silos, eroding quality and consistency. Thirty-five percent of CFOs report poor data as the biggest hurdle to AI adoption, making scalable automation nearly impossible.
• Talent and Change Management Shortfalls: Autonomous finance requires new skills and new ways of working. Seventy-seven percent of CFOs cite a lack of digital skills, while more than half identify talent shortages. Without structured change management, the benefits of automation never stick—leaving productivity gains unrealized.

Overcoming these challenges isn’t about brute force—it’s about strategic balance: risk, modernization, and people.

De-Risk and Govern for Scale. Build cross-functional innovation teams that include finance, legal, IT, and risk from the start to avoid implementation roadblocks. Demonstrating ROI through controlled pilots builds confidence¹, while establishing an automation center of excellence clarifies ownership, enforces standards, and accelerates enterprise-wide adoption.

Modernize and Strengthen Data Foundations. Reliable data is the fuel for faster, more accurate decision-making—and it is especially critical for GenAI, where poor data can create amplified errors at scale. Rationalize² and shift toward modular, API-first systems to prepare for technology transformation. Cloud-based platforms³, paired with data lakes and data fabrics, ensure consistent, high-quality data that automation can trust.

Restructure and Upskill Talent. Treat change management as a must-have, rather than a nice-to-have to put your people first. Redeploy finance professionals into higher-value roles, embed digital skills training, and weave change adoption into every phase of the journey. This ensures the workforce evolves alongside the technology for a “people in the loop” approach and can fully leverage GenAI and autonomous finance-driven insights and recommendations.

Those who get it right aren’t just optimizing processes—they’re transforming the role of finance. Finance teams gain the ability to:

• Redirect focus to strategy and value creation – Freed from manual reconciliations and error-prone data entry, professionals can focus on investment analysis, scenario planning, and business partnership.
• Enhance resilience – Adaptive AI models can monitor regulatory, market, and supply chain signals in real time, enabling finance to anticipate risks and adjust course before disruptions escalate.
• Unlock new growth capacity – With automation scaling transactional workloads, finance leaders can pursue mergers, expansions, and digital business models without proportionally increasing staff or cost.
• Elevate credibility with stakeholders – Reliable data pipelines and transparent AI-supported insights provide boards, regulators, and investors with higher confidence in reported results and forward-looking guidance.

 
The transformation goes beyond efficiency. It reshapes finance into an engine of agility and foresight. With automation as the driver, finance evolves from being a recorder of history to a real-time navigator of the future—proactively steering decisions rather than simply validating them.

ScottMadden recently supported a Fortune 100 energy company in transforming its finance and accounting function. To support the growth of the organization amid regulatory demands, ScottMadden was contacted to help by automating key processes, enhancing data governance, and shifting focus to strategic analysis. The objective of the transformation was to identify opportunities to centralize, automate, and outsource work to reduce costs and improve service levels.

The results:

• $30 million in savings through error correction in nearly 20 percent of accounting journal entries⁵
• $8 million in staffing savings by redefining more than 450 positions without sacrificing productivity⁶
• Strengthened governance model to include improved line management accountability, reduced layers and spans of control, and stronger central governance and oversight
• 100 processes identified for further automation

1. De-Risking Innovation: AI prototype delivery to forecast returns and de-risk further AI investment for a Fortune 500 manufacturing client, resulting in measurable improvements. Twenty-five percent accuracy improvement, 80 percent less manual entry, and four times faster AP processing were established.
2. Strategic Modernization: IT operating model designed to facilitate technical debt rationalization program for an energy client. MISO_IT_US_Strategy_100841-10420_Energy_2023_SM755.pptx
3. Strategic Modernization: Cloud-based machine learning service and custom code development for a large electronics product distributor, resulting in elimination of 50 percent of targeted manual work. Arrow_SC_Assess_393-006_Technology_2019_SM675_WS.pptx
4. Establishing Governance for Scale: Conducted pilot and designed a sustainable governance model for an enterprise-wide RPA program for a leading provider of online legal research for immediate ROI and 10x improvement in process speed. LexisNexis_IT_Global_Implement_Strategy_422-001_ProfSvcs_2017_SM622_WS.pptx
5. Exelon_FA_US_Improve_360-306_Energy_SM660_WS.pptx
6. Exelon_FA_US_Assess_Implement_Energy_SM667_WS.pptx

• Conduct functional assessments and planning
• Develop strategic and implementation roadmaps
• Define use cases and build¹
• Lead and ERP modernization initiatives²
• Support ³
• Establish automation governance frameworks⁴
• Embed change management to sustain momentum

 
We’ve helped Fortune 100 enterprises and midsize innovators alike capture millions in savings, streamline operations, and strengthen governance—all while equipping finance teams for the future.

The barriers to autonomous finance are real, but they’re not permanent. The path forward is clear: reframe the obstacles as opportunities and turn hesitation into acceleration.