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Key takeaways:
- Finance is shifting from scorekeeper to strategic partner as AI and predictive analytics enable teams to focus more on profitability, forecasting and capital allocation.
- Agentic finance could fundamentally reshape how work gets done, with autonomous AI running more core finance cycles while people provide oversight, interpretation, judgment, and strategic decision-making.
- Trusted, governed data is becoming the foundation for both AI and reporting, helping finance improve forecasting and decisions while meeting growing demands for transparency, consistency, and control.
- Cash flow and capital allocation remain central to the finance agenda, with greater emphasis on working capital and scenario planning amid shifting market conditions.
- The finance operating model is evolving alongside technology, combining automation, new skills, and managed services to shift talent toward higher-value analysis and strategic advice.
The expectations facing the finance function today have outpaced its design. Increasing demand for deeper, actionable insights as a strategic advisor to the business are weighing on top of 30 years of operating model changes and technical debt. While AI may help solve this capacity crisis, CFOs and their teams need to act decisively to provide organizational trust to exponentially growing sources of data.
Dedicated investment in enterprise data models and digital capabilities is the first step. Without these foundations, many finance leaders may struggle to elevate the function’s strategic visibility. In addition, the competition for skilled AI and functionally knowledgeable talent remains challenging, increasing pressure to offer an innovative culture and climate that appeals to many workers.
As a finance leader, you should carefully consider and clearly understand these shifting responsibilities and goals. Finance for finance—increasing efficiency in traditional finance functions and acting as your company’s scorekeeper—is still important. But finance for business—increasing insight throughout the organization and driving strategic growth—can be your key to success. To help achieve that, consider four critical elements that can enable your intelligent enterprise.
Going forward, leading finance functions may no longer simply report results after the fact. Intelligent agents could run core finance cycles, insights could surface in real time, and finance could increasingly guide the response to change. Getting there will require reliable data, modern platforms, stronger governance, and finance talent prepared to work alongside increasingly autonomous systems.
Moving toward an agentic office of the CFO
In finance for business, static reports give way to metrics, forecasts, and operational drivers that update continuously with supply chain signals, customer sentiment, and insights into macroeconomic developments, resulting in forward-looking insights.
This is finance becoming more agentic: an environment where autonomous AI agents operate across cloud-native platforms, connecting data, processes, and decisions in the value chain. Core finance cycles could become increasingly self-running while finance professionals focus on oversight, interpretation, and strategic decision-making.
Humans are still at the center, especially for decisions where context, ethics, business judgment, and strategic trade-offs matter. The opportunity is to build foundations that make this future possible: trusted data, modern architecture, strong governance, AI-enabled processes, and a workforce that can make smarter decisions.
Elements of agentic finance
- Source-to-pay anticipates demand and evaluates suppliers.
- Record-to-report reconciles continuously and detects anomalies.
- Quote-to-cash optimizes pricing, billing, collections, and cash flow.
- Treasury manages liquidity dynamically as market conditions change.
AI and analytics to drive profitability and efficiency
After decades of targeting costs, many finance leaders are reaching the limits of reduction strategies and increasing their focus on tech capabilities that provide deeper insights. That has intensified competition for talent, prompting companies to automate manual processes and transform the financial planning and analysis (FP&A) function with predictive analytics and AI tools. The resulting organizational and operational models often include outsourcing and managed services.
If you think of finance activity as a triangle, transactional processes traditionally form the large base. Tech such as AI and machine learning is inverting that triangle, enabling finance teams to offer actionable business intelligence. More and more, businesses count on finance to help provide better forecasting, profitability analysis, and capital allocation insights.
As this transition from scorekeeper to strategic partner continues, CFOs should prioritize data fluency and pull from various business areas—from operations to risk to marketing—to drive operational decisions. In a successful data strategy, data cleanup and use case development occur concurrently, and AI is integral to enabling faster execution.
What you can do
Increasing cash flow, capital, and liquidity
With a growing focus on cash collection and working capital, many companies are prioritizing the transformation of the order to cash process. This includes rapid assessments for order to cash and working capital, revenue leakage analysis, digital automation, and process improvement.
Cash and capital positions remain critical as companies pursue acquisitions, divestitures, and portfolio reshaping with greater discipline. While overall deal activity has been uneven, organizations are increasingly prioritizing transactions with clear strategic rationale and stronger paths to long-term value creation.
For finance leaders, this raises the stakes for capital allocation, scenario planning, and valuation. Acquisitions can accelerate growth, while divestitures can generate capital to reinvest in businesses. At the same time, infrastructure modernization and sustainability initiatives can help reduce long-term operational costs and unlock new sources of value.
In this landscape, you should reevaluate your ability to consistently convert earnings to cash flow. Does your financial structure provide sufficient flexibility and reduce cost of capital? Do you have sufficient visibility into cash drivers and levers to increase cash flow?
What you can do
Meeting multiple regulatory reporting requirements
Led by OECD Pillar Two, sustainability, and FASB DISE, regulatory reporting requirements increase the need for transparency—not only in financial performance but in climate risk, infrastructure resilience, and supply chain accountability.
Many finance teams want more visibility into financial operational performance at a granular level and with more governance and control. Many companies record financials at a group level and use informal means to back into their legal entity reporting. They may also have multiple teams across the company developing disparate new tools, processes, and policies for obtaining data.
Addressing these challenges requires greater functional collaboration, including accounting, tax, finance, financial technology, legal, and others. A centralized approach to managing the systems, processes, and policies for sourcing and reporting data through a common data model can help improve accuracy and consistency. Companies can use a common data model to:
Clearly define data requirements across uses
Provide ongoing governance for monitoring and adapting to new requirements
Improve legal entity mapping
Standardize master data usage, policies, and processes
Proactively collaborate across all functional teams
Beyond compliance, reporting requirements can be a catalyst for building the trusted data foundation that future finance will require. Trust is becoming a strategic requirement, and data integrity is a differentiator. Finance organizations that can govern, validate, and explain their data will be better positioned to support not only regulatory reporting but also AI-augmented forecasting, scenario planning, and decision-making.
Over time, unified data fabrics can help connect operational, transactional, and external data into governed enterprise platforms, creating a more consistent source of truth across the business. As these capabilities mature, verification agents may help validate transactions, models, and data quality in real time. That can allow finance to move faster while preserving transparency, control, and confidence in reporting and decision-making.
What you can do
Evolve your finance operating model to get more value from managed services
Transforming finance can be resource-intensive, leading companies to turn to shared or managed services for non-core processes. By freeing up management and staff resources in those areas, finance leaders can dedicate teams to more forward-looking work that can increase the finance function’s value.
The key is to focus on outcomes. What opportunities exist to centralize or standardize service delivery? If you’re already outsourcing business processes, what’s working well that could further reduce costs or fill skills gaps? How can different contract structures and pricing models in managed services help your finance teams provide more specialized finance expertise at scale and less cost?
This is a chance to free finance talent to focus on higher-value activities: interpreting signals, advising on future scenarios, challenging assumptions, and helping your enterprise make better strategic choices. Technology and alternative delivery models should elevate the finance workforce, not simply replace capacity.
A future-ready operating model should also account for AI agents and automation. Finance leaders will need to clarify which decisions can be automated, which require human review, and which should be escalated based on risk, materiality, or strategic impact. This requires new governance models, clear accountability, and finance professionals who understand how to work with intelligent systems.
What you can do
Lead the next era of finance
The future of finance won’t be built through a handful of tech implementations or isolated investments. It will emerge through the cumulative effect of decisions that finance leaders make now—how they modernize data, deploy AI, strengthen governance, manage capital, respond to regulatory change, and redesign the finance operating model. The most successful finance functions will connect today’s priorities to tomorrow’s capabilities.
Improving order-to-cash can be a step toward more intelligent cash flow management.
Building a common data model can be the foundation for AI-enabled reporting and decision-making.
Transforming FP&A can be a path toward continuous planning.
Evolving managed services can free finance talent to focus on insight, judgment, and strategic advice.
As AI, data, and digital platforms reshape work, the finance function’s role as steward, strategist, and enterprise advisor will only become more important. The organizations that lead tomorrow will be the ones where finance helps the business move first, adapt faster, and create value with confidence.
Future-proof your finance function
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