The CFO’s new mandate: trust, data and decisions in uncertain times

Key takeaways:

• As AI accelerates finance transformation, trust in data, insights and governance is becoming a critical source of competitive advantage and decision-making confidence.
• The CFO’s role is expanding beyond capital allocation to help establish the trust, control and accountability needed to scale AI across the enterprise.
• Organisations that combine high-quality data, robust governance and AI-enabled agility are better positioned to navigate volatility and drive sustainable growth.

In today’s frequent discussions around the evolving role of the finance function in organisations, much of the debate centres — quite rightly — on the pace of change and the arrival of AI in judgment-based work. The first of these themes is multifaceted, driven by rapid economic, geopolitical and technological shifts. The second is equally disruptive, as agentic AI creates opportunities to take speed, efficiency automation and human-machine collaboration in finance functions to new levels.

Together, these forces bring profound implications for the CFO. For some years, the CFO’s role has moved steadily towards being an active strategic partner to the business and pivotal creator of enterprise value. While this expanding remit has been described in many ways, we at PwC have termed it as a “critical investor”: overseeing and deciding where and how the business should invest its capital, monitoring the performance of that capital, and guiding the board on the stewardship, growth or perhaps withdrawal of that investment.

This evolving role for the CFO is now well-established. However, today it is being augmented by a subtler yet even more significant shift, as the CFO increasingly becomes the principal provider of trust and credibility in the data used to make every decision. What is scarce today is not capability but credibility, making trust in information the key source of durable advantage. In an environment where forecasts must be recalibrated monthly and AI is generating the analysis behind them, the binding constraint becomes trust in data — an attribute that determines whether the board, investors and regulators can rely on the numbers enough to make decisions and act with confidence and agility.

The importance of trust in data is increasing in tandem with the ongoing headlong digitalisation of finance functions and processes. As an example of the global trends, take PwC’s Digital CFO 2026 research report, based on a survey of CFOs in publicly listed and larger non-listed companies in Germany, Austria, and Switzerland. An overwhelming 71% of respondents said they assign high priority to the digitalisation of the finance function, and 20% rate their own finance departments as already highly or very highly digitalised.

While digitalisation of finance has been ongoing for many years, rising usage of AI is changing the game around the latest wave. Past transformation cycles reinvented how finance produces information. The current cycle tests whether that information can still be trusted at the speed with which decisions must be made in a shifting and uncertain context. The trust gap is widening and it's costly. In EMEA in particular, the pressure to make data truly credible is intensified by a highly regulated environment — including sustainability reporting, AI governance, and fragmentation of regulations across markets — that turns trusted, defensible numbers into a competitive asset rather than a compliance cost.

The effect is to redefine the CFO’s role from architecting enterprise value into what is ultimately a mandate focused on building and sustaining trust. As enterprise decisions come to depend increasingly on data and AI that originate inside finance, the CFO and finance function become the guarantor that the information that the business acts on is reliable — positioning finance as the department that provides insights trustworthy enough to bet on. Applying this perspective, the CFO’s remit expands from directing capital toward the right opportunities to encompass acting as the enterprise’s trust layer in a human-led, technology-powered finance model.

For the wider C-suite, the effect is that finance becomes the function that gives every other function the confidence to move. This vital role is underlined by instances of recent failed investments, many of which are essentially rooted in issues around trust in the accuracy and completeness of the available data. In the automotive sector in Europe, for example, some gigafactories built to manufacture batteries for the global market have closed before reaching production. The reason was that lower-cost competition from China made the facilities economically unviable — a reality that the data should ideally have revealed before the investments were made.

Alongside capital investment decisions, the CFO’s role as the guarantor of data is equally pivotal in navigating through turbulent times. Agility, scenario planning and dynamic capital allocation are all widely accepted and understood as elements of managing volatility. However, as these capabilities become more commonplace across enterprises, they cease to be a major differentiator. Instead, our experience suggests the real gap between winners are losers is around having the confidence to act: organisations stall or dither not because they lack scenarios, but because their leaders do not trust the inputs sufficiently to commit capital at pace.

Therefore, competitive edge comes from pairing fast, strategic driver-based planning with the data assurance and governance that enable decision-makers to move without second-guessing the quality of the model and its outputs. In Europe’s fragmented markets and currencies, that ability to reallocate resources quickly and defensibly is what drives consistently better decisions. This mirrors what CFOs identified in our Digital CFO 2026 research: "increasing the speed and agility of decision-making and other processes" is the objective cited most frequently by digital transformation leaders — yet it is precisely those organisations that couple speed with assurance that achieve it most effectively.

The importance of speed and agility raises a further question: how can CFOs combine data and AI to generate the trustworthy information that really will lead to better decisions made at a higher pace? On the surface, this sounds contradictory and it is, which is why the data foundation matters so profoundly. The answer lies in the data itself. Our experience supports the view that weak data foundations — and not the tools deployed on top — are what hold back both the finance function and wider enterprise from realising the promise of AI. Given this reality, the next frontier that is opening up is trust and control: in other words, the explainability, auditability and governance of increasingly agentic systems that do not merely inform decisions but are beginning to make them. As AI advances from assisting to acting, the question shifts from “is the data good enough?” to “can we stand behind what the machine did?”.

Answering “yes” to this question, emphatically and credibility, is where finance functions can now create defensible advantage. Once again this has particular implications for Europe, where the EU AI Act makes governed, auditable AI a near-term operating requirement. This means the organisations that engineer control early into their data foundation and AI tools can turn an apparent regulatory burden into a genuine competitive head-start.

For finance functions across all industries, the direction of travel is now widely recognised: automate the transactional layer, build analytics centres of excellence, embed finance in the business, and reskill the team. However, an overarching requirement for the future finance operating model is that it should be assured by design. As work migrates to blended human-and-agent teams, trust and control must be engineered into the model from the outset rather than bolted on as a response when something goes wrong.

Given the evolving landscape that we’ve described, what steps should companies and finance functions take as a matter of urgency? We would urge C-suites to target three priorities over the coming 24 to 48 months.

1. Get the data foundation fit for purpose.
2. Build the human-led and technology-powered talent model.
3. Set up the governance and assurance frameworks that will enable the organisation to scale AI with confidence and deliver sustained enterprise-wide outcomes rather than one-off wins.

The future of finance is taking shape before our eyes. It’s time to build it, starting with your data foundation and the governance that will allow you to scale AI with genuine confidence.

In forthcoming articles we’ll drill down into three aspects of the future of finance: first, Enterprise Performance Management (EPM); second, data, technology and AI; and third, people and structure. Stay tuned!