Finance transformation has never been higher on the agenda. Advances in automation, artificial intelligence, analytics and cloud technologies are creating new opportunities to improve efficiency, strengthen controls and provide faster access to insight. At the same time, expectations of the finance function continue to grow. Business leaders want better visibility of performance, quicker decision-making and more forward-looking support.
For CFOs, the challenge is no longer simply how to deliver a transformation programme. It is how to build a finance function that can continue evolving as technology, business priorities and skills requirements change around it.
CFO priorities reflect the scale of this shift. Deloitte’s CFO Signals survey found that 50% of surveyed CFOs considered digital transformation within finance a top priority, while separate research found that between 84% and 86% of CFOs are prioritising finance technology, automation and digital transformation as key focus areas. The challenge for many organisations is no longer whether to transform, but how to build the capability needed to sustain that change over time.
The organisations that make the greatest progress are unlikely to be those that focus solely on technology. Instead, they will be the ones that invest in their people, skills and ways of working alongside their systems and tools.
Drawn from the experience of Claire Barham, BIE’s Advisory Partner, this article explores some of the capabilities finance teams will need if they are to sustain transformation over the long term.
Historically, finance transformation often had a defined beginning and end. Organisations would deliver an ERP implementation, launch a shared services programme or redesign reporting, realise the benefits and then move their attention elsewhere.
That model is becoming increasingly difficult to sustain. Technology is evolving quickly. New automation tools are changing how work is completed. AI is beginning to reshape how reporting and analysis are performed. Expectations around data, insight and decision support continue to rise.
As transformation becomes less of a discrete programme and more of an ongoing management responsibility, finance leaders face a different challenge: how to sustain change while continuing to run the function effectively.
Many organisations ask leaders who know the business exceptionally well to take responsibility for transformation, despite those leaders having limited exposure to large-scale change programmes. Their teams are then expected to contribute alongside an already demanding operational workload.
The issue is rarely commitment. More often, it is capacity, prioritisation and experience. Organisations can find themselves tackling systems, data, reporting, AI, operating models and skills development simultaneously. Without clear priorities, teams can quickly become overwhelmed.
There is sometimes a temptation to wait for greater certainty, particularly around AI. Yet many of the most important foundations of transformation do not depend on knowing exactly how technology will evolve. Process simplification, stronger governance, clearer ownership and better data quality continue to deliver value regardless of future developments.
The question for finance leaders is no longer whether transformation should continue, but how to build the capability required to sustain it.
Much of the discussion around finance transformation focuses on capability gaps. In reality, most finance teams already possess many of the foundations required for success.
Long-tenured teams often hold deep organisational knowledge. They understand how processes work, where previous challenges have occurred and how the business operates in practice. That expertise is extremely valuable and should not be underestimated.
At the same time, experience can sometimes make it harder to challenge established ways of working. Teams that have spent many years within a single organisation may have fewer opportunities to compare their approach with alternative operating models, benchmark performance externally or assess what good looks like elsewhere.
Reporting often exposes this issue most clearly. Many finance functions are frequently measured on primarily on responsiveness. New requests arrive, reports are produced and additional analysis is created. Over time, significant amounts of effort can become focused on producing information rather than helping the business use it effectively.
One of the most important shifts many finance teams need to make is from answering every question to helping the organisation focus on the questions that matter most.
That requires confidence as well as technical expertise. Finance professionals need to understand not only how to produce information but why it is needed, what decision it supports and whether it genuinely creates value.
It also requires a broader set of capabilities. Technical finance expertise remains essential, but modern finance functions increasingly need people who can lead change, work across organisational boundaries, influence stakeholders and translate strategic ambitions into practical improvements.
Transformation capability should not sit with a single programme lead or sponsor. The organisations most likely to sustain improvement are those that build change capability throughout the function, giving more people experience of process redesign, stakeholder management and programme delivery.
Few topics currently generate as much discussion within finance as data and AI.
KPMG’s 2026 Global AI in Finance research found that more than three quarters of surveyed organisations are already using AI in areas such as planning, reporting and commercial analysis. However, only a minority believe it is exceeding expectations. The same research identified data fluency as one of the most important capability requirements for finance teams.
The reason is straightforward. AI can only be as effective as the information it is working with.
Many organisations still face challenges around data quality, governance and consistency. Different functions may use different definitions, maintain separate reporting structures or hold alternative versions of key performance measures. As reporting requirements increase, complexity can increase alongside them.
These challenges cannot be solved by technology alone. Successful organisations recognise that finance, IT and specialist data teams each have an important role to play. Technology teams provide expertise in platforms, integration and architecture. Finance brings an understanding of controls, performance measures and decision-making requirements.
The objective is not ownership for ownership’s sake. It is creating a trusted data environment that enables consistent reporting, meaningful analysis and effective decision-making.
AI makes this even more important. Many organisations are now exploring how to scale AI across finance. While the technology is developing rapidly, AI can only be as effective as the information it is working with. Data quality, process consistency and clear reporting standards remain critical foundations.
In practice, many organisations are still debating where to begin. Faced with multiple change agendas, leadership teams can spend significant time discussing future possibilities rather than addressing the foundational changes needed today. It can feel safer to wait for greater clarity on AI than to make decisions about process standardisation, reporting structures or data governance.
Yet much of the work required to create value from AI is already clear. Organisations can simplify processes, strengthen data quality, clarify ownership and establish more consistent reporting structures today. In many cases, these are the very changes that will enable successful AI adoption in the future.
As AI becomes better at identifying trends, highlighting variances and generating analysis, the role of finance will also continue to evolve. Finance will create value less through producing information and more through interpreting it, applying judgement and helping leaders decide what to do next.
Rather than reducing the importance of finance business partnering, AI is likely to increase its significance.
The challenge for most finance leaders is practical rather than theoretical. They understand the need to strengthen capability, but they must also continue delivering against today’s priorities and commitments.
One of the practical challenges facing finance leaders is how to continue delivering today while building the capabilities needed for tomorrow. Few organisations have every skill they need in-house. Equally, few can afford to pause business delivery while they build those capabilities from scratch.
The most effective approach is usually a balanced one. Organisations continue developing internal capability while selectively bringing in external expertise where it can accelerate progress or address specific gaps.
That might involve strengthening transformation leadership, adding specialist data expertise, supporting programme governance or providing experience that does not yet exist within the organisation.
The most successful support models focus on capability transfer as much as delivery. The goal is not dependency. It is leaving the organisation stronger, more confident and better equipped to lead future change.
Finance transformation is becoming a permanent feature of the modern finance function. New technologies will emerge, business requirements will evolve and expectations will continue to grow.
Organisations are unlikely to succeed simply because they have the largest transformation budgets or the newest technology. They will succeed because they invest in their people alongside their systems, building the skills, confidence and ways of working needed to improve continuously.
Ultimately, finance transformation is no longer a programme to complete. It is a capability to build. The organisations that invest in that capability alongside technology will be best placed to adapt, improve and create value long after any individual transformation project has ended.
Claire partners with BIE to lead its Business Advisory service for clients.
She brings extensive expertise in Transformation strategy, Operating Model Design, finance and back office transformation, and GBS/Shared Services. Claire also boasts experience across industries such as consumer goods, pharmaceuticals, technology/digital, Hospitality, retail, oil and gas, support services and postal.
