Beyond The AI Hype: Are Finance Teams Ready For What Comes Next?

AI is moving into practical finance use, but trusted data, connected systems and strong processes still determine how much value organisations can really achieve.

AI has dominated business conversations for the past year, but for finance leaders the question is beginning to change. It is becoming less about what AI can do and more about whether organisations have the right foundations to use it effectively.

That distinction matters. AI is already moving beyond experimentation and into practical finance use cases, from analysing information and identifying anomalies to supporting forecasting, reducing repetitive tasks and helping teams access insight more quickly. But adding AI to a finance function does not automatically make that function more efficient, more accurate or more strategic.

For many organisations, the bigger challenge still sits underneath the technology.

Finance teams are often working with information spread across multiple systems. Core finance, payroll, CRM, ticketing, ecommerce, hospitality and other operational platforms may all hold different pieces of the picture. When those systems do not connect effectively, finance teams become responsible for bringing the information together themselves.

That can mean exports, spreadsheets, manual reconciliations and repeated checks before anyone can confidently use the numbers.

The finance challenge behind the AI conversation

The conversation around AI can sometimes make it sound as though every organisation is starting from the same place. In reality, finance teams are at very different stages of their technology journey.

Some are already using automation and AI as part of everyday processes. Others are still dealing with reporting structures that depend heavily on spreadsheets or the knowledge of one or two individuals.

Neither position should be ignored.

For finance leaders, the important question is not whether they are using the latest technology. It is whether their current environment gives them reliable information, appropriate control and enough visibility to make better decisions.

If producing a management report still requires several exports and hours of manual work, adding an AI tool on top may simply create another layer of technology without solving the underlying issue.

Trusted data, connected systems and clear processes therefore remain fundamental.

Why this matters in professional sport

Professional sport is a good example of just how complex the finance environment can become.

A club or sporting organisation may be dealing with income and information across ticketing, hospitality, sponsorship, retail, payroll and other commercial operations. Yet the finance teams supporting those organisations are often relatively lean.

That creates a very practical challenge. The organisation may have plenty of data, but the finance team still has to bring it together in a way that can be trusted and understood.

Eureka Solutions has seen this through its work with organisations across professional sport, including the Scottish FA, Aberdeen FC and Luton Town.

While every organisation has different priorities, many of the underlying conversations are similar. How can we reduce manual reporting? How do we get clearer visibility across the organisation? Can our systems exchange information properly? Are we spending too much time gathering data and not enough time analysing it?

Those are not simply technology questions. They affect the role finance can play across the wider organisation.

From reporting to decision-making

The role of finance is changing alongside the technology available to it.

Traditionally, a significant part of the finance function has been focused on producing and explaining what has already happened. That remains essential, but leadership teams increasingly expect finance to help them understand what is happening now and what might happen next.

That requires capacity.

If a finance team is spending too much time collecting, correcting and reconciling information, there is less time available for forecasting, scenario planning and working with other departments.

Modern finance technology should help reduce that friction.

ERP provides the financial foundation. Integration connects finance with the other systems used across the organisation. Automation removes repetitive work. AI can then help teams interrogate information more quickly, identify patterns and access insight in new ways.

But the order matters.

AI works best when the data underneath it is reliable and the systems feeding it are properly connected. It should enhance financial judgement, not replace the controls and processes that make the information trustworthy in the first place.

AI readiness is also about people

Technology is only part of the conversation.

As AI takes on more routine work, finance leaders also need to think about how roles develop. If teams spend less time compiling reports or carrying out repetitive administration, what should they do with that capacity?

Ideally, more time moves towards analysis, business partnering, forecasting and supporting better decisions.

There is also a skills question. Finance teams still need to understand how numbers are produced, challenge unusual results and recognise when something does not look right. Making work easier should not mean losing the knowledge required to question it.

Good AI adoption therefore needs a balance between efficiency and oversight.

The same applies to governance. Finance leaders need confidence around permissions, security, data use and accountability. If AI is helping produce an insight or recommendation, someone still needs to understand whether that information is appropriate to use and where human judgement is required.

Getting the foundations right

For organisations thinking about the next stage of finance transformation, there are a few straightforward questions worth asking.

Can we trust the information we are using? Are our core systems properly connected? How much work is still being done manually between those systems? Can leadership access useful information quickly enough? And if we introduce more AI, are the controls and processes underneath it strong enough to support that?

The aim is not to have the most technology.

It is to create a finance function that spends less time gathering and correcting information and more time understanding it, planning ahead and supporting the wider organisation.

Bringing the conversation to Hampden

These are some of the questions that will be explored at Hampden Park on 21 October, where Eureka Solutions and Lightyear are bringing finance leaders from across Scotland together to discuss what AI-ready finance looks like in practice.

The day will look beyond the headlines and focus on where AI is delivering value today, what finance teams need to get right before increasing adoption, how roles and skills may change, and where security, governance and trusted data fit into the picture.

The panel will also include Karen Martin from the Scottish FA, bringing an important perspective from within professional sport and helping reflect the reality that organisations are at very different stages of their finance and AI journeys.

AI may be changing what is possible for finance teams, but the organisations that benefit most are likely to be those that get the fundamentals right first.

Finance professionals interested in joining the conversation at Hampden Park can click here to register their interest.