Artificial intelligence in financial services

What’s actually changing in 2026?

With so much speculation and controversy about the impact artificial intelligence will have on financial services, you could be forgiven for tuning out the whole subject.

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You’ll have heard people predicting that AI will replace people on a large scale. But the more exciting possibility is that finance professionals who adopt AI will have greater opportunities and will play a vital role in steering their organisations. As always, the reality for finance teams is quite different from the headlines.

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How is artificial intelligence being used in financial services today?

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Research conducted by iplicit sought to find out how finance teams were already using artificial intelligence. The survey, conducted with Sapio Research, was carried out among 250 senior finance people at medium-sized organisations.

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It found:

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• 62% were using AI for invoice processing

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• 54% for expense and spend management

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• 49% for anomaly and fraud detection or financial reporting

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• 44% for strategic decision making; and

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• 46% for integration with other functions.

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AI speeds up the transactional work of a finance team through new and powerful automations. It also has the power to rapidly digest large amounts of data and spot outliers or anomalies. Finance teams are using that power to detect fraud and mistakes – flagging transactions of surprising value, for example, or those that happen at unusual times.

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This same capacity to handle a lot of data is allowing teams to accurately forecast cash flow without humans having to manually review a large volume of transactions. Since cash flow can be a make-or-break issue for a business, that’s a potentially decisive benefit. Teams are also using AI to produce reports and analysis that a person couldn’t feasibly accomplish in the available time – and to answer queries that the user types or speaks in ordinary conversational language.

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What does AI mean for in-house finance teams specifically?

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In-house finance teams often find themselves bogged down in routine and repetitive tasks. That tends to prevent them spending much time on the high-value, strategic work.

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Those routine tasks – the ones that revolve around processing and data entry – are the most susceptible to replacement by AI. But rather than representing a threat to finance professionals, AI can liberate them. With transactional work under control, finance teams can step back, take a strategic view of the finances and use insights from the data to help drive the direction of the organisation.

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AI takes care of such tasks as invoice processing, PO matching and transaction posting. It keeps track of credit control and flags anomalies. It can even draft commentary to help reveal insights about pricing or the profitability of individual accounts. But rather than removing humans from the process, it allows them to focus on the areas where they can make the biggest contribution, whether that’s identifying margin risks or advising on pricing.

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What are the benefits of AI in financial services?

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A financial services team that adopts AI wisely should quickly see tangible ROI.

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An early benefit is that routine tasks will happen much faster, with the time spent on tasks like invoice processing or data entry dramatically reduced. Complex calculations like deferred revenue and prepayments happen quickly and automatically. All this should significantly reduce the time spent on month-end tasks.

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At the same time, your data should improve. It will become more accurate, with so many opportunities for human error removed from the process. Complete data will be visible in real time, without all that work in spreadsheets. And it should be available in the form you want, whether in reports, dashboards or plain-language answers to specific queries.  With the team relieved of the manual burden, there should be less pressure and more opportunity to interrogate the data, using it to drive a more effective and profitable business.

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What should finance leaders look for in an AI finance tool?

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You may have a choice between AI that’s part of your finance system and a separate tool. It’s important that your data (and your customers’ data) isn’t exposed to the outside world, so any third-party tool should be subject to the same controls as the rest of your system. When AI produces reports or analysis, you’ll need to be confident that its outputs are traceable back to the transactions in your finance system for verification.

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As you weigh up tools, you’ll also need to consider how easy each is to use. AI chatbots respond well to natural human language. However, things can get more complex as you set AI to work on bigger, repeatable tasks and projects. Consider how much time and appetite your team has for learning and experimenting – and how steep the learning curve might be.

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While AI can do a lot of work on your behalf, you’re the one held accountable for the results. You’ll want confidence in its accuracy, reliability and security.

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What’s next for the future of AI in finance?

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Artificial intelligence will get ever better at integrating with all the platforms a finance team uses, pulling together data ever more efficiently for review and analysis. At the same time, it will be able to automate increasingly complex tasks, subject to human review and checks.

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Firms will increasingly be able to use AI to detect fraud and manage compliance – which will help them deal with a rising tide of AI-enabled scams and cybercrimes as well as the traditional human kind.

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We can also expect big advances in agentic AI. This is an intelligence that goes beyond following instructions and acts autonomously. It can plan, reason and take action across a range of tools to deliver an outcome that you’ve asked it to achieve. Users of systems such as iplicit will find their software doing more than recording the past. It’ll also help manage what comes next.

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FAQ

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What is artificial intelligence in financial services?

AI uses machine learning and automation to perform tasks that would otherwise require manual effort – such as processing invoices, reconciling transactions, detecting anomalies and generating real-time reports. It handles high-volume, rules-based work at scale, freeing teams to focus on analysis and decision-making.

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How is AI used in accounting and finance?

Common applications include automated invoice processing, intelligent bank reconciliation, real-time anomaly detection, and faster management reporting, all leading to faster month-end closes, better data and sharper financial insights.

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How do finance teams maintain control when using AI?

The key is that AI flags and alerts. Only people verify and approve. Well-designed platforms maintain a full audit trail of every automated action, keeping finance teams in control and regulated organisations audit-ready.

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iplicit brings AI into your finance platform in a secure, responsible way, transforming efficiency and freeing you to do the high-value work. You need just three minutes to take a quick tour.

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