No need to panic; it’s not replacing your team, it’s freeing them to focus on what matters.
If you work in finance you’ve probably heard and seen a lot of commentary about artificial intelligence replacing finance teams. Instead AI is fundamentally changing what they spent their time on, so for teams who have spent years buried in data entry and manual reconciliations, that shift can’t come soon enough.
What are finance teams using AI for right now?
iplicit surveyed 250 senior finance professionals at medium-sized UK organisations to answer this very question, and the results show a clear picture of where AI is already embedded in day-to-day financial operations.
62% use AI for invoice processing
48% for fraud detection and reporting
54% for strategic decision making
What’s striking is that AI is being used across the full spectrum of finance work, from transactional to strategic.
From data entry to decision-making: the real value shift
The tasks that AI typically handles best are the ones that usually eat up the most time but add the least value, like processing, matching or chasing. These are also the tasks that are prone to human error, due to their repetitive nature that is inherently error-prone at scale; not because of finance teams.
When these time consuming tasks are automated, finance professionals then get their time back. They instead can actively contribute in what happens next for the business; identifying margin risks, advising on pricing and contributing to strategic planning in ways that were previously impossible when month-end close took all week.
The practical benefits
AI-powered finance tools tend to show their results faster than organisations expect.
- Routine tasks like invoice processing and PO matching happen in a fraction of the time and often automatically
- Data accuracy improves significantly when human error is removed from repetitive entry
- Real-time visibility replaces spreadsheet snapshots which means complete, current data at any moment
- Fraud and anomalies are flagged automatically so unusual transactions or timing patterns get caught before they become problems
- Cash flow forecasting becomes faster and more reliable without needing manual transaction reviews
- Reports and analysis can be generated and even queried in plain language
What to look for when choosing an AI finance tool:
Whilst they have incredible benefits, not all AI tools are created equally and ethically, and there are some critical questions worth asking before committing to one.
- Is your and your customers’ data kept securely within the system, not exposed to third parties?
- Can you trace every AI-generated output back to the underlying transactions for verification?
- How easy is the tool to use day-to-day, and what’s the learning curve for your team?
- Who’s accountable when something goes wrong?
The best AI finance tools should feel like a natural extension of your existing workflows, not another new platform that you have to learn to use on top of everything else.
Where is AI in finance heading next?
AI is already transforming how finance teams detect fraud and stay compliant; reducing risk, tightening controls and removing the manual effort that slows everything down, but that’s just the current wave of AI.
The next wave is agentic: systems that can plan, reason and take action across multiple tools to achieve a goal you set. Less “assistive” and more “proactive”.
For teams using platforms like iplicit, this shift means your finance system can guide your next move, not just record the last one.
Ready to see what AI-powered finance actually looks like?
FinSweep helps mid-sized organisations move to iplicit smoothly so your team spends less time on the routine and more time on the work that matters. Find out more about how iplicit brings AI into finance systems in a safe and secure way.
Source: ipicit.com and AI for the FD Guide by iplicit.
