Every week, one report used to take hours to put together. Someone on the team would pull data from several systems, compile it in Excel, format it for presentation, then check the whole thing line by line before it went anywhere. Multiply that by the weeklies, the month-end close, and the annual deadlines every finance team runs to, and you have a function that spends most of its time producing numbers rather than understanding them.
As ClearPoint brings AI into its finance team, it is steadily taking over the transactional work. Everyone's role is shifting with it, away from compiling and towards analysis and business partnering. The team is still early in the journey, and that was a deliberate choice by ClearPoint's CFO, Neil Robson. Finance keeps being named as one of the functions most exposed to AI, and he would rather lead that shift than have it happen to the team.
That same weekly report now runs differently, with AI connecting into the data sources, pulling the information automatically, and presenting it back through a dashboard the team built itself. The hours the team used to spend on that report now go into analysing the outputs and working out what the numbers are telling them, rather than pulling it all together in the first place. They didn't end up with spare capacity as a result, just a different kind of work.
The same shift let the team retire a much more expensive piece of reporting infrastructure. When Neil joined ClearPoint around three and a half years ago, it ran a data warehouse and Power BI to handle reporting, at a cost of roughly $80,000 a year, on top of the developers needed to build and maintain it. Even then it was not flexible enough to keep up as the company's reporting needs changed. Now he can connect the tools to the company's data sources, pull everything together, and produce a customised dashboard structured exactly the way he wants, without being a technical person, for the cost of a monthly licence.
The gains from that are already measurable, with one automated dashboard saving at least three hours every week, and monthly reporting that once took days now taking a fraction of that. The point was never to do less work, but to free the same team to spend more of its time on analysis and on partnering with the business.
Finance leaves no room to be casual about accuracy, because what the team reports has to be true, and everyone on the team knows how unsettling it can feel to introduce something new into that. That is why they put the structure in place before scaling anything up.
Neil built a finance intelligence framework of 27 capabilities the team is assessed against, one of which is governance and controls. The rule underneath all of it is a human in the loop. AI can produce output that reads as entirely convincing, which is exactly why someone with the expertise still has to confirm it is accurate and verifiable. The tools save the team time on generating the work, but they do not remove the responsibility to check it.
The importance of having a human in our finance team cast their eye over the outputs, to make sure they are verifiable and accurate, is the most important thing.
Neil Robson - Chief Financial Officer at ClearPoint
This quarter the team is documenting every core process to create a clear baseline of how it works today. A second pass then redesigns each process to introduce AI where it fits, with the right controls built in, rather than bolting tools on piece by piece. The whole approach runs on a 90-day improvement cycle, so change stays constant but measured.
Systems integration is where most finance people feel most nervous, and Neil was no different. For now, the team's AI retrieves data from the accounting systems rather than writing back into them. Claude connects to the systems, draws information from multiple sources into one place, and reports up from there. Letting AI write into finance systems would need far more review, testing, and control before the team would trust it, so they have not gone there yet.
There are two ways to look at AI in a finance team. One treats it as a way to cut cost, which usually means cutting people. That is not the view Neil takes. The finance team uses it to expand the frontier of work it can do, and both the team and ClearPoint's chief executive see it the same way.
Every finance leader has a list of projects they have never had time to start. Continuous improvement needs time, and business as usual rarely leaves any. AI creates the space to finally work on the things that have been put off for some time, reviewing the team's own processes among them.
It also lets the team grow with the business without growing headcount. As ClearPoint has expanded into new regions over the past year, with new legal entities, tax obligations, and compliance requirements to manage, the same-sized team has been able to keep pace. Along the way, the tools have acted as a mentor on unfamiliar overseas tax and compliance, and audited legacy spreadsheets to surface errors that had gone unnoticed for years. They have also helped the team write thorough business cases far faster, often raising issues for the board that the team might otherwise have missed.
The nature of the team's work will look very different in six months, and different again a year after that. The team's job is to be stewards of the numbers, but the bigger prize is the time it frees up to partner with the business and drive real value back into it.
What excites Neil most is that every single person on the team is on board. They see this as a chance to lead in their field, from the CFO through to an accounts assistant, and their enthusiasm for finance has gone up, not down.
Plenty of people feel threatened by AI, and that reaction makes sense. The real risk, though, is not the technology itself but standing still and never working out how your role changes around it. The team has been fortunate to have talented AI people inside ClearPoint to lean on, and executive support to explore the tools properly, inside a structure that keeps the controls and governance firmly in place.
If you are considering this and have not started yet, four things have mattered most for Neil's team.
For today's CFO and finance team, building, monitoring, and refining these AI workflows is now part of the role. A human still sits at the centre of it all, overseeing the work, holding the controls, and verifying what the tools produce.
The team is only one 90-day cycle in, and the gains are already there to see. The move from transactional work to business partnering is the future for every finance function, not just ClearPoint's.