How AI Is Actually Being Used in Transaction Services in 2026

In 2026, AI in transaction services is moving from pilot to standard practice across advisory firms of all sizes.

There is no shortage of commentary about AI changing professional services. Most of it describes a future that has not arrived yet. This is about what is actually happening now.

Where AI has genuinely landed in TS

The use cases that have taken hold in transaction services are not the dramatic ones. They are the unglamorous, time-consuming tasks that have always sat at the bottom of the work hierarchy.

Extracting data from management accounts. Mapping inconsistent chart of accounts across periods. Building the first cut of monthly revenue and EBITDA runners. Flagging where numbers do not reconcile before anyone has asked the question.

These are the tasks where AI has found its footing in TS practices, and the reason is simple. They are rules-based, repetitive and take significant time from people who could be doing more valuable work.

What most firms are not doing yet

The majority of advisory firms have not yet formalised how AI fits into their FDD workflow. Individual team members are using general-purpose tools in ad hoc ways. Some are using ChatGPT to draft management question lists or summarise sections of an information memorandum. A smaller number are using purpose-built platforms designed specifically for financial due diligence.

The gap between firms that have structured this properly and those that have not is starting to show in delivery times and margin.

The quality of earnings question

QoE is the area where advisory firms are most cautious about AI, and rightly so. A QoE adjustment needs to be defensible. The reasoning behind it needs to hold up in front of a client and, in some cases, in front of a lender.

What AI can do well is surface candidates for adjustment. Unusual patterns in revenue recognition. Cost items that appear in some periods and not others. Margin movements that do not track with the stated business narrative.

What it cannot do is make the final call on whether something is a genuine QoE adjustment or an operational blip. That still requires a professional with context. The firms getting this right are using AI to generate the list and experienced judgement to refine it.

The client conversation is changing

Something that does not get discussed enough is how AI is changing the early client conversation on a deal. When a firm can turn around an initial data assessment within hours of receiving the data room, the kickoff meeting looks different. There are actual numbers on the table. There are questions worth asking from day one.

That changes the dynamic with management teams and with the acquirer. It signals a level of preparedness that manual processes simply cannot match on the same timeline.

What the next 12 months looks like

The firms that are thoughtful about this now will have a meaningful advantage within the year. Not because AI will do the FDD for them, but because they will be able to take on more work, deliver faster and protect margin in a market where fee pressure is not going away.

The advisory teams still doing everything manually are not going to disappear overnight. But the gap is opening and it will become harder to close.

PinpointAI is purpose-built for transaction services teams. It handles the data ingestion, normalisation, and initial analysis so your team can spend their time on the work that matters.