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Why a simple project question can take so long to answer
A project manager and a finance director can look at the same engagement and reach different conclusions about the margin it is likely to make. The financial report shows costs recorded so far. The project manager knows that additional design work is likely and that a change to the fee is still being discussed.
To decide whether the project needs attention, they need to agree what the remaining work is likely to cost and which fees the client has approved. Some of the assumptions behind that position were made when the firm was bidding for the work. A useful forecast depends on understanding what has changed since then.
When I discuss AI with a professional services firm, I start with how people make these decisions. In an architecture, engineering or cost consultancy, a project review is a useful example. It draws on information from several teams, gathered at different points in the engagement.
The information behind a project forecast
A dependable forecast combines costs already recorded with a current estimate of the work still to be completed. It should reflect the agreed scope and distinguish approved fees from changes still under discussion.
Late time recording can understate the effort already spent. An old estimate of the hours needed to finish can hide an emerging overrun. A project team may be absorbing additional work while the commercial discussion with the client remains open.
The project manager needs a current estimate of remaining effort, and the client lead may need to agree a change to the scope or fee. Finance needs that position explained before relying on the forecast for reporting. Getting the figures together can itself take several spreadsheets and a round of emails.
I want to know who updates the estimate and what happens when the expected margin falls. Someone needs the authority to act on what the review reveals.
How the proposal becomes the project
The starting point for that forecast is set before delivery begins. A proposal contains assumptions about the effort required, the people available and the work covered by the fee. Those assumptions need to reach the project manager when the appointment is agreed.
Relevant project experience helps the team judge what it will take to deliver. Shared client information can reveal relationships held by colleagues in another office. Someone still needs responsibility for the account and authority to decide whether the pursuit deserves the firm's time.
Once the work is won, an agreed handover gives the delivery team a basis for managing it. If the client later asks for additional work, the project manager can assess the request against the original scope and raise the commercial implications with the client lead.
Where AI could help with the review
An AI application could retrieve the agreed scope and relevant client correspondence, then prepare a summary of proposed fee changes for the project manager to check. Each point should link to its source. The manager can compare that summary with the current forecast and follow up on anything still awaiting agreement.
Access to the right records and the user's permissions need to be established before testing. The reviewer also needs to check whether more recent correspondence changes the position.
Some improvements will come from clearer handovers or better use of existing reports. The case for AI needs to explain which task it will help someone complete and how the firm will check the result.
Before commissioning a pilot, choose a project question that currently takes too much effort to answer. Follow it from the agreed scope through to the latest forecast. Establish where the delay occurs and what would help the people involved act sooner. That gives the investment a specific purpose and a benefit the firm can assess.
Our whitepaper explores practical AI use cases across winning work, project delivery and knowledge reuse in AEC. It includes a focused 90-day plan for firms deciding where to begin.
Download From AI Pilots to Better Decisions in AEC
George Morton works with professional services firms at HSO and has more than a decade of experience in the sector. His focus is how business applications, data and AI support the way firms win and deliver work.
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