AI is everywhere. Construction leaders know it, talk about it, and increasingly feel pressure to do something about it. But knowing AI matters and knowing where it genuinely adds value are two very different things.
That gap – between intention and financial reality – was at the heart of our recent webinar with Microsoft. Focusing on real, practical AI use cases that improve financial visibility and protect margins, the session explored where AI is already delivering value in construction finance today.
Microsoft’s AI Business Process Lead, Elliott Poulter, and Business Central Specialist, Sean Allan, bring key insights to construction’s AI conversation, offering clear guidance for contractors looking to scale in a margin-pressured environment.
Here are their top six takeaways for construction leaders.
1. AI wins margins by speeding up financial insight – not by being clever
The biggest enemy of construction profitability isn’t bad intent or poor decision-making. It’s late information.
This point surfaced time and time again in our webinar: by the time many finance teams have completed CVRs, analysed variances, or fully understood why margins have shifted, the project has already moved on. More work has been completed, more money has been committed, and the window to intervene has closed.
Elliott explains how AI comes into the picture: it doesn’t create value by being impressive or complex, it creates value when it shortens the distance between what happens on site and when finance can see, understand, and act on it. In construction, where cost movement is constant and margin pressure is relentless, that timing gap is often the difference between control and damage limitation.
Using tools like Copilot within Dynamics 365 Business Central, finance teams can interrogate live data rather than waiting for month-end. Cost spikes can be explored as they occur, not weeks later. Cashflow forecasts can be built from current data rather than static spreadsheets. Commercial and finance teams can ask simple, natural-language questions — such as “Why has concrete spend increased this month?” — and receive immediate, contextual explanations grounded in their own data.
2. CVRs and margin control are prime targets for AI impact
Few processes matter more to construction profitability than the CVR — and few are as exposed to delay, manual effort, and human error.
In the webinar, it became clear just how common it still is for CVRs to start weeks after month end, take days to assemble, and rely heavily on spreadsheets stitched together from multiple systems. By the time the numbers are reviewed, the financial reality they describe is already out of date. Costs have moved. Decisions have been made. Margin erosion has already happened.
AI changes this. Not by reinventing the CVR wheel, but by accelerating and strengthening them. With data already structured in an ERP like Dynamics 365 Business Central, Copilot can help finance and commercial teams interrogate cost movements as they occur, not retrospectively. Instead of manually reconciling figures across spreadsheets, teams can ask direct questions of live data, identify anomalies earlier, and understand the reasons behind why margins are shifting.
Earlier CVR insight means earlier conversations with site teams, procurement, or subcontractors. It means understanding where costs are trending before they crystallise into losses. And it means senior leadership making decisions based on current reality, not last month’s picture.
Faster CVRs restore their original purpose: to act as early-warning detection for financial risk.
3. Variations are where AI can quietly save (or lose) you serious money
If CVRs are the heartbeat of construction finance, variations are often where margins quietly leak, or disappear altogether.
During the session, Sean and Elliott highlighted how variation management is still dominated by disconnected processes, creating chain reactions of lost visibility. An on-site issue becomes an email. That email becomes a follow-up. Documents are stored in inboxes, spreadsheets, or folders only certain people can see. Approvals are delayed. Financial impact is unclear. And by the time the variation appears in a CVR, it’s too late to control the outcome.
AI connects the dots by ensuring nothing falls through the cracks. Emails, documents, photos, approvals, and financial values can all be surfaced in a single workflow. Copilot can track where a variation sits in the process, who needs to act next, and what the projected cost impact is long before it hits the bottom line.
This matters just as much for cashflow as it does for margin. Variations that aren’t properly logged, approved, and tracked are far more likely to be billed late — or not at all. AI doesn’t need to replace the judgement needed to negotiate or agree a variation, but it can remove the operational risk that causes value to be lost simply because information wasn’t visible at the right time.
4. If you don’t provide safe AI, your teams will bring their own
One of the most important (and sobering) points raised was around governance.
Microsoft’s Elliott Poulter was clear: if organisations don’t give teams a secure, sanctioned way to use AI, people will find their own solutions. Public AI platforms are already being used to summarise documents, analyse data, and draft content, often without any consideration for data sensitivity or compliance.
In construction finance, this creates serious risk. Commercial rates, subcontractor costs, payroll data, and cashflow forecasts are not information you want being fed into public models that may retain or reuse that data. Once it’s shared, control is lost.
Copilot is designed to address this problem head-on. It operates within existing permissions, respects security roles, and uses company data without training public AI models on it. For finance and IT leaders, this is critical. Company-wide AI adoption doesn’t just extend to productivity gains; it also serves to protect sensitive commercial information while still enabling teams to work smarter.
The reality is: AI is already being applied by end users. The question is: is it happening safely, transparently, and under your control?
5. AI should be a response to capacity pressure, not a technology trend
A recurring theme throughout the session was the mounting pressure to drive AI adoption, especially in construction where we’re usually late to the party.
Increasingly so, construction businesses are being asked to deliver more with fewer people. Skills shortages persist. Projects are more complex. Reporting demands are heavier. And finance teams, in particular, are expected to provide faster insight without additional headcount. In fact, 80% of the global workforce say they lack enough time or energy to do their work.
AI, in this context, is an enabler. It absorbs repetitive, low-value tasks that consume time but don’t require judgement: reconciling data, searching for information, drafting first versions of reports, or answering routine questions. This frees experienced professionals to focus on what actually protects margin: analysis, challenge, and decision-making.
It’s crucial to note that when applied correctly, AI doesn’t remove the need for finance or commercial expertise. It actually amplifies it by removing the friction that slows teams down. In an industry under sustained capacity pressure, that distinction matters.
6. AI delivers the biggest gains when focused on one painful process
Rather than advocating for large-scale, sweeping transformation, Microsoft’s advice was pragmatic: start where it hurts.
AI adoption often fails when it’s positioned as a silver bullet, but problems of this magnitude can’t be plastered over with one quick-fix solution. Instead, AI adoption succeeds when it’s applied to a specific, well-understood problem with a tangible and measurable outcome. This could be time saved, errors reduced, or visibility improved.
In construction finance, those pain points are rarely hard to find.
Where CVRs take weeks, purchase invoices bottleneck approvals, and cashflow forecasts rely on static spreadsheets — that’s exactly where construction businesses should be looking. These are ideal starting points because they’re already understood, already painful, and already costly.
By focusing AI on a single process, businesses can build confidence, demonstrate value, and create momentum. From there, adoption becomes organic rather than forced. Teams see the benefit in their own work, and that’s when AI stops being “a project” and starts becoming part of how the business operates.
Construction doesn’t need to be last place
“Construction always seems to be last to come to the party when it comes to technology, and that mindset has to change.”
That sentiment captured one of the most important undertones of the session. Only a small fraction of construction businesses would say AI is fully embedded today. Most are either exploring, dabbling, or deliberately delaying.
But Microsoft’s Elliott brings the point home: this is no longer a future problem.
AI is already capable of changing how finance teams report, how commercial teams manage risk, and how leadership teams consume information. The organisations that benefit most won’t be the ones chasing the latest tech fad; they’ll be the ones taking a disciplined, purposeful approach.
That means fixing data foundations before expecting AI to deliver insight, targeting real financial pressure points, and rolling AI out with governance, security, and clear ownership in mind.
If you’re thinking about how to address financial pressure, modernise your systems, and introduce AI in a way that genuinely supports your teams, we’d be happy to continue the conversation.
Watch the full webinar, where we explore real construction AI use cases and share practical guidance on how finance and commercial teams can start applying AI today.
