Ask suppliers what digital trading has given them, and cost savings or efficiency usually come up first. Ask what they value most, and the answer is rarely automation. It's visibility.
In the first post in this series, we looked at why construction finance is at a turning point, and how three pressures - the 2029 e-Invoicing mandate, rising invoice fraud and tightening fair payment rules - are converging at once. Here, we're digging into how AI tackles the risk side of that turning point.
Knowing an invoice has been received. Knowing it's been matched, queried, approved or paid. Knowing exactly what's holding things up if it hasn't moved yet. That single piece of certainty changes everything about how a finance team can plan and operate.
They start because neither side can see its status in the same way. Shared visibility builds shared confidence, and confidence changes behaviour.
The impact is measurable. Organisations that make this shift report first-time invoice match rates climbing from around 15% to 70%, with processing times falling from 12 days to just two.
Once finance teams have visibility, the next question becomes what to do with it. That's where AI starts to move from operational efficiency into real commercial decision-making, flagging the risks that visibility reveals before they turn into costs.
And those risks are real. Invoice fraud is a genuine, growing problem in construction. £3.9 million was lost in a single month between 2024 and 2025 across 83 UK cases, and construction and manufacturing accounted for 25% of all invoice fraud incidents that year. UK police have gone as far as launching a dedicated campaign, warning that the sector's complex payment chains make it especially vulnerable.
PDF-based invoicing is a known weak point here. Emails get intercepted. Bank details get changed. Fraudulent invoices get paid before anyone notices something's wrong.
Alongside fraud risk, the Fair Payment Code is putting real pressure on tier-one contractors to pay their supply chains on time, with genuine commercial and reputational consequences for those who don't. Suppliers, in turn, are under pressure to submit cleanly and chase efficiently.
Then there's the 2029 e-Invoicing mandate. From April 2029, all VAT-registered businesses will need to exchange invoices electronically. That's not just a finance change. It's an operational shift that touches systems, processes and trading relationships on both sides.
Yet, this is also a major opportunity for businesses, if they use this current window of time to put the proper infrastructure in place.
Here's the challenge most contractors face: without an established, many-to-many digital community, connecting every trading partner individually could take years. Building that network from a standing start, in the time available before 2029, isn't realistic for most organisations.
The good news is you don't have to build it from zero. Contractors are already achieving rapid adoption by connecting into an existing network of thousands of companies, rather than building their own community from scratch. CausewayOne already connects thousands of businesses across the construction supply chain, which means new contractors join a ready-made trading community rather than an empty room. Compliance readiness and AI-enabled trading both happen far faster as a result.
You can watch the full OnDemand webinar here.
For Accounts Payable teams, AI checks every invoice against known risk patterns before payment is released. That means it can flag:
A supplier's bank details changing shortly before a payment run
Duplicate invoice numbers or amounts across suppliers
Tax treatment that doesn't match a supplier's registered status
Payment timing that's about to breach a Fair Payment Code commitment
Miss any one of these manually, and the cost isn't just the fraudulent payment itself - it's the time spent unpicking it afterwards, and the fair payment record it leaves behind.
For Accounts Receivable teams, AI validates that an invoice meets each customer's submission rules before it's sent, not after it bounces back. That means it can catch:
A missing PO number before the invoice goes out
An incorrect VAT treatment for the customer
A mismatched delivery reference or quantity
A submission format that doesn't match the customer's portal rules
Crucially, how quickly these benefits show up depends directly on the size and maturity of the network behind the platform. Connect into an existing community of thousands of companies, and every participant benefits immediately from efficient processing and the intelligence built up across all those trading relationships. Adoption speeds up. Time to value shortens. And the intelligence available, sharpened by AI, does a better job of supporting your decisions.
In a market where risk is rising and tolerance for late payment is falling, this advantage becomes harder to ignore. The real value of AI won't be judged by how fast it processes a single transaction. It'll be judged by how effectively it helps teams prevent loss, manage compliance and protect commercial performance.
When AI is embedded in a connected, many-to-many trading platform, it can tackle all three pressures at once: saving time by cutting manual effort, reducing risk by flagging anomalies and building the structured data foundation compliance depends on, and supporting better decisions by surfacing intelligence from your own transaction data.
In the next post in this series, we'll look at why generic AI tools like ChatGPT or Copilot, however useful they are for everyday tasks, simply aren't built to handle the realities of construction trading.
At Causeway, we help construction finance teams turn visibility into action. See how CausewayOne flags fraud risk before payment is released.