How UK mid-market firms can get ahead of rising costs

Margins are already thin. Then a supplier raises prices without warning, a shipment is delayed, and the weekly cost report lands two days late. For many UK medium-sized businesses, this is not an unusual week. It is most weeks.

Research by BDO finds that 46% of medium-sized UK businesses expect rising costs and supply-chain disruption to be their main concerns in the coming months. That figure points to a structural problem, not a temporary blip. When cost pressure and supply volatility arrive together, the businesses that cope best are not necessarily those with the deepest reserves. They are the ones whose leaders see the warning signals earliest and act on them fastest.

AI is changing how quickly those signals surface.

The pressure building on UK mid-market businesses

Medium-sized businesses occupy a difficult position in the current environment. They are large enough to carry complex supplier relationships and multi-site operations. They are also small enough that a single disrupted supply line or an unexpected cost spike lands directly on the bottom line. Fire protection manufacturers and installers pricing jobs on bought-in components know this well.

CFOs and operations managers at this scale often find themselves managing by exception, but the exceptions keep multiplying. A cost overrun in one category, a delayed delivery in another, an energy price movement that invalidates last quarter's model. The data to track all of this usually exists somewhere across ERP systems, spreadsheets, and supplier portals. Pulling it together into a coherent picture takes hours, sometimes days.

By the time a report reaches the leadership team, the moment to intervene has often already passed.

What the data reveals about decision timing

The BDO finding is not simply about costs being high. It is about certainty being low. When nearly half of mid-market businesses are flagging supply-chain disruption as a top concern, the underlying problem is that leaders cannot see far enough ahead to plan with confidence.

This is a forecasting problem as much as a cost problem. Businesses that can identify a supplier risk or a cost trend three weeks earlier than their competitors can act on it. They can renegotiate terms, adjust production schedules, or build alternative sourcing relationships before a disruption becomes a crisis.

The gap between reactive and predictive management is not primarily a technology gap. It is a data-access and decision-speed gap. That is exactly where AI can change the picture.

Why this is 80% a people and process problem

At gecco, we see a consistent pattern in mid-market businesses facing this kind of pressure. The technology to surface cost and supply-chain data faster already exists in most organisations. The actual bottleneck is usually a small number of people, often a finance analyst or an operations coordinator, who spend the majority of their week compiling reports manually.

This is the 80% that rarely gets discussed. The conversation tends to focus on which analytics tool to buy. The real question is what happens to the working hours currently consumed by manual data gathering. Until those hours are freed, the organisation has not gained decision speed. It has just added another platform to maintain.

AI adoption in this context works best when it starts with the reporting workflow itself. Automating the compilation step means the analyst is reading the report on Monday morning rather than finishing it on Wednesday afternoon. That shift changes what decisions the leadership team can make, and when.

How AI Assistants address the forecasting gap

Businesses tackling this kind of challenge are using AI Assistants connected to their existing data sources to do several things that were previously manual and slow.

The first is exception identification. Rather than reviewing an entire cost report line by line, an AI Assistant can be configured to surface only the lines that deviate from expected ranges. A CFO who previously spent two hours reviewing a report can focus on the six items that actually require a decision.

The second is trend flagging. AI Assistants can monitor supplier lead times, commodity price indices, and internal order data simultaneously. When a pattern emerges that historically precedes a disruption, the assistant flags it before the disruption materialises. This moves the conversation from reactive to anticipatory.

The third is narrative generation. Turning raw data into a board-ready summary is a task that typically takes a skilled finance professional an hour or more. An AI Assistant can produce a first draft of that summary in minutes, drawing on structured data and pre-set context about the business.

None of these applications require the business to replace its ERP or restructure its finance function. They work with the data and systems already in place.

Practical applications for CFOs and operations managers

For a CFO managing cost pressures across multiple categories, the most immediate application is automated cost monitoring. The assistant receives data from the ERP, compares actuals against budgets and prior periods, and sends an alert when a threshold is crossed. The CFO sees the issue the same day it emerges, not the week after.

For an operations manager dealing with supply-chain volatility, the value comes from exception-based supplier tracking. Rather than manually chasing delivery confirmations, the assistant monitors expected arrival dates against confirmed despatch information and escalates discrepancies automatically. The operations manager spends time resolving exceptions, not finding them.

Both applications share a common feature. They reduce the volume of low-value information-gathering tasks and increase the time available for decisions that actually require human judgement.

Considerations before implementing AI in financial reporting

Implementing AI in cost monitoring and supply-chain reporting is practical for most mid-market businesses. It is not, however, free of considerations.

Data quality is the most consistent constraint. An AI Assistant is only as reliable as the data it draws on. If the ERP contains inconsistent cost codes, or if supplier data arrives in multiple unstructured formats, the assistant will surface noise alongside signal. Organisations that invest time in data standardisation before deployment see materially better results.

Confidence calibration is a second consideration. AI Assistants can identify patterns and flag exceptions with speed. They cannot substitute for the contextual knowledge that an experienced finance or operations professional applies when interpreting those signals. The assistant informs the decision. The human makes it.

Finally, adoption takes time. Introducing an AI Assistant into a reporting workflow changes how team members spend their day. That change needs to be introduced with clear communication about why it is happening and what the team's role becomes. The technology implementation is rarely the hard part.

Making this work for your business

For CFOs and operations managers who want to move from reactive reporting to predictive risk handling, the starting point is usually identifying the single reporting workflow that consumes the most manual time. That is the highest-value place to begin.

gecco's AI Assistants are built to connect with existing data environments and surface cost trends and supply-chain signals in near real time, giving finance and operations leaders the information they need before a disruption becomes a crisis.

The shift from reactive to predictive does not require a large implementation project. It requires a clear view of where decision lag is costing the business most, and a structured approach to closing that gap.

Ready to see where AI fits in your planning cycle

If your team is weighing up where AI can reduce the decision lag in cost and supply-chain management, the AI Readiness survey is built to surface exactly that.

Take the AI Readiness survey. You will receive 65+ free resources and a custom AI Readiness report based on your answers. From there you can book a free 30-minute showcase to walk through the results with a gecco adviser.

Website · LinkedIn · Case Studies · Newsletter