AI costs for small businesses: what should you budget for?

The costs of AI used to be predictable. Now it depends on how you use it. John Speed, the founder of IT solution provider Heliocentrix, explains how AI companies are now pricing their software – and what this means for your IT strategy if you want to keep your costs under control. 

How AI costs are changing 

A client recently said something that I think many SMEs will recognise: “The AI is useful, but I don’t know what it should cost anymore.” They were not questioning whether the technology worked. They could see the value. What unsettled them was more basic: they could no longer tell, with confidence, what “normal” should look like from one month to the next. 

That reflects what many SMEs are now starting to experience. Traditional software has usually been predictable. You buy a licence, pay per user and build the cost into the business. It may increase over time, but the model is understandable. AI is different because the cost is increasingly linked to activity, not just access. 

A simple way to think about this is to compare AI with paying for an assistant, PA or virtual assistant. If you ask them to book a meeting, send a reminder or copy information from one place to another, that is fairly predictable work. If you ask them to read through a messy inbox, work out which messages matter, decide what needs action and draft responses in your tone, that is more valuable work, but it also takes more time and judgement. 

AI is starting to work in a similar way. The cost is no longer just about whether you have access to the tool. It increasingly depends on the type of work you ask it to do, how often you ask it and how much judgement is involved. In Microsoft Copilot Studio, for example, agent usage is measured through Copilot Credits, and the number consumed depends on how the agent is designed, how often it is used and which features it uses. 

The budget implications of changing AI cost structures 

We are already seeing this shift in the market. Microsoft has started moving some AI services towards usage-based charging, where businesses pay according to consumption rather than only through a fixed monthly licence. That does not mean AI is becoming unaffordable, but it does mean businesses need to understand what activity is being charged for and design their use of AI with that in mind. 

This is why two businesses can use similar AI tools and see very different costs. One might use AI occasionally to draft emails or summarise meetings. Another might use an agent to monitor inboxes, search customer records, update systems and create follow-up tasks. Those are not the same level of work. 

The practical question for SMEs is therefore changing. It is no longer only “how many people need a licence?” It is “what work are we asking AI to do, how often will it do it, and is the outcome worth the cost?” 

The mistake I see businesses making is treating AI as a feature to switch on, rather than a costed business process to design. That mindset matters. If you simply enable AI and hope value appears, costs can drift and results can be inconsistent. If you design the process properly, you can decide where AI genuinely adds value, where simple automation is enough, and where the work should be changed altogether. 

AI cost control starts by classifying the work 

Before adding AI to a process, classify the task. The test is not “can AI do this?” In many cases it can. The better question is “should AI do this, or is there a simpler, cheaper and more controlled way?” 

If the work needs interpretation or judgement, AI may be useful. That might include understanding a customer email, identifying the real issue, drafting a sensible response, summarising a complicated email chain, or explaining what has changed across several documents. 

If the work follows fixed rules, AI may be unnecessary. Sending a standard reminder when a task is overdue, moving an approved action into a planner, or copying a KPI from a known source can often be handled by a simpler workflow. That is usually cheaper, faster and easier to control. 

If the work is low-value or unclear, the best answer may be to stop doing it. AI can make inefficient processes run faster, but that does not automatically make them worth keeping. Cost control starts by using AI where judgement creates value, and using automation where the rules are already known. 

Start with one measurable process 

A sensible starting point is not the most impressive AI demo. It is one process that happens regularly, takes time, has a clear business outcome and can be measured. 

For example, start with a process such as handling common customer enquiries, preparing meeting follow-ups, triaging support requests or collecting information for a regular report. Map how the work is done today, estimate the time it takes, decide where judgement is required and then design the AI or automation around that. 

This avoids the usual trap of trying to “use AI more” without knowing what problem is being solved. It also gives you a way to judge value. If the process saves two hours a week, improves response time or reduces missed follow-ups, you can compare that benefit against the cost of running it. 

Where your IT provider can help 

Getting value from AI is not only about choosing the right licence, model or tool. It depends on two practical foundations: how well your information is structured, and what controls are in place around how AI is allowed to use it. 

The first foundation is information structure. Poor folder layouts, duplicated files and unclear document ownership used to be frustrating but manageable; someone might waste time looking for the latest version. With AI, the issue is more significant because the tool may be searching across many places at once and drawing conclusions from what it finds. If the source information is messy, out of date or poorly labelled, the output is more likely to be unreliable. 

The second foundation is guardrails. AI needs boundaries around what it can access, which actions it can take, who can use it and how much it can consume. Without those controls, there is a risk of sensitive information being surfaced to the wrong people, actions being triggered without enough oversight, or usage costs creeping up unnoticed. 

Your IT provider should help review both areas: the structure of your information and the controls around AI usage. That includes SharePoint and OneDrive structure, permissions, sensitive data, workflow design, usage monitoring and regular reviews to make sure the cost remains proportionate to the value. 

Questions worth asking to keep AI costs under control 

If you are starting to rely on AI more heavily, the useful questions are practical: 

• What work are we asking AI to do? 

• Does that work need judgement, or does it just follow rules? 

• Is our data organised well enough for AI to use? 

• How long would the same work take a person? 

• Which process should we test first? 

• How will we measure value against cost? 

AI has not suddenly become unaffordable for most SMEs. What has changed is the discipline required to manage it. The businesses that get the most value will not be the ones that use AI everywhere. They will be the ones that choose the right work, design the process properly, keep their data usable and measure whether the outcome justifies the cost. 

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