How business leaders can turn AI into an everyday advantage

I spend a lot of time talking to growing businesses about AI, and one thing has become increasingly clear. Those conversations rarely begin with the technology itself. They usually start with the practical realities of running a business: forecasts that still aren’t reliable enough, finance teams rebuilding reports, or leaders waiting for accurate information because departments are working from different sources of data.

 

According to the Office for National Statistics, 35% of UK businesses with ten or more employees are now using at least one AI technology. However, AI usage remains “relatively shallow”, with few businesses reporting extensive AI deployment across their operations. While adoption is accelerating, integration is lagging, meaning many are experimenting with AI without relying on it as part of their normal work. That leaves much of AI’s practical value untapped, from reducing the time people spend finding information and handling routine work to spotting problems earlier and making decisions with better context.

 

Small and mid-sized businesses have their own challenges here. Much of the AI market has been designed for large enterprises with specialist technology teams or for individual consumers, which leaves growing businesses in an awkward middle ground. Growing businesses need technology that fits the way they already operate, without needing a large technical team to manage it.

 

Give AI enough context to be useful

Most businesses aren’t short of data. The difficulty is getting finance, operations and other parts of the organisation working from the same underlying information, particularly as a company grows and more complexity enters the picture.

 

Corston, the architectural fittings manufacturer, has seen this first-hand as it has expanded internationally. The company consolidated its business information in NetSuite, bringing data from different teams together to give people a more complete view across its operations and better information for decision-making. That same foundation is now supporting Corston’s use of AI. Through NetSuite, the business can use AI-driven guidance to explore and analyse financial and operational information, surfacing patterns or anomalies that might otherwise be difficult to spot and helping teams decide where to focus their attention.

 

When business information is already connected, people spend less time assembling it before they can start analysing what it means, while AI has a fuller picture to work from. The context around the numbers remains important. Financial and operational information viewed together can change the interpretation of a decision. An answer can make sense from the data and still be wrong for the business if that context is missing.

 

Fit AI to the work

A finance team trying to shorten its reporting cycle has different needs from an analyst exploring a forecast. For finance, the most useful AI may sit quietly inside the process, removing manual work or drawing attention to an exception. The analyst may want to interrogate the data in natural language, test an assumption and follow the answer somewhere unexpected.

 

Some processes will lend themselves to agents that complete a series of routine steps before asking someone to intervene. Employees shouldn’t need specialist technical knowledge to use any of these approaches. What they need is AI that fits the work in front of them.

 

When AI sits inside the system that already holds the data and runs the workflow, it has the information needed to support that work in context. It might help someone investigate a forecast, surface an exception at the point where intervention is useful, or move a routine step forward without another manual handoff.

 

AI can also expose parts of a process that no longer make much sense. An approval may still depend on someone gathering information manually, or a report may pass through checks that have simply accumulated over time. Putting AI into that workflow creates an opportunity to remove some of those steps instead of making an inefficient process move faster. Sometimes the improvement is less dramatic and a task simply stops taking as long as it used to.

 

Keep access consistent

Easier access to AI raises a practical issue. Employees may have new ways to reach business information, but the rules governing who can see that information must still apply.

 

Astrak, the construction equipment parts supplier, is using NetSuite to securely connect its business data with its chosen large language model. Employees can ask questions in natural language and get to the information they need without first finding the right report or navigating different parts of the system. Astrak can use its preferred AI while NetSuite remains the source of the underlying business information, with existing role-based permissions determining what each person can access. That gives employees a quicker route to an answer without weakening the controls already applied to the company’s data.

 

Those controls shouldn’t change simply because someone is accessing information through AI. Judgement remains important too. Routine queries can sit within defined boundaries, while decisions carrying greater consequences stay with the person accountable for them.

 

Look at what changes in the work

Counting users gives leaders a limited view of whether AI is working. What people do once the initial novelty has worn off is more revealing.

 

A finance team spends less time reconciling information at month-end. The planner who once maintained a parallel spreadsheet stops doing it because the forecast is reliable enough to use. A customer service adviser gets an answer without searching across several systems. Those changes are mundane, but impactful.

 

AI can generate a great deal of activity very quickly, but another report or piece of analysis may add little if nobody makes a better decision as a result. I’d pay attention to whether rework falls, or whether decisions that used to wait for information start happening sooner.

 

Eventually, people may spend less time talking about the AI altogether. They notice that a process is quicker, information is easier to find, or something that used to require several steps now takes one.

 

For growing businesses, that is a useful definition of an everyday AI advantage. AI has become part of the systems and processes people already rely on, with enough understanding of the business to make familiar work easier. They don’t need to think about AI every time they use it.

 

---

 

Nicky Tozer is EMEA Senior Vice President at Oracle NetSuite

 

Main image courtesy of iStockPhoto.com and your_photo