Most businesses are past the point of asking what AI can do. They have deployed it, seen it work and discovered the limits of simply switching it on. The harder and more important question now is: “How do we make AI work better for our businesses, our people and our customers?”
Increasingly, capability is not the issue. AI can answer a phone, write an email, analyse huge amounts of data and hold a remarkably natural conversation with a customer. The opportunity now is to work out how to deploy that capability brilliantly and how to move from simply having AI to getting real value from it.
Start with the outcome, not the technology
The pressure on businesses to adopt AI has been enormous, and many organisations have moved beyond experimentation into real-world deployment. The challenge is no longer simply keeping up with competitors; it is making sure AI is solving the right problems, removing friction and delivering meaningful results.
But the most successful AI strategies do not start with the technology. They start with the problem you are trying to solve. Pete Hanlon, Chief Technology Officer at Wrexham-based Moneypenny, believes the better approach is to ask what outcome you are trying to achieve first. Is there a genuine customer problem? Is there a repetitive task taking people away from more valuable work? Is there a process that could be made simpler?
If the process is already frustrating, confusing or poorly designed, automating it rarely fixes the underlying problem. You can end up delivering a bad experience more efficiently. Get the process right first, however, and AI has the potential to make it dramatically faster, smarter and more scalable.
The best AI knows when to act and when to escalate
Customer service is a good example. At Moneypenny, the company is seeing first-hand how much AI can transform the way businesses manage conversations. Its AI Receptionist can handle enquiries instantly, consistently and at scale, helping customers make bookings, check appointments, access information and get where they need to go without unnecessary friction.
But truly intelligent AI is not about forcing every conversation through the same journey. A straightforward booking may be handled entirely by AI. A complex, sensitive or high-value conversation may benefit from human judgement. The most sophisticated systems can recognise that difference and respond accordingly.
The intelligence is not simply in answering the question; it is in understanding the context, knowing what action to take and recognising when another route will deliver a better outcome. For Hanlon, reliability comes from putting the right architecture and boundaries around AI so businesses can deploy it confidently. Some decisions can be automated confidently. Others need verification, and some should trigger a human handover.
When it does escalate, the handover matters. If a customer spends five minutes explaining something to AI and then has to repeat the entire story to a person, an extra barrier has been created rather than removed. A good handover should bring the context with it so the person can pick up the conversation naturally.
Trust has to come with capability
The same thinking applies beyond customer service. As businesses give AI access to more information and allow it to take more actions, questions around data, security and governance become increasingly important. Getting these things right is not a reason to slow AI adoption; it is what enables businesses to get more from the AI they have already adopted and expand its use with confidence.
Just because a system can access information does not mean everybody using that system should be able to access it. And just because AI can make a decision does not mean that decision should happen without oversight. Businesses need to decide where those boundaries sit: what AI can do independently, what requires verification and where a person needs to remain accountable.
That may sound less exciting than talking about the latest AI breakthrough, but this is what turns impressive technology into AI that can operate reliably at scale and technology that businesses and customers can genuinely trust.
The age of intelligent automation
The biggest technology opportunity for businesses in 2027 will not simply be adopting more AI. It will be turning the AI they already have into something that works harder and delivers better outcomes. The winners will be businesses that build AI into the way they operate and use it confidently wherever it can improve speed, scale, availability and customer experience, while designing clear pathways for the moments where human judgement adds something different.
AI is extraordinarily good at speed, scale and handling structured tasks. People bring judgement, empathy, creativity and the ability to understand situations that do not fit neatly into a process. The opportunity is not to choose between the two. It is to design experiences that make the best use of both.
AI should make simple things simpler, remove repetitive work and help customers and employees make progress. And as it becomes more capable, the organisations that succeed will be those that understand how to put that capability to work intelligently. Sometimes it should act. Sometimes it should check. And sometimes it should recognise that a person will deliver the better outcome and step aside. That is not AI failing. That is intelligent AI doing exactly what it was designed to do.
