A few years ago, everyone started getting very overexcited about the technology known as ‘Artificial Intelligence’. Having watched sci-fi films for decades, the scenes on screen were coming to life. Some feared the robots were coming to take all of our jobs, while others realised early on how helpful these new tech tools could be in getting tasks done that were previously laborious, tedious or even nigh-on impossible.
Now we’re in a sort-of twilight zone where some companies have gone all-in, using AI for every single task they can possibly automate, while others are still refusing to touch anything more technical than an email. Meanwhile a third (and sizeable) set of businesses are trying to work out exactly how to implement AI and which of the multitude of tools available might be the right fit for them.
Change is always people-led
The secret, which isn’t really a secret at all as the change management sector has been loudly shouting about it for decades, is keeping people at the centre of decision making, no matter what decision is being made. In the case of AI, there are plenty of questions leaders can be asking themselves to ensure their plans are truly aligned with what’s best for their employees. Is this tool going to make life easier for my team? Will it speed up processes for staff, or make them more complicated? And, most importantly of all, how are teams going to feel about adapting to all this new technology being thrown at them?
Rather than being blind-sided by fancy technology which looks really impressive, the focus must remain on how well it can fit into the existing structures in place in the business. Because when you start asking people to work in a completely different way just because you’ve been awestruck by an extravagant piece of tech (which probably has an equally extravagant price tag attached to it), that’s when you’re likely to run into trouble.
First off, you need to fundamentally understand the benefits the AI tool is going to bring to your business, or to a specific department if it has a specialised function. Instead of echoing the jargon and IT-speak that often surrounds new technology, being able to explain in a way that people ‘get it’ speaks volumes. Teams are far less likely to resist change if they can understand the end benefits – if they know that after a few months of bedding in, the tech will save them a certain amount of hours per week that they currently use to undertake repetitive admin tasks, for example.
By sharing tangible ways in which the roll-out will help them do their jobs even more effectively, it becomes easier to allay any worries surrounding the change. Encouraging feedback every step along the way also seems like an obvious point, but can often be forgotten in all the excitement around AI. Even better, why not get the teams who will actually utilise the new tools every day to test them out, so they can tell you which work most effectively and align most smoothly with their existing processes? Through empowering teams to take this active part in the very first stages of the project, this not only rapidly builds AI literacy but also perhaps uncovers benefits of specific tools that you’d not initially thought of, it also helps to alleviate the worries staff might have about implementing AI, if they have already had the chance to try out the technology.
A thorough testing process also cements the business case to justify financial outlay, as you’ll be able to hear first-hand about the advantages and determine the overall value in terms of long-term cost reduction, revenue growth or improved customer experience.
Tech requires training
Throwing new technology at people and expecting them to simply figure it out is a fundamental error, and one that a surprising number of companies have made. Comprehensive training is simply not a negotiable outlay, and needs to be factored into the budget when you’re pricing up the cost of implementing any new systems. It doesn’t just make good business sense, by ensuring everyone can use all of the tools at their disposal as effectively and efficiently as possible, but also eradicates the stress and concern that may come with getting used to new technology, especially for the less digitally-savvy among the workforce.
Being able to communicate from the offset that the changes will be rolled out in conjunction with full training can also help people feel more welcoming of what’s to come. People don’t want to oppose change – it’s something we all do as an instinctive human reaction; so, give them plenty of reasons to feel comfortable, talk to them openly and honestly, and mean it when you say they will be properly supported throughout the process.
From exploratory play to enterprise scale
The success of a people-first adoption strategy, where teams are empowered to ‘play with it’ and uncover genuine benefits, must then be matched by a serious, enterprise-level plan for scaling those winning ideas. This is the crucial bridge between initial excitement and sustainable business value.
We’ve seen some enterprise organisations really embrace AI by allowing their teams to play with it, use their creativity and explore the possibilities. This exploratory approach is a fantastic way to go compared to the old method of dropping some tech in on a strict timeline, training people, and hoping for the best. The risk, however, is fragmentation, shadow IT, and security vulnerabilities.
To achieve genuine, strategic enterprise value, the transition from a grassroots proof-of-concept to production requires a serious, mature operating model based on three crucial pillars of AI maturity:
Firstly, establishing a Centre of Excellence – a centralised body required to vet use cases, manage technical standards, and prevent duplicated efforts across the organisation. The CoE ensures a focus on responsible AI practices from the outset and decides which initial experiments receive the resources needed to scale.
Secondly, define clear governance and ethics: the need for continuous monitoring and strict adherence to Responsible AI principles is non-negotiable. This must cover fairness, transparency, and accountability as systems scale up, specifically noting compliance with regulatory standards such as UK GDPR.
Lastly, measure tangible business impact: enterprises must move beyond novelty and rigorously quantify the value of scaled solutions to justify sustained, long-term investment and prove the value of the initial creative exploration.
The most successful modern enterprises embrace the synergistic integration of both creativity (allowing teams to play) and structure (implementing governance) to turn initial plans into sustainable competitive advantage.
Human v robot
Given they lack the stress hormones that cause humans to react defensively to change, the prospect of robots might seem appealing to some managers. But in reality, your people are what make your business so great. Their ideas, enthusiasm, creativity, and camaraderie make a fundamental difference to how well the company runs, which in turn boosts your bottom line.
So, let’s never allow technology to distract us from what change management specialists have been aware of all along, that everything we do must remain people-centred. The moment we lose focus on our people is the moment we lose any semblance of loyalty, motivation and hard work that we rely on in order to see our businesses thrive. No amount of automation can replace the unique qualities that make every person in our workforce the right fit for their job, and there’s no tool that’s yet been invented which is worth losing them as you make your way along the road to AI implementation.
