Is Your Organization Messing Up AI Adoption? — Smashing Magazine

Paul is a leader in conversion rate optimisation and user experience design thinking. He has over 25 years experience working with clients such as Doctors … More about Paul ↬
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The way I see most organizations roll out AI feels more like a farce than a strategy. If it were turned into a movie, reviewers would say it was unbelievable. Nobody could be that stupid.
Yet here we are. And what makes it all the more frustrating is that we have been here before.
Back in 2014, I wrote a book for Smashing Magazine called Digital Adaptation, looking at the mistakes being made in how organizations were approaching digital transformation and what they should be doing instead. The similarities between then and now are striking.
So in this post, I want to look back at Digital Adaptation and see how the lessons in that book apply to the AI era and what we can learn from the past to help us navigate the challenges of AI today.
The biggest mistake, both then and now, is approaching each as a technological challenge.
Sure, both digital transformation and AI are technological advances, and yes, some level of technological implementation is required. But that is the tip of a very large iceberg.
Back in the midst of the digital transformation era, IT departments were rolling out CMSs, CRM systems, intranets, and so on. Meanwhile, on the customer-facing side, organizations were rolling out websites, apps, and personalization. But they were putting almost no emphasis on how people were going to use these systems.
Internal systems were hard to use, and customers either didn’t care what was being built or wanted something else entirely.
The same is happening with AI. Senior management are buying into the hype, and IT teams are rolling out Copilot Studio licenses company-wide and considering the job done. Sure, there is a bit of organization-wide generic training, but that’s about it.
Just like before, staff are left wondering what to do with these new systems and feeling under pressure to use them and deliver results.
After all, this time around, it is even worse, because this time, staff fear for their jobs. They have read the same headlines that you have, and no amount of promises from senior management is going to make them feel any better.
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I mean, think about it from a staff member’s point of view. AI offers them very little personally, even setting aside the fact that management may be intending to use it to replace them.
The main reason senior management are excited about AI is that it provides additional productivity. People can do more in less time. But that does not benefit staff. They are still required to work 9 to 5, but now they are expected to do more in the same time. They don’t get any time back, and they don’t get paid more, so why would they embrace AI?
One strategy is to help staff identify the parts of their job they hate and how AI can help them do those tasks more quickly and less painfully. People tend to be a lot more receptive to change when it is presented as an opportunity to improve their working lives.
But, that should just be the beginning. Organizations may need to consider providing incentives for staff to adopt AI in terms of career progression, compensation, or shorter working hours.
Also, adopting AI is not a simple task. It involves challenging every working practice they have built up over (in some cases) decades. All of that procedural knowledge has to be rebuilt. That is a lot to ask of anybody in even the best of circumstances, and most employees do not find themselves in the best of circumstances.
Most are overworked and struggling to stay on top of their to-do lists. They don’t have time to sit down, learn a new tool, and figure out how it fits into their workflow.
That doesn’t just take time. It also takes a lot of consideration and experimentation. It is not enough to just send a member of staff on a training course and expect them to be able to use AI to its full potential.
At a minimum, staff need training specific to their roles, such as the AI training I provide to UX teams. But organizations should be going even further.
They need to develop sophisticated training programs that help staff from different departments understand how to use AI in their specific roles. They need ongoing support and the time to experiment with AI to find the best ways to use it.
But formal training will only take you so far. In my experience, the most effective support comes from colleagues, which is why I would start with the enthusiasts rather than the resisters. Every organization has a handful of people who are already experimenting with AI, often without anybody asking them to. Bring those people together, give them the time and space to share what is working for them, and let their enthusiasm spread to everyone else.
I saw this work during the digital transformation era too. In Digital Adaptation, I described an internal conference where staff showed their colleagues what they had built, and it did more for adoption than any memo from the top ever could. People are far more likely to try something when they see a colleague in a similar role using it successfully than when they are told to by senior management.
Unfortunately, experimentation comes with a big downside… mistakes will be made.
Many organizations have, to be frank, a culture of fear where mistakes are seen as a sign of incompetence. However, by its very nature, learning a new tool like AI will involve making mistakes, and this can be a massive barrier to adoption.
I saw this during the era of digital transformation. Senior management would demand digital transformation and were confused when it didn’t happen.
What they didn’t realize was that they were