There's a long-term problem with the consultant-client relationship, and I'm seeing it play out with AI rollouts in a big way.
Businesses deploy shiny new tools, bring in consultants, and tell employees to crack on. Six months later, leaders are scratching their heads, wondering why adoption is flat and returns are non-existent. Meanwhile, the consultants who should've been accountable are already three deals down the road.
The last part is key to the fix. Instead of delivering the tool and heading for the door, consultants need to stick around long enough to properly embed the tech. That way, they can guide employees and troubleshoot in person, in real time, until adoption sticks.
This can bridge the gap between AI implementation and effective use – enabling businesses to finally reap the benefits.
Why usage, not tools, drives AI returns
The link between effective use and ROI is clear. New data from Ramp and Revelio Labs found companies achieving the greatest AI gains understand something important: tools only move the dial when the workforce understands how to use them effectively.
That might sound obvious, but most businesses and consultants are getting this wrong. They treat implementation as the end goal rather than the starting gun and fail to realize the part that comes next – getting people to change how they work – is just as important.
Businesses focus on the tech and skip over training their employees how to use it. Fewer than 23% of workers receive employer-led AI training, and even those who do get just five hours on average. That might cover the basics, but it'll never build the confidence needed to really drive value with AI. And left to their own devices, most employees quickly ditch the tools and revert to old habits.
Putting a consultant in the room
Lasting AI adoption requires someone in the room available for ongoing technical and skills support. That's core to our delivery model at TSCi. We embed our people within the client's business for the duration of the contract, meaning someone is physically sat in the client's office, showing employees how to incorporate the tech we implement.
When someone in operations doesn't trust an output, they can walk over and get a second opinion. When a workflow needs shifting, we can tackle it proactively rather than catching the issue next quarter. This approach gives employees the confidence to radically shift the way they work with AI.
And once adoption soars, so will ROI. Employees produce better work more efficiently, and the consultant ensures those gains move specific operational and financial KPIs. Businesses will quickly realize the problem with their AI transformation was always in the usage, not the tech.
New tools won't fix a business on their own. People using them well, with someone accountable standing next to them, just might.
What consultancies and leaders should change
In my opinion, any consultancy still billing for implementation and disappearing afterwards is optimizing for their own delivery rather than the client's outcomes. To sell execution and accountability rather than hype, firms must now redesign their consulting engagements accordingly.
And for enterprise leaders sizing up AI spend for next year, the question to ask isn't which model, which platform, or which brand-name firm to go for. It's who will still be at your desk in month nine, accountable for helping you realize the benefits you were promised.
That's what I mean when I talk about ownership. A named person who stays until the outcome is real and whose reputation is on the line if it isn't. That's a core value that my father instilled in our business and one that will always be felt by our clients.
New tools won't fix a business on their own. People using them well, with someone accountable standing next to them, just might.
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