AI transformation is not a tool rollout
The frontier moves fast, but firms still need stability, trust and people who believe in the change.
Hi there,
I think it would be an understatement to say that the focus in the corporate world on doing an AI transformation or adopting AI has reached a fever pitch.
The idea that you can do things better, faster, and cheaper in your operating model and achieve your corporate goals through just adopting a new technology is quite an enticing prospect.
I fear that a lot of leaders have forgotten many of the lessons we’ve learned in the realm of change management. These lessons apply to an AI transformation just the same as they do to any other project or program of work.
Tailoring beats the default playbooks
AI transformation requires a tailored change approach. It needs to take into consideration how your business works. It also needs to consider how your people feel about change and all of the different characteristics of your culture. This means how you approach an AI rollout is going to be very different.
A cookie-cutter approach where we do a pilot, a proof of concept, then roll things out with the help of a big consulting firm or a business process outsourcing firm - it just isn’t going to work for many businesses. The default isn’t going to move the dial here.
A lot of smaller businesses and startups will find that because they don’t have the baggage of bureaucracy and process, they can move faster. This means there are a lot of risks they’re introducing. These require careful management and deliberate decision-making about where you strike the balance of human and AI in a new workflow.
Rebuild fast, protect trial-and-error
The pace of change is faster than it’s ever been before. Every few weeks, there’s something new that is worth exploring. We sanity check whether it could add value, or dismiss the latest tool as mere hype. The pace of this change is far beyond what most businesses are capable of dealing with properly, let alone implementing, doing all of the testing and controls, and getting it into production use.
This new normal presents enormous challenges. Leaders want to be able to demonstrate that they’re operating close to the frontier. Unless they’ve been operating their business in this way for the last decade, they need to entirely rebuild their operating model from the ground up. It’s not that they were too slow in the past, it’s that the speed of today dissolves the quarterly cadence of yesteryear into mist.
If they want to evolve in this direction, that presents enormous risk to any business. Being able to run business operations from a position of stability is critical. You can’t be constantly chopping and changing what tools you’re using and what workflows you’re doing. Clients won’t tolerate it, and your people will get very frustrated if they have to change how they do their work every five minutes.
Imposing top-down change is hard in this environment. A lot of the value is coming from bottom-up experimentation. Your best people are figuring out, through using the tools themselves, how to apply AI in new ways to do things better, faster, and cheaper. You need to listen to them, incorporate their new solutions, and reward them.
This entrepreneurial trial-and-error process is how we get all the cool things and innovations in our world today. Keeping that experimentation and openness to novelty is one of the most important cultural things that a company going into this AI era with eyes open is going to want to retain.
