As I work on a new trend report, this one titled Future of HumAIn Work, I am researching, thinking and synthesising as I go. To help me and publicise this ongoing work, I’m writing posts and also creating videos. This post contains some thoughts about the factors that impact AI technology adoption.

I think a core aspect of the Future of HumAIn Work will be how we adopt the technologies whilst the technology shapes us. Without further ado, let me dive into each of the 3 main elements that I think play into this.

Systems

I like to think of systems because process (the alternative) is not all encompassing enough. Processes are just one part of systems and do not consider the important component of technology that these days form an integral part of systems.

James Clear is widely known as the New York Times bestselling author of Atomic Habits which has sold nearly 20 million copies in five years since publication. A now well quoted statement from the book struck me:

You do not rise to the level of your goals, you fall to the level of your systems.

James Clear

I couldn’t agree more. Systems are often what get you there and I think this is especially the case with technology adoption and will be critical with AI. But, and this is a big BUT, only if they are the right systems.

What makes a system right? For one (and there will be many more I won’t go into here), they should be simple.

Keep complexity out of the system and with people who can handle and deal with it better. Don’t let complex systems interfere with people’s decision making and the smooth completion of their activities.

With simple systems and technology that supports the simplest means to getting processes and tasks done, with a way to collaborate simply around them, you are already winning.

When designing systems (including frameworks that govern them), if the system gets in the way because it’s not clear, you’ve already failed. Keep this in mind.

As an example, I’ve created a system for adoption that borrows from some of the best: Lean startup methodology applied to successful enterprise technology adoption.

I also think use cases are important and have captured thoughts on that here: Enterprise technology adoption – Use cases are the currency of success.

Last but not least, I have written about people collaboration and community-oriented software supporting technology adoption here: Microsoft Viva supporting adoption of M365 Copilot.

Culture

Culture is amorphous and hard to measure and shape. It doesn’t mean it’s not important and as Peter Drucker famously said, culture eats strategy for breakfast.

I’m not entirely convinced of that anymore. For one, as the author of this post believes, process can eat culture for lunch: 7 Strategies to Get Your Employees On Board with GenAI (hbr.org).

Coming back to my earlier point on systems, if you can have good processes and supporting technology in place, you can override culture or counteract the effects of culture that is not conducive to where you want to go, and which is hard to change.

I’m a big believer that software shapes culture, especially with social components that often go with enterprise software. I come back to the point I made under systems, about social collaboration functions that operate alongside work processes and how you get work done.

Still, it’s risky to ignore culture’s role and focus just on the technology or system. And this can be especially the case when AI is in the mix. From Corporate Ozempic: Avoid The AI Side Effects (forbes.com):

The first is the flattening of workplace culture. An organisation’s culture is its force-multiplier for progress. Many scientific studies have empirically demonstrated that strong cultures result in teams that are more determined, more entrepreneurial, and more resilient. If machines increasingly replace our colleagues, we will also lose the cognitive diversity that improves the way people create and invest the discretionary effort needed to beat the competition. Ultimately, when AI is used to diminish the human factor of organizational life, then so too will the grit and drive needed to push organizations forward.

I think we always have to take people into consideration and people shape culture depending on how we and technology shape them.

Strategy

Talking further of risks, especially when it comes to AI adoption, the biggest is not having a good strategy.

And the first thing to say: A plan is not a strategy and too many make the mistake of confusing the two. The best person to explain this is Roger Martin in the video below which will take 9.32 minutes of time well worth spending.

How are you truly going to leverage technology to drive business impact, growth and performance?

That is what you need a strategy for. Not a plan or list of actions, but as Roger Martin said, an integrative set of choices that positions you on a playing field of your choice in a way that you win.

Technology and AI in particular is just an enabler.

What you have to think about is how you are going to leverage it for competitive advantage. How you are going to insert it into your business model to make it spark and bring new life to your business. Reinvent your business and change business outcomes.

First and foremost, you need a clear strategy for your business, only then can you insert enablers into it like AI technology to accelerate it.

Then it needs to be articulated in a way that everyone who needs to execute on it, understands it. And you can plan for how execution can be guided with use of systems and culture changes.