Change is inevitable - Growth is optional.
Making AI work means change. Context, culture and legacy will make that hard and painful. You may as well unleash your curiosity and have fun along the way.
“There are no AI-shaped holes lying around” ->
this is how I reconcile the facts that (a) AI is already powerful and (b) it’s having relatively little impact so far Making AI work today requires ripping up workflows and rebuilding for AI.
This is hard and painful to do…
Perhaps the dumbest analogy I have heard this year came from Mark Logan at a techscaler event. He compared building businesses to sending a man to Jupiter. Jupiter is difficult because it requires advances in complicated physics. Whereas he thought building successful businesses would be easy because we already know the formula.
Nothing could be further from the truth. Businesses are complex organisms made up of incredible, adaptable, unpredictable people. All customers, suppliers and stakeholders are made of people too.
Multi-dimensional people problems are unsolvable. You need to move people forward, not remake them.
Matt is spot on. This stuff is hard.
The hard things about change
It’s hard for two reasons. One is essentially captured in Clayton Christensen’s famous “Innovator’s Dilemma". Shifting your product or business model to take advantage of new ideas is difficult because you are putting your existing business at risk. So AI creates opportunities but, for example:
It's hard for a professional services firm to become a software business.
It's hard for a school to stop relying on homework and exams.
Yet both these things may happen. More likely from startup disruption than by incumbents reinventing themselves.
I think of this as the positive side! The negative view is that there are an infinite number of blockers and resistors that prevent change happening. Even when that change is simply adopting some new technology to make life easier or at least to reduce the cost base.
Context, culture and legacy
Most AI projects are sitting in this second category right now. Hence Matt’s observation is very relevant. Here’s there reasons why this is so tough:
Context. Every business is different. It has its own character, history, circumstances and challenges. Change must fit the specific context.
Culture. Related but different. Businesses are made of people. People have their own customs, incentives, status rules and habits. Change changes culture but not in easily predictable ways.
Legacy and the data question. There are no analogue organisations any more. Every business has a legacy of systems and especially data. A lot of vital information is buried in those silos. No-one wants to give you that data and nothing is connected together - this is a great explanation of why from Sarah Constantin.
Moving fast and slow
I liked this quote from Sarah about how data regulates the pace of change: “it happens at the speed of human negotiation and learning.”
I see a lot of bullshit about the “unprecedented” pace of change. Change is hard and it requires patience. AI is not different. Change will take time.
But it will be worth the effort. Change is tough but it's how we make the world a better place. Don’t be put off by the barriers, be curious and have fun along the way.
Take positive steps now. Here are some suggestions:
Get out ahead of this - learn about AI and try some new things.
Micro implementations not sandboxes or experiments. Some hurdles but not hard boundaries. Let your people use the things that make their lives easier. Let the good stuff spread.
Be driven by curiosity and optimism, not ROI or numbers.
Look for interconnected ideas - not how do I use AI but How might AI work with X - X does not need to be tech or digital at all.
Doing the next right thing
Change is tough but it's how we make the world a better place. Don’t be put off by the barriers, this is going to be fun.
How will AI change your business? When will that happen? What can you do now to prepare for the changes ahead? How do you sort your data legacy? If you are interested in exploring these questions, I would love to help. Please get in touch.
Thanks for reading.