McKinsey’s list of best practices and cross-reference to large vs. smaller businesses adopting them. These jive with what I’m seeing as well, but what’s missing?

If an executive asked me, “what is the difference between success and failure”? The answer I’d give them is, “alignment between strategic growth plan and technology’s possibilities with a willingness to experiment to get there”. For sure, Gen AI has a part to play, as it is an enabling technology like electricity, the internet, and the industrial revolution. The hard part is not just boiling that technology down into “use cases” but instead looking hard at the nature of the business and how we can achieve something greater.



We know that applying AI to the business is critical and sitting still is not an option. The misstep is to chase the technology (which is somewhat reflected above) and instead of chasing business impact.



Does every effort need to be “big”? Absolutely not. I’ve unfortunately seen some companies miss out on employee-impacting AI capabilities because they incorrectly saw the incremental impact as too small. That said, without clear focus we’ll potentially adopt some AI, have mediocre results, and then say, “well… AI was a bust”. The limiter is our imagination, not likely the technology in the long-run. Think about where the business should be in three years… your employees, your customers, your partners, your opportunity… understand that AI has a dramatic impact on that… then paint the picture of the stepping stones to get there. Understand that there will be experiments that cause the adjustment of that strategy along the way and prepare yourself to invest in multiple paths for the sake of learning.