Know Thyself

What observing pickleball players taught me about ... AI adoption?

If you follow many athletes today, you likely encounter a lot of talk about the importance of supplements or mornings routines and recovery protocols with cold plunges, compression sleeves, and similar. Part of that is optimization of things based on a narrow set of priorities, like optimal physical performance around competition schedules. Part of it is also the underlying incentive via partnerships - sponsorships, affiliate links, etc. If you are not also an athlete in that area, you will probably dismiss a lot of it since you don’t aim to compete at that level. 

I get a similar impression about a lot of AI conversation. You see a lot of people working in the field that also share their stacks, markdown files to be fed into tools, workflows, etc. A lot of them work with AI and are also incentivized to promote products or services, though quite likely because of their businesses or employers. In addition, because of the overarching narrative around AI, you see a lot of additional participants in this who further advance the narrative simply because they don’t want to appear as “behind”, as there is a significant amount of FOMO. 

However, here, too, it may be worthwhile to assess if you really need to buy into everything that gets shared and promoted. While the delineation might not be as obvious as with elite athletes, for businesses it is also important to evaluate what advice or which tools apply to them and their situation. 

I recently had a conversation with a SMB leader who shared that they felt like SMBs do not need the best in class that is often advertised. They need something that fits their reality, in terms of business maturity and their customers’ needs and expectations. And this is something many more conversations should be grounded in.

Thus, we typically assess things like business maturity in various dimensions: operational maturity, CX maturity, or different frameworks. Within the context of the current discourse, it is important to also assess an AI maturity, but connecting it to an operational maturity. Without it, initiatives follow the same pattern that is so often commented on: haphazard pilots, or best practices that don’t connect to the operational constraints and reality of the business. 

If we don’t assess where a business is on a maturity scale, any prescription of frameworks to use or best practices to follow is likely misguided. You would not adopt an Olympian’s training and supplement routine if you are barely starting to play pickleball, either.