Invention, innovation, diffusion.
The three stages of AI progress according to a newish long read from
and in their regularly excellent Substack newsletter, .
We use invention to refer to the development of new AI methods—such as large language models—that improve AI’s capabilities to carry out various tasks. Innovation refers to the development of products and applications using AI that consumers and businesses can use. Adoption refers to the decision by an individual (or team or firm) to use a technology, whereas diffusion refers to the broader social process through which the level of adoption increases. For sufficiently disruptive technologies, diffusion might require changes to the structure of firms and organizations, as well as to social norms and laws.
, April 2025
I’m guessing that only a handful of readers of Data Runs Deep are working in the ‘invention’ stage of Generative AI.
But many will be working in and around organisations where ‘innovation’ and ‘diffusion’ - both early adoption and adaptation - is definitely a choice and in some industries, perhaps a necessity.
Encourage (but don’t mandate) uptake and experimentation
I’m not at all a fan of the recent flurry of CEO memos exhorting their teams to reach for AI as a default for every task.
There is something almost desperate in the tone of a number of the notes which makes me wonder how many hard driving executive teams with little understanding of either the technology or the cadence of research breakthroughs have overcommitted to efficiency savings on the promise of autonomous agents and workforces full of AI employees.
Productivity gains to date have been modest, in the few cases where people are actually striving to measure them.
My bet is that this reflects that we’re in the very beginning of diffusion. We have no idea yet what the equivalent of the factory floor transformation that finally enabled full adoption of the electric engine will be for Gen AI.
So, many organisations will benefit over the medium term from encouraging and rewarding active experimentation with new Gen AI based tools. What’s needed is a little more patience, and the willingness to invest in some tools and a fair bit of decent training. As my Kiwi/Aussie readers will appreciate, it won’t happen overnight but it will happen.
We need to embrace tinkering across the workforce, not drive people into active opposition of all things AI by forcing it down their throats.
I didn't realise this was a 'thing', Kendra. A really interesting read!
I think people took the wrong lesson from the Jeff Bezos API memo.