How AI is Reshaping R&D
As technology has advanced—and technology use cases have become even more diverse—so there has been a significant increase in the use of research and development (R&D) projects. These are the initiatives that aren’t necessarily expected to generate internal or customer-facing solutions, but that explore the boundaries of what is possible in order to inform more mainstream solution development later on.
One of my earliest exposures to this type of work was when I was working for an investment company in the early 2000s. It had a team looking at developing investment software for the then-latest generation of gaming consoles. (It sounds silly now, but only because smartphones exploded a few years later.)
Now, AI is dominating these exploratory R&D initiatives. That’s no surprise, but I think that there needs to be a bit of a shift in how these projects are handled. I have always viewed R&D work as starting with the question, “Can we do this?” That may lead to the determination that it can be done, or (more likely) that a slightly modified “something” can be done.
That in turn leads to continued R&D around the question of “What would be the best way to do this?” That serves to provide more of a framework and define the parameters of the more formal project that will turn the concept into a
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