Companies that went hunting to be the first to adopt the next big thing in generative A.I. did so on the presumption that because it was so user-friendly it would also be easy to implement. That has turned out not to be the case.
Incorporating generative A.I. for strategic purposes, in even straightforward applications, has so far proven resource- and capability-intensive. Accounting for data security, company-specific functionality, and a miniscule global talent pool, has meant only the big players have been able to even attempt meaningful pilot programs beyond basic use cases (and those use cases don’t create substantial differentiation from the competition). That’s the exact opposite of the future the technology appeared to promise.
