Oracle implemented AI for its development teams. The good news is that its development teams are providing changes faster with AI than without. The bad news is that Oracle is not delivering updates to customers faster.
The road to AI for Oracle had some problems. While employees adopted the new tools, Oracle didn't initially share the cost of the tools, which meant that, to employees, each tool was equally "free" -- that is, costless. Once the bills arrived (and worked their way through Oracle's accounts payable system) managers saw the true cost of AI and decided to change their strategy. Now the cost is available to employees, and they can pick the AI engine (Clause, GPT, etc.) and consider the cost.
The bigger lesson for Oracle (and all of us) is that improving efficiency in one part of a system does not necessarily improve overall efficiency. AI helped Oracle's developers, and those developers made changes faster than before. But AI also helped the testing teams, and those testing teams found more problems -- and faster -- than before.
The net effect is that Oracle is running faster but delivering at the same rate. That's a particular problem for Oracle, as their revenues are not as high as desired. Its stock price is declining, and shareholders are collecting pitchforks and torches.
Back in the "good old days" we had a saying: "A fool with a tool is still a fool." That saying still holds. We in the development community are learning how to use AI to be effective. AI is easy to use to be active, but effective is elusive. The latter requires judgement, and good judgement comes from experience.
The journey to effective use of AI will be a long one, filled with mistakes. A complicating factor is the rapid change of AI and the frequent release of new AI engines. The rules for one version of GPT may not hold or be efficient for a later version. New versions and new rules for effective use make it hard to learn them.
No comments:
Post a Comment