"But here's a comforting yet uncomfortable truth about enterprise AI: Most of what's loud today won't persist tomorrow. While models trend like memes, frameworks spawn like rabbits, and at any given moment a new "this time it's different" pattern elbows yesterday's breakthrough into irrelevance, the reality is you don't need to chase every shiny AI object. You just need to master a handful of durable skills and decisions that compound over time."
"The most consequential AI decision is figuring out what problem you're trying to solve in the first place. This sounds obvious, yet most AI projects still begin with, "We should use agents!" instead of, "We need to cut case resolution times by 30%." Most AI failures trace back to unclear objectives, lack of data readiness (more on that below), and lack of evaluation."
Models and frameworks change rapidly, so chasing every new AI breakthrough is unnecessary. Durable enterprise AI requires mastering core skills and decisions that act as an operating system for AI work. Success begins by defining a concrete business problem and measurable KPIs rather than selecting technologies first. Translate goals into task specifications that list inputs, constraints, and success criteria. Prepare and vet data for readiness and design evaluation mechanisms to measure outcomes. Embed humans in the loop and build iterative evaluation into the design to ensure accuracy, compliance, and practical value over time.
Read at InfoWorld
Unable to calculate read time
Collection
[
|
...
]