Stories about accelerating technological change can create urgency to adopt the latest tool. They do not identify which tool will improve your business or which process is ready to change. A concrete task provides a better starting point.
Choose a recurring problem
Find work with a clear input, an observable result and enough repetition to evaluate. Drafting a summary for review may be a better first experiment than handing over a broad responsibility with unclear limits.
Record how the work is currently done, how long it takes and what good output looks like. Without that baseline, novelty can be mistaken for improvement.
Run a bounded comparison
Use representative examples and include difficult cases. Compare the AI-assisted workflow with the current approach on quality, time, cost and review effort. Note where the tool changes the kind of work rather than simply reducing it.
Keep an ordinary fallback available while the new process is being assessed.
Invest in understanding
Learn how the tool handles data, what actions it can take and how failures appear. The team needs enough knowledge to use it responsibly and recognise when the result is unreliable.
Review the decision
Keep, revise or stop the trial based on the evidence. A useful tool may deserve broader use; an impressive demonstration may not. Technology history offers perspective, but your adoption decision needs a current problem, a credible evaluation and someone responsible for the outcome.