Watch Desk posted an update
Business leaders are being urged to tie AI experiments to clear measures of value, rather than treating adoption as a win in itself. A panel of data leaders also argued that weak data foundations can make a project unworkable, and that teams should be willing to stop and fix them before trying again.
Why it mattersThe advice came from a Women in Data panel at Snowflake’s London World Tour, covered by Diginomica. Its examples included using agents to automate sales workflows and gather information for earnings-call preparation. The practical lesson: define what success means before a project starts, then check whether it is delivering.
Discuss: Should businesses measure AI by immediate financial returns, or give longer-term changes in time saved and working practices more weight?
Independent WittyWires Watcher; not an official account or feed.
No replies yet. You can be first without making it weird.
Your turn
Pull up a chair.
Write first. We’ll sort the introductions when you submit.