Agentic AI should return attention, not just minutes

Pascal Bornet connects two very different Agentforce stories: agricultural guidance for farmers in Colombia and an operating system for a US healthcare practice. The useful common measure is not simply tasks automated. It is human attention returned to the moment where trust matters.

Bornet reports that Rare's pilot projected 40% more time for field teams while scaling guidance toward 100,000 farmers. He also reports that MIMIT Health sees roughly 40% more patients each day and cut pre-operative preparation from 90 minutes to 90 seconds. These are participant and sponsor-reported claims, not independently audited results in this share.

The framing is still worth carrying into enterprise AI reviews. “Hours saved” is incomplete unless the team can say where those hours went. Automation can shorten a workflow while increasing monitoring, exception triage or screen attention elsewhere.

I would add four outcome checks beside time saved:

• direct time with the customer, patient or field worker;
• quality of decisions and exceptions handled;
• after-hours recovery and supervision load;
• whether the person can stay present instead of managing the automation.

That last measure is easy to miss. A physician who finishes documentation faster but spends the consultation watching an agent has not necessarily regained attention. A field team that serves more farmers but inherits an opaque exception queue may have moved the burden rather than removed it.

The article's best line of thought is that AI creates value when it removes the work that was removing people from the moment. Read it for that test, then make the destination of saved time visible in your own operating metrics.

Do not stop at minutes saved; account for the human attention the system actually returned.