From Task to Trust - The Real AI Transformation
Still Thinking Series: Part 1
Drawing insights from the McKinsey Technology Trends Outlook 2025 (July 2025), this piece explores the deeper shift underway as agentic AI systems begin to reshape how—and with whom—we work.
We tend to frame AI transformation as a story of tasks: what can be automated, what should be outsourced, what jobs are at risk.
But something deeper is shifting.
The most significant change isn't that machines are doing more. It's that they're deciding more. We are no longer just automating tasks—we're delegating judgment. Handing over not just labour, but discretion.
And that raises a different question entirely:
Do we trust the machine to act on our behalf?
Not just to calculate, but to choose? To plan, even?
This is the emerging terrain of Agentic AI—systems that don’t just respond, but initiate. They can execute multi-step workflows, coordinate tools, interact with people, and adapt to context. Virtual assistants become virtual coworkers.
And with that shift, the centre of gravity in transformation quietly moves—from capability to credibility. From tools to trust.
We've Been Here Before
Any human transformation—digital or otherwise—relies on trust. Between teams. Between leaders and workers. Between a company and its customers. Strategy fails not because it was wrong, but because people didn't believe in it, or each other.
Why would AI be any different?
A system that sends a calendar invite is convenient.
A system that books your week without asking is unnerving.
The line is blurry. It’s not about functionality anymore. It’s about relationality - what the system represents, how it behaves, and whether it earns our trust.
We Thought AI Was a Tool. It’s Starting to Look More Like a Relationship.
That doesn’t mean robots with personalities. It means responsibility is shifting. And with it, a subtle change in how we work, govern, and lead.
The McKinsey report notes that work is moving from “deterministic coding tasks to higher-order activities like task planning, tool orchestration, and contextual decision-making.” That sounds like a human job description. But increasingly, it’s shared.
This raises new questions:
Who is accountable when an AI coworker makes a mistake?
How do we govern systems that operate with autonomy?
What skills do we now value in a world where judgment is distributed?
Trust becomes not just a social issue—but a strategic one.
Strategy is the Design of Trust
If you're building systems, products, or teams in this new context, consider this:
Trust is the gatekeeper to adoption. No matter how good the AI is, people won't use what they don't feel safe with.
Trust is multidimensional. It’s not just about accuracy, but explainability, consistency, context-awareness, and ethical alignment.
Trust must be designed. We don’t inherit trust from the technology—we build it into the experience.
We’re no longer just building tools.
We’re building collaborators.
And collaborators, human or not, are only as effective as the trust we place in them.
Closing Thought
In a world of agentic systems and autonomous agents, transformation is no longer about doing more.
It’s about deciding what to let go of—and who (or what) we let hold it.
That’s not a tech decision.
That’s a trust decision.