Designing the Agentic Future for Super-Users
But when you talk to the people actually using today’s B2B tools, the story changes. The reality does not live up to the promise.
Let’s unpack the disconnect between hype and adoption.
Where Agentic AI Breaks Down
When you look at most so-called agents today, a few patterns keep showing up:
- Most agents are really workflows dressed up with AI, not systems that can adapt on their own.
- Too many surface answers without context or evidence, asking experts to make critical calls on faith.
- Many automations don’t match how domain experts actually work, so processes get bypassed the moment pressure is on.
No wonder adoption stalls. Gartner expects 40 percent of agentic AI projects to be cancelled within two years because of cost, poor ROI, and complexity. Only 19 percent of organizations have made significant investments so far, while almost a third are holding back. Leaders keep saying the same thing: they do not trust the systems.
And it is super-users — the people who live in these tools every day — who decide whether they get adopted or abandoned.
This is not resistance to change. Agents fail not because they are inaccurate, but because the experience does not feel agentic.
Agentic ≠ Autonomous
One of the biggest misconceptions I see is people equating “agentic” with “autonomous.”
Adoption in B2B does not hinge on an agent taking over. It hinges on an agent that amplifies human judgment.
Autonomy without explainability undermines credibility. A tool that overrides expertise will never survive, no matter how advanced the model. In pharma, the stakes are even higher. Regulations demand full auditability and traceability. If super-users cannot defend an output, they will not use it.
The best agents I have seen do not displace expertise. They make experts feel more competent and more confident.
The Behavioral Adoption Curve
When you watch adoption up close, you realize it is not binary. It follows a curve:
The Mythical Adoption Curve
How adoption is often imagined:
The Real Adoption Curve
How adoption actually plays out:
Most organizations design for the mythical curve. In reality, the real leverage is in the middle stages that everyone tends to skip.
Super-users move from tentative trust to habitual use when three things are present:
- Confidence cues that outputs are reliable.
- Explanations that preserve autonomy.
- Feedback loops that let them shape the tool.
Too few teams design for these conditions, which is why so many promising pilots stall.
Principles for Agentic UX
When you zoom in on the experience itself, a few behavioral principles stand out. These are the conditions that decide whether super-users trust and adopt:
- Defendable outputs. Show reasoning users can stand behind if questioned by colleagues, clients, or regulators. Without this, people avoid using the tool in moments that matter most.
- Credibility framing. Present recommendations in ways that support expertise rather than undermine it. If the system makes experts feel second-guessed, they will work around it.
- Confidence cues. Provide signals that outputs are reliable under pressure, not just plausible in a demo. Trust grows when users see evidence that the tool holds up in real conditions.
- Clear fallibility. Make uncertainty and human handoffs explicit. The fastest way to lose trust is when a system pretends to be certain when it isn’t.
- Recognition loops. Reinforce early adopters by making their use visible and valued. When super-users feel recognized as champions, they pull the rest of the organization along with them.
The best part is these do not require ripping apart the tech stack. They can be layered onto existing systems without major rework.
Experience Is the Differentiator
Agentic AI will shape the next decade of B2B. But the winners will not be the ones with the flashiest models. They will be the ones who design experiences super-users trust, adopt, and advocate for.
Because in the end, the challenge of agentic AI is not just technical. It is human.
At Cloudberry, we help teams bridge the gap between smart technology and human trust. If you’re building agentic experiences or facing adoption challenges, let’s chat.