15. October 2025 By Annette Kauppinen and Ville Vuorio
From Assistant to Collaborator - How AI Is Changing the Craft of Coding Part 4
Blog 4 of 6 — Preparing the Team: Building AI Readiness Across Roles
AI coding agents are powerful—but only if people know how to use them.
As a consultant working with various client development teams, Ville Vuorio, Technical Architect at adesso Finland, has seen one thing clearly: the biggest barrier to getting value from AI isn’t technical—it’s human.
“Some developers embrace it immediately. Others aren’t sure what to make of it,” Ville explains. “It’s not about skill—it’s about trust, understanding, and habits.”
That’s where many organizations get it wrong. They introduce AI tools and expect instant results, but forget to support their people through the transition. No matter how smart the agent is, it won’t deliver value if the team doesn’t know how to work with it.
AI literacy isn’t optional anymore
Ville has worked with developers of all experience levels across multiple industries. The common pattern? The need for AI literacy—understanding what agents can and can’t do, how to guide them, and when to double-check their output.
Especially with junior developers, Ville notes a tendency to overtrust. “They sometimes assume the AI is always right. But you still need to think critically, test the results, and be ready to adjust.”
This applies across roles. QA engineers might hesitate to delegate test case generation. Product managers may not grasp how to prompt the agent for specification drafts. Even experienced devs might be unsure how to use AI during high-pressure delivery cycles.
That’s why Ville recommends role-specific onboarding, hands-on demos, and a safe space to experiment.
“When people see the tool perform inside their own workflow, the hesitation turns into curiosity,” he says.
Don’t just onboard the tool—onboard the people
AI agents, like new team members, need context to perform well. But the rest of the team also needs support in learning how to collaborate with them.
In client projects, Ville helps organizations introduce agents gradually. That might mean:
- Creating internal guides that explain how AI supports each role
- Sharing use cases from the organization’s own projects
- Hosting team demos and “AI pairing sessions”
- Encouraging experimentation in sandbox environments
The goal isn’t perfection—it’s familiarity.
“When people are free to try without fear, they gain confidence. That’s when adoption begins,” Ville notes.
Resistance is normal. Curiosity is the goal.
In almost every project, Ville sees initial skepticism—especially from experienced developers. And that’s natural. AI doesn’t just introduce a tool. It introduces a new way of thinking about development work.
“It’s not just about writing code faster. It’s about how the team works together, how decisions are made, and what skills are valuable,” Ville says.
The key is to frame AI as a collaborator, not a threat. It's there to handle the repetitive tasks, support decision-making, and free up developers to focus on meaningful, complex work.
Team leads and tech decision-makers play a vital role. By encouraging experimentation, admitting uncertainty, and creating room for feedback, they help create a culture where AI is a teammate—not an imposition.
AI adoption is not a rollout—it’s a culture shift
Bringing AI into software development is about much more than installing a plugin or giving access to a dashboard. It’s about building a shared understanding of how human and machine intelligence work together.
Ville puts it clearly:
“The earlier you prepare your people—not just technically, but culturally—the faster you start seeing real results. Not just in delivery, but in confidence, ownership, and momentum.”
Next in the series:
In Blog 5, we’ll dive deeper into how to tailor AI agents to your team’s exact needs—connecting them with your stack, shaping their behavior, and turning them from general assistants into specialized collaborators.
