From AI Adoption to AI Transformation
Redesign workflows and empower employees to lead AI adoption
E5 | Expand
what it means Translate individual experiments into team- and function-level transformation. Expand is where the organization moves from scattered AI usage to intentional workflow redesign. This means identifying where AI integration creates the most organizational value and systematically building it in.
What it looks like in practice: Structure workflow mapping sessions that bring experienced workers into the redesign process as contributors. Document what’s working, scale it deliberately, and connect AI fluency to career development rather than treating it as a performance compliance issue.
The organizational principle: High-performing AI organizations are nearly three times more likely than other organizations to have fundamentally redesigned individual workflows. Intentional workflow redesign has one of the strongest measurable contributions to AI business impact of all factors studied.
E6 | Empower
What It Means Give experienced workers protected time and a structured prompt to do something most organizations skip entirely: sit down and ask themselves which of their workflows still make sense, and redesign their relationship with AI on their own terms. This is the stage where the organization stops doing AI to its workforce and starts doing AI with them.
What it looks like in practice: Provide dedicated, uninterrupted time (not squeezed between meetings and deliverables) for employees to use the workflow audit tool in the companion activation document. A manager check-in afterward should treat the worker’s insights as organizational intelligence, not a homework assignment. Recognize experienced workers who share what they’ve discovered then empower them to guide and encourage their peers.
The organizational principle: Workers who guide AI outputs rather than simply receiving them see significant productivity gains. This is substantially more than those in full-automation models. The Empower step creates the conditions for experienced workers to stay in the driver’s seat, which is where their judgment is most valuable and where AI is most effective.
PUT IT INTO PRACTICE
Days 61–90 | Expand and Empower
Theme: Move from individual experiments to workflow transformation on the worker's own terms.
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Begin formal workflow redesign conversations
Bring ambassadors and experienced workers into structured sessions to map their current workflows and identify AI integration points. This is not an IT initiative. It is a talent and change management exercise, and it requires the people who actually do the work. PwC reported productivity gains of 20–50% in functions that redesigned workflows around AI, not those that simply added tools to existing processes. [01] Experienced workers, who know their workflows in depth, are your most valuable contributors to this redesign work.
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Give experienced workers protected time for their own workflow audit
This is the Empower step in practice, and it is the one most organizations skip. Schedule dedicated, uninterrupted time for experienced employees to work through the Workflow Audit in the companion activation document. Not as homework. Not squeezed between meetings. As a recognized, valued activity with a manager check-in afterward. Research on job crafting and worker-centered design shows that when employees’ own expertise shapes how new technologies get deployed, organizations achieve more sustainable productivity gains than when adoption is mandated from the top down. [02] [03]
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Design for augmentation, not replacement
The most productive AI implementations position experienced workers as guides who apply judgment to AI outputs, not as processors who rubber-stamp them. That takes training. Employees receiving over 81 hours of annual AI training report an average productivity gain of 14 hours per week—well above the median of eight hours. [04] This distinction—augmentation versus automation—is the design choice that keeps experienced workers engaged, valued, and central to the organization’s AI capability.
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Recognize and share early wins publicly
Specifically celebrate experienced workers who have made AI work for them. Name them. Share what they discovered. This counters the tech-phobia stereotype in real time, gives peers permission to try, and signals organizational values clearly. BCG’s 2025 AI at Work survey found that at high-performing organizations, employees are significantly more likely to say their leaders actively support them, and that this visible support, more than tool access, drives adoption depth. [05]
30-Day Success Signals -
At least one function or team has a documented, AI-integrated workflow redesign underway, with experienced workers represented as contributors.
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The companion activation tool has been used at least once in a structured, supported context.
- [01] Inc., "AI Success Requires Intentional Redesign of Workflows," February 2026
- [02] Frontiers in Psychology, "When Digital-AI Transformation Sparks Adaptation: Job Crafting and AI Knowledge in Job Insecurity Contexts," August 2025
- [03] Microsoft New Future of Work Report, 2025
- [04] EY Work Reimagined Survey, 2025
- [05] BCG, "AI at Work 2025: Momentum Builds, But Gaps Remain," July 2025