A logistics company had rolled out AI-assisted route planning and warehouse allocation tools, but hadn’t changed a single job description — leaving 300 planners doing the same tasks the software now did, alongside the new tasks the software created.
Redesigning 300 Roles Around AI-Augmented Workflows
Service Provided
Capabilities Utilized
Job Design, Organizational Design, Change Management
Client challenge
Route planners were still manually double-checking routes the AI tool had already optimized, out of habit and a lack of trust, while newer tasks like reviewing AI-flagged exceptions and tuning allocation parameters had no clear owner. Productivity gains from the technology investment weren’t showing up because the organization around it hadn’t changed.
Our solution
We redesigned the planner role from the ground up around what the AI tool now handled well versus what still required human judgment, retiring the manual double-check step entirely and formally assigning exception review and parameter tuning as core responsibilities. New job descriptions, updated performance metrics, and a revised training curriculum followed directly from that redesign.
We ran the rollout with the planners themselves rather than to them — a working group of frontline planners co-designed the new role definitions, which meaningfully reduced the resistance that typically comes with AI-driven job changes.
Results
Planner productivity, measured in routes finalized per person per day, increased 34% within four months of the redesign, and voluntary attrition among planners — which had ticked up after the initial AI tool rollout — returned to its historical baseline. Internal surveys showed planner-reported trust in the AI tool’s route recommendations rose from 41% to 79% once double-checking was formally retired and replaced with targeted exception review.
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