Turning excitement into an actionable AI roadmap.

The challenge

Taymor had most of the ingredients for AI adoption across the organization. A 78-year track record in Canadian manufacturing. Strong executive sponsorship. Budget committed. A leadership team that understood AI mattered and wanted to move. They had already launched their first AI application, a Copilot agent providing access to organizational data, and had done foundational data work to get onto Databricks.

What they hadn't done was build the connective tissue across the organization: shared language across leadership, vetted opportunities grounded in how the business actually runs, and a sequenced plan that balanced near-term wins with the bigger bets. Without those pieces, enthusiasm risked becoming scattered pilots, vendor-led decisions, or a strategy that wouldn't survive contact with the operating business.

What changed

Over four months, we helped Taymor move from early momentum to a prioritized, defensible plan their leadership team owns and is executing against:

• Leadership aligned on a shared framework for AI. Seventeen leaders now operate from a common understanding of where AI creates value, what it takes to get there, and how Taymor's values shape the approach.
• A vetted inventory of business opportunities. Engagement across eight departments surfaced 53 documented pain points, each scored on value, effort, and risk. Leadership can now defend what's in and what's out.
• New strategic opportunities on the table. Discovery surfaced opportunities the team hadn't previously considered, now positioned for deeper exploration alongside the near-term work.
• Motion, not a document. The roadmap is built around pragmatic next steps that demonstrate near-term ROI while reducing risk for the larger opportunities, so the operational track actively informs the strategic one.

Why it worked

• Discovery before prescription. We went deep across the organization before recommending anything. The roadmap holds up under scrutiny because it's grounded in what people doing the work actually experience, not assumptions about where AI should go.
• Shared language at the leadership table. The workshop created a common frame for talking about AI across the exec team. Strategy conversations became faster and more productive when everyone worked from the same foundation.
• Collaboration that surfaced the best opportunities. The people closest to the work are the ones who see where value lives. By combining their perspective with ours, we identified opportunities neither side would have found alone, and built a plan the team is ready to execute because they helped shape it.