Key takeaway
AI initiatives succeed when organizations define the target operating model first and select tools second. Skipping straight to tooling is the most common cause of stalled AI programs.
Tool selection is the last decision in an AI strategy, not the first.
Why it matters
When a tool is chosen before the target workflow is defined, teams end up reshaping their work around the tool's defaults instead of the other way around. That produces adoption without impact.
What we're seeing
In our advisory work, the organizations that see measurable ROI are the ones that mapped their current-state workflow, identified where judgment and where repetition lived, and only then evaluated vendors against that map.
Practical recommendations
Document the workflow you want before you demo a single product. Separate decisions that require human judgment from ones that don't. Pilot with a narrow, well-defined process rather than a department-wide rollout.
Key takeaway
Strategy first, implementation second. Reverse the order and you're buying software, not building capability.
Paige Bradbury
Founder & Principal Consultant, The Bradbury Group
Instructional designer, AI consultant, and former CNN Radio correspondent helping leaders build AI-ready organizations.