Bob Morse, co-founder of Strattam Capital, highlights how companies achieve transformational AI productivity gains by redesigning teams and workflows around AI, rather than merely layering technology onto existing structures.
- AI-sprinkled workflows provide limited 10-30% productivity lifts
- AI-native transformations require CEO and board-driven organizational redesign
- HireRoad cut a legacy rewrite from 18 months to 15 weeks using AI-native model
What happened
HireRoad, a portfolio company owned by Strattam Capital, faced a daunting legacy code rewrite that was originally planned over 18 months with a sizable increase in engineering staff. When Jeff Fernandez became CEO, he proposed a radical shift: redesign team roles and daily workflows to embed AI tools at their core rather than merely using AI as an add-on.
This AI-native approach enabled the company to complete the rebuild in just 15 weeks—well ahead of schedule—while migrating customers to the new platform within the same year. Surprisingly, this was accomplished with a smaller team than initially planned, freeing resources to pursue other product initiatives.
Why it matters
The experience underscores a critical lesson that mere AI adoption falls short of its promise: productivity gains plateau around 30% when organizations simply add AI tools to existing ways of working. To unlock transformative gains—measured in multiples rather than percentages—companies must fundamentally rethink how their teams and workflows operate around AI.
This shift from an 'AI-sprinkled' to an 'AI-native' mindset means embracing new roles, more delegation of tasks to AI, and rapid iterative learning cycles. It requires strong leadership intent and active involvement from CEOs and boards to drive the necessary organizational change.
What to watch next
Private equity firms and traditional enterprises will increasingly face the dilemma of remodeling established organizations to become AI-native. Observing how portfolio companies track their productivity gains after such reorganizations will offer insights into best practices for AI-driven transformation.
Startups that launched post-AI revolution have an advantage by building AI-native operations from the ground up. Established companies must overcome legacy constraints, which will require bold leadership and a willingness to redesign job functions and team structures. The coming years will reveal whether this approach delivers on AI's full potential across industries.