AI Product Leadership

Turn AI plans into products teams can own and ship.

I help enterprise teams clear up ownership, intake, adoption, platform choices, and how progress gets measured.

$15M+
Portfolio leadership

Portfolio planning across digital commerce and platform work.

40+
Practice scale

Product practitioners supported through practice, coaching, and portfolio leadership.

17%
Commerce lift

Checkout conversion lift tied to unified commerce platform work.

50%
AI-native discovery

Faster initial engagement, triage, and discovery through AI-native workflow.

Where I can help

Three places where AI product work usually needs a firmer hand.

AI product strategy

Turn loose AI plans into product bets with ownership, intake, adoption, and proof.

Product operations

Clarify how work enters the system, how choices get made, and how teams learn.

Platform product

Connect platform choices to developer experience, product adoption, and shipped outcomes.

Selected outcomes

Proof that strategy connected to operating moves and shipped work.

Read the selected outcomes

How I work

From AI ambition to a shipped product system.

Tools do not make AI shippable. Teams need ownership, governance, adoption, measurement, and delivery to work together.

AI ambition to shipped product system
  1. 01
    AI ambition

    Executive intent, market pressure, and experiments need a product frame.

  2. 02
    Platform ownership

    Clarify what becomes governed capability, what remains exploration, and who owns adoption.

  3. 03
    Operating rhythm

    Connect intake, discovery, roadmap, funding, delivery, launch, and learning.

  4. 04
    Adoption paths

    Help product and engineering teams know where AI belongs in real workflows.

  5. 05
    Measurement

    Tie adoption to product accountability, developer experience, and shipped outcomes.

Ask Brian

Ask about fit, AI product strategy, product operations, or what to read first.