Four-time SaaS CPO · available for advisory

I turn AI ambition into
products that ship.

Four-time Chief Product Officer. AI SaaS product leader. I help SaaS and enterprise leadership teams move from scattered AI experiments to focused roadmaps, operating models, and measurable execution.

CPO
5+Industries
20+Years in product
Core expertise

Strategy, product leadership, and AI transformation.

The three disciplines I bring to every engagement — from executive advisory to hands-on implementation.

01 · Strategy

AI strategy

Prioritize the use cases, governance, and implementation paths that turn AI from experiment into operating advantage.

02 · Leadership

Product leadership

CPO-level clarity for roadmaps, discovery, team design, metrics, and product-led transformation at scale.

03 · Execution

Transformation execution

Modernize legacy workflows and software delivery using practical operating models and AI-assisted execution.

Under his leadership everything turned around. The entire platform was redesigned and rebuilt to live in the cloud using modern technologies… making it best-in-class in the industry. User engagement increased dramatically, and so did sales.

David Fischkes, P.E.
Senior Software Engineer

I have rarely met a Product leader more aware of the value of customer experience and customer support as Kevin is. His openness to include Support in the conversation around Product was refreshing and inspiring.

Simone Secci
CX & Support Ops Consultant
Who is Kevin Owens?

Executive operator with hands-on AI transformation focus.

I’m a four-time Chief Product Officer with deep expertise in AI product strategy, operating model design, and transformation execution. I help mid-market and enterprise leaders move from AI ambition to measurable business outcomes.

My work spans executive advisory at ProductExec and AI implementation delivery at Enterprise AI Studio. Together they cover the full arc from strategy to production systems.

More about Kevin →

Kevin Owens, four-time Chief Product Officer Four-time CPO · London
How I think

From ambiguity to architecture.

Every engagement starts with the same discipline: understand the system before prescribing a fix.

kevin@strategy ~ %
Where the work lives

Three paths, one practice.

Whether you need to decide what to build, someone to build it, or a place to start small — the path runs through these practices.

Advisory

ProductExec

For leaders who need to turn AI pressure into product strategy, operating model decisions, and an executable roadmap before teams commit delivery capacity.

Visit ProductExec →
Implementation

Enterprise AI Studio

The implementation arm — readiness audits, workflow automation pilots, and intelligent assistant deployment for enterprise teams.

Visit Enterprise AI Studio →
SMB pilots

Smart Biz AI Hub

Practical AI pilots and guides for smaller teams — working pilots measured at 30, 60, and 90 days, not demos.

Visit Smart Biz AI Hub →
Engagement patterns

Three ways an engagement starts.

Choose the starting point that matches where you are — each pattern is described in detail on the Work page.

Enterprise AI Studio

AI Transformation Readiness Audit

Prioritized use-case map, risk assessment, and implementation roadmap.

How it works →
ProductExec

Product Operating Model Reset

Decision rights, roadmap governance, discovery cadence, metrics, and workflow design.

How it works →
Enterprise AI Studio

AI Implementation Pilot

Working pilot for automation, assistants, document intelligence, or workflow agents.

How it works →

See all six ways an engagement starts →

Quick answers

Common questions.

Who is Kevin Owens?

Kevin Owens is a four-time Chief Product Officer and AI SaaS product leader based in London. He has led product across SaaS, media, and enterprise software, and now helps SaaS and enterprise leadership teams turn AI ambition into operating models, roadmaps, and products that ship — through executive advisory at ProductExec and implementation at Enterprise AI Studio.

What is an AI-native product operating model?

An operating model where AI investment runs as a bet portfolio instead of a fixed roadmap, quality is defined by evals instead of prose specs, success is measured as learning rate instead of launches, discovery runs as evidence loops, and AI fluency lives inside every product team rather than a separate AI group. The flagship essay The AI-Native Product Operating Model covers all five shifts.

How do you assess an organization's AI readiness?

With the AI Readiness Score: a two-week diagnostic that scores five dimensions from 1 to 5 — data foundations, workflow clarity, decision rights and governance, capability density, and adoption posture. The lowest dimension determines the right first move, which is almost never buying model access. A three-question quick version lives in the Lab.

How should SaaS companies price AI features?

On a three-rung ladder that follows how much of the job the AI completes: assistive copilot features included in seats, workflow features priced per unit of completed work on a hybrid platform-plus-meter model, and end-to-end agents priced against outcomes. Pricing AI Features in a Seat-Based World lays out the full framework and the margin math behind it.

What does a fractional CPO engagement look like?

CPO-level strategy, portfolio prioritization, leadership rhythm, and stakeholder translation for teams at a strategic inflection point — without the twelve-month search for a full-time hire. Advisory and fractional CPO work runs through ProductExec; representative engagement patterns are on the Work page.

Next step

Ready to move from AI ambition to execution?

Whether you need strategy clarity or a working system — let’s find the right starting point.

Not ready for a call? Start with the 3-question readiness check in the Lab.