Results

AI adoption is no longer a question of if — it’s a question of how you bring your people, leaders, and systems along. These case studies show what that looks like in real organizations and in composite scenarios drawn from many leadership conversations. They are written for senior leaders who care about three things at once: business outcomes, responsible use of AI, and the humans asked to change how they work.

CASE STUDY

Leading Change Across a Global Sales Transformation

Intel Corportation, Global B2B Tech

 

A major global technology company facing competitive pressure, declining market share, and a fundamental shift in its commercial model needed to overhaul how it sold. That meant changing sales compensation, tools, methodology, customer targeting, and culture — simultaneously, across a globally distributed salesforce already skeptical of leadership.

 

Over two years, I stepped into a fragmented transformation effort, unified a disjointed change team, and built a rigorous change strategy from the ground up. The work included restructuring how sellers used data and AI, partnering on a fully reimagined annual sales conference, rebuilding three global change champion networks, and surfacing the leadership misalignment that was quietly undermining the whole effort. The results were uneven — as they often are in large-scale transformation — and the lessons were hard-won.

 

  • Who it’s for: CHROs, CCOs, CROs, and transformation leaders navigating multi-dimensional organizational change where the human barriers are as significant as the strategic ones.

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CASE STUDY

AI Strategy Grounded in Mission: A Board-Ready Blueprint for SustainableIT.org

SustainableIT.org, Global Technology Nonprofit

 

A global nonprofit advancing responsible technology practices needed an AI strategy that could make a new learning academy financially viable, strengthen member value, and position the organization for its next chapter of growth. With a two-person staff team without an established AI practice, and a constrained budget, the path forward had to be both ambitious and realistic.

 

Working closely with a consulting partner, we helped SustainableIT.org see past the assumptions that had made a learning academy feel out of reach, starting with a fundamental rethink of how AI could change the economics of content creation. The result was a board-ready blueprint the leadership team could actually act on, and enough confidence in the direction that the board expressed interest in continuing the advisory relationship through implementation.

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  • Who it’s for: Senior leaders at mission-driven organizations — executive directors, VPs of strategy or operations, and board members — facing pressure to modernize programs, diversify revenue, or incorporate AI into operations with limited internal capacity.

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CASE STUDY

Scaling Seller Effectiveness with an AI Knowledge Assistant

Intel Corportation, Global B2B Tech

 

In a large technology organization, sellers supporting deeply technical products depended on personal networks to get answers to customer questions. Newer sellers were at a disadvantage, engineers were overwhelmed, and response times often stretched from days to weeks.

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A Sales AI team built an internal, RAG-based knowledge assistant, and a dedicated change and adoption effort focused on the human side: grounding design in real seller pain, setting clear guardrails, addressing the hidden influence of engineering behavior, and orchestrating a phased rollout with strong enablement. Within six months, roughly 5,000 global users were resolving more than 90% of queries through the assistant, with an estimated $4M in annual savings, faster onboarding, reclaimed engineering time, and a reusable blueprint for the broader AI platform.

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  • Who it’s for: Sales, product, and AI platform leaders deploying AI assistants for complex, knowledge-intensive sales.​

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CASE STUDY

Saying Yes Responsibly: Building AI Alignment at World Salmon Council

World Salmon Council, Environmental Education Nonprofit

 

World Salmon Council — a Portland-based nonprofit that brings students to Oregon rivers to study salmon and watershed health — was in a period of reset. A new executive director in her first leadership role, one and a half staff, a working board of retired educators and business advisors, and constant pressure to do more with less. AI was an obvious lever. It was also a genuine problem: for an environmental organization, the energy and water demands of AI infrastructure are not an abstraction. A proposed data center in the Columbia River Gorge would draw cooling water from a tributary with an active salmon run.

 

Two 90-minute leadership sessions, two weeks apart with structured hands-on experimentation in between, gave the board and executive director a working understanding of the technology, an honest reckoning with the tension between the tool and the mission, and a decision they made themselves: yes to AI, conditional on guardrails they defined. The organization left with five named work streams, a board advisor paired to each, a quarterly review commitment, and a reordered set of priorities. Following the workshops, the board requested an ongoing advisory engagement to coach the executive director; that work is written into the organization's budget and will begin as funding allows.

 

  • Who it's for: Executive directors and board members at small mission-driven organizations weighing whether and how to use AI — particularly those whose mission gives them real reason to hesitate.

ILLUSTRATIVE CASE

From AI Pressure to Aligned, Responsible Adoption

illustrative composite, Mid-sized B2B Company

 

A mid-sized B2B company (~2,000 employees) had AI pilots everywhere but no shared story about why any of them mattered. Leaders urged teams to “use AI,” while employees quietly experimented, worried about risk, and asked for clearer guidance.


By reframing AI as a leadership and change challenge, the organization aligned executives on priorities and guardrails, built role-specific support for managers and teams, and focused experimentation on a few high-value use cases tied to real work. The result was faster first drafts, less shadow AI, more grounded decisions, and a noticeable drop in anxiety as expectations became explicit.

 

  • Who it’s for: CEOs, COOs, CHROs, and functional leaders in mid-sized B2B organizations wrestling with AI pressure, uneven adoption, and unclear boundaries.

  • Read the full illustrative case