Case Studies

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.

ILLUSTRATIVE CASE

From AI Pressure to Aligned, Responsible Adoption (Illustrative – 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

CASE STUDY

Rebuilding Leadership Alignment in a Global Sales Transformation (Anonymized – Global Tech)

A global B2B technology company was modernizing its enterprise sales motion, asking sellers to adopt new tools, processes, and ways of working while also changing compensation. Resistance was loud and rational: sellers doubted CRM value, questioned whether leaders used the data, and worried the changes would not help them close more business.


Working from within the sales excellence function, the change and communications leader clarified the transformation narrative, surfaced eight real barriers from the field, and helped senior leaders confront three critical behavior gaps — including the fact that many had not used the CRM themselves. A leadership workshop, revamped champion networks, seller led enablement, and better measurement led to double digit improvements in CRM usage, forecast accuracy, and account planning, along with stronger alignment at the top.

 

  • Who it’s for: CROs, sales excellence and revenue operations leaders, and executives leading complex sales transformations.

  • Read the full case study

CASE STUDY

Scaling Seller Effectiveness with an AI Knowledge Assistant (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.​

  • Read the full case study

ILLUSTRATIVE CASE

How a Content-Driven Agency Adopted AI Without Losing Quality, Trust, or Its People (Illustrative – Comms Agency)

A mid-sized, content-driven B2B agency was feeling AI pressure from all sides: clients asking hard questions in RFPs, junior staff experimenting, and senior leaders worrying about erosion of craft and talent pipelines. Adoption was uneven and uncoordinated, with real anxiety about relevance, quality, and confidentiality.


This composite scenario shows how an agency can reframe AI as a quality and trust issue, not just a speed lever. By defining a human-led AI philosophy (“Enhanced by AI. Led by humans.”), setting security guardrails, designing a repeatable AI-assisted content process, and rethinking how juniors and seniors grow with AI, the agency uses AI to reinforce its differentiation instead of undermining it.

 

  • Who it’s for: Agency CEOs, managing directors, and practice leaders who want to use AI in client work without sacrificing craft, trust, or their people.

  • Read the full illustrative case

supporting CASE

Enabling Responsible AI Adoption Inside a Global Communications Team (Enterprise Tech)

A six-person internal communications team supported more than 5,000 employees through transformations, tooling shifts, and crises — with no backfill during layoffs and shrinking capacity. Leadership needed the team to “do more with less” without eroding trust, quality, or wellbeing.


With a secure, internal LLM as a foundation, the team established clear guardrails, focused on practical use cases, and built coaching and skills so both junior and senior communicators could use AI well. Over time, they cut time to first draft from hours to minutes, increased consistency across initiatives, synthesized employee feedback more quickly, and sustained performance without burning out.
 

  • Who it’s for: Heads of Communications and HR/People leaders supporting global workforces through intense change.

  • Read the full supporting case