Disclaimer
This scenario breakdown is a fictionalized, illustrative case study created for educational and strategic thinking purposes. While inspired by real-world patterns and organizational challenges, all details—company context, team structure, and suggested approaches—are generalized and do not represent any specific employer, client, or confidential situation.
The content is designed to demonstrate strategic problem-solving, not to prescribe one-size-fits-all solutions. Readers are encouraged to adapt ideas and frameworks to suit their unique organizational needs, capabilities, and compliance contexts.
A mid-size SaaS company (approx. 300–500 employees) has a leadership team excited about AI but no concrete implementation roadmap. They’ve experimented with ChatGPT internally, a few developers built side projects, and execs keep mentioning AI in town halls — but there’s no structure, budget, or alignment. The product org is fragmented — PMs are unsure where AI fits in the roadmap, engineers are unclear on approved tools or processes, and data privacy concerns are creating friction between innovation and compliance. There's potential, but no orchestration.
Root Problems
- No Shared AI Vision: Leadership mentions AI in aspiration, but it hasn't translated into prioritized roadmaps, funding, or team charters.
- Capability Gaps Across Roles: Engineers lack access to models or experimentation space. PMs lack fluency to define realistic AI features.
- Missing Infrastructure: No secure, sandboxed environments for testing; no GPU access; fragmented toolchains.
- Risk Aversion: Legal, security, and privacy concerns create a culture of "better not try."
- Isolated Prototyping: Early experiments aren’t visible, shared, or reused — most die in the dev’s notebook.
To bring coherence to this chaos, we use the "Enable → Align → Build" strategic rollout model. It’s designed for speed and structure.