Rank workflows before vendors
A 75-person business is usually too large for informal experimentation and too small for enterprise theater. The roadmap should start with repeatable workflows: intake, research, triage, drafting, handoff, reporting, and review. McKinsey State of AI research and IBM Institute for Business Value AI capabilities research both point toward the same conclusion: value depends on redesigning work, connecting data, and getting adoption from the team that owns the process.
The template should rank each workflow by pain, data readiness, risk, reviewability, and business value. That gives leadership a funding sequence instead of a tool wish list.
Design governance into the first phase
NIST AI Risk Management Framework helps make the roadmap practical because it asks leaders to map the use case, measure behavior, manage risk, and govern the system over time. For a 75-person company, that can be a simple operating cadence: workflow owner, data owner, reviewer, exception rule, and weekly metric.
PwC Responsible AI survey is also relevant because responsible AI is easier to install before habits harden. Permissions, customer data boundaries, and approval rules should be part of the first roadmap phase.
Use a roadmap to earn expansion rights
Bain agentic AI transformation research is a good reminder that agentic AI needs tools, permissions, monitoring, and exception handling. Do not begin with a broad autonomous agent. Begin with a constrained workflow that produces a reviewed output and proves adoption.
Use the AI Opportunity Score to rank candidates, then use the AI Transformation Blueprint when the leadership team is ready to turn the first workflow into a broader roadmap.
