Assess workflow readiness before tool appetite
A 25-person consulting firm usually has valuable reusable material scattered across proposals, deliverables, call notes, and partner knowledge. McKinsey State of AI 2025 shows why workflow redesign matters: AI value is harder to capture when teams stay in pilot mode and do not change operating routines. The readiness question is not whether consultants will try AI; it is whether the firm can govern a repeatable workflow.
Start with four areas: knowledge reuse, proposal development, delivery quality assurance, and client-data handling. Each area needs source ownership, review standards, and a measurable operating outcome.
Check data, governance, and adoption capacity
IBM Institute for Business Value AI capabilities research frames AI return around capabilities, not just tools. For a consulting firm, those capabilities include reusable source libraries, clean permissions, partner review cadence, and enough training for consultants to use AI without inventing unsupported claims.
PwC Responsible AI survey is useful because consulting work often touches confidential client context. A readiness assessment should define which materials can enter AI-assisted workflows, which require anonymization, and where human review is mandatory.
Pick one workflow that proves quality
Bain agentic AI transformation report points toward agentic workflows, but a small consulting firm should not start with broad autonomy. Start with one constrained workflow such as account research, first-draft proposal support, or delivery QA. Measure cycle time, partner revisions, source citation quality, and client-ready output quality before expanding.
Use the AI Transformation Blueprint for the operating model and the AI Opportunity Score to rank candidate workflows.
