Choose the workflow because it repeats and can be checked
SMB and mid-market executives should evaluate an AI readiness assessment by asking whether it names the first workflow, the source material, the accountable owner, and the review model before a vendor demo begins. RSM middle-market AI survey, San Francisco Fed analysis of AI and small businesses, and the OECD report on AI adoption by small and medium-sized enterprises support a narrow operating approach for SMB and mid-market AI adoption: start where the business can name the owner, source, action, and value.
A strong assessment should identify workflow candidates, data quality gaps, permission boundaries, change-management burden, and expected operating value before any demo script appears.
Use the workflow automation screen to separate high-value first use cases from tasks that only look attractive in a demo.
Build the control layer before users trust the answer
NIST AI Risk Management Framework and CISA AI Data Security Best Practices both point to the operating work behind safe AI: approved data, access boundaries, monitoring, incident handling, and human accountability. For an AI readiness assessment, those controls are not administrative overhead. They are the difference between a useful roadmap and a software-led recommendation.
Ask whether the assessment reviews source data, access rights, governance ownership, exception handling, and measurement design. If the answer is only a maturity score, it is not enough to guide production work.
Use the AI use-case scoring model to rank value, readiness, risk, and adoption burden before committing budget.
Measure operating value, not tool activity
Deloitte State of AI in the Enterprise 2026 frames the gap between experimentation and production value. The same gap appears in readiness work for growing companies: teams can generate drafts or summaries quickly, but value only shows up when the business action becomes faster, cleaner, or less dependent on individual memory.
The output should be a ranked roadmap, not a generic maturity label. It should say what to automate first, what not to automate yet, what needs cleanup, and what evidence will prove value.
Use the assessment to reduce vendor risk and focus leadership attention on the workflow that can survive real operating conditions. Use the 90-day AI implementation plan to move from pilot to governed production without broad rollout risk.
