Sample report for a fictional professional services firm. Your report is built from your own answers.
Your AI readiness · Lite
Sample firm
Professional services · 50 to 249 employees · Owner or CEO
61/100
Scaling
AI is part of how work gets done in many areas, with ownership, policy, and training in place. The opportunity now is to measure results, close the gaps in your weakest areas, and move proven use cases into core workflows.
AT A GLANCE
Your summary
- Top priority
- Governance and Policy
- Strongest area
- Strategy and Leadership
Your top 3 moves this quarter
- 1.
Put your AI rules in writing
Publish a one-page policy naming approved tools, the client data that never goes into AI, and who reviews output before it leaves the firm.
- 2.
Sort your sensitive data
List the three systems that hold client data, mark what is confidential, and confirm who can access each one.
- 3.
Turn pilots into measured workflows
Pick two workflows, such as proposal drafts and meeting summaries, and record the time they take for two weeks as a baseline.
YOUR SCORES
AI Readiness Radar
YOUR SCORES
AI Readiness Scores
How do you pay for AI?
A set yearly budget75 out of 100
Answers are not available in this saved view.
Answers are not available in this saved view.
Do you measure what AI is doing for you?
Just impressions25 out of 100How is AI used in day-to-day work?
Some people, for basic tasks50 out of 100
Have you sorted out which information is sensitive and who can see it?
Informally25 out of 100
Do you have written rules for using AI?
Written, but few people know about it50 out of 100
YOUR ANALYSIS
What your answers tell us
Leadership is committed and people are building real skills, but the rules have not caught up. Governance is the gap that matters most: staff use AI on client work without a written policy, and sensitive data is handled informally. Fix the rules first, then clean up the data your best use cases depend on.
Put your AI rules in writing
You have a funded plan and a named owner, but no written AI policy. In a firm that handles client files, that is the biggest risk on this page.
First step: Publish a one-page policy naming approved tools, the client data that never goes into AI, and who reviews output before it leaves the firm.
Sort your sensitive data
Client data sits in several systems with informal access rules, so your best use cases cannot scale safely.
First step: List the three systems that hold client data, mark what is confidential, and confirm who can access each one.
Turn pilots into measured workflows
Teams use AI often, but results are judged by impressions.
First step: Pick two workflows, such as proposal drafts and meeting summaries, and record the time they take for two weeks as a baseline.
YOUR PLAN
Your first 90 days
Five steps, in order. Start step 1 this week.
- 1DAYS 1 TO 15Start here
You said: Written rules exist, but few people know about them.
Publish a one-page AI policy naming approved tools, banned client data and the review step, and send it to all staff.
You said Written rules exist, but few people know about them. Publish a one-page AI policy naming approved tools, banned client data and the review step, and send it to all staff.
Why: Clear rules protect client confidences before use grows further.
- 2DAYS 16 TO 30
You said: Sensitive information is sorted informally.
Label confidential data in your three main systems and tighten access to match each role.
You said Sensitive information is sorted informally. Label confidential data in your three main systems and tighten access to match each role.
Why: Clean, controlled data lets your best use cases scale safely.
- 3DAYS 31 TO 45
You said: Results are judged by impressions.
Record hours spent on proposal drafts and meeting summaries for two weeks before changing how they are done.
You said Results are judged by impressions. Record hours spent on proposal drafts and meeting summaries for two weeks before changing how they are done.
Why: A baseline turns AI value from opinion into numbers.
- 4DAYS 46 TO 75
You said: Some teams use AI, others do not.
Run a 30-day pilot on both workflows with named owners, using only approved tools, and compare results to the baseline.
You said Some teams use AI, others do not. Run a 30-day pilot on both workflows with named owners, using only approved tools, and compare results to the baseline.
Why: A measured pilot shows what to scale and what to stop.
- 5DAYS 76 TO 90
You said: AI spending is reviewed once a year.
Review pilot results with leadership, scale what worked, and put a quarterly AI review on the calendar.
You said AI spending is reviewed once a year. Review pilot results with leadership, scale what worked, and put a quarterly AI review on the calendar.
Why: Regular reviews keep spending tied to results.
By day 90 you should have
- A published one-page AI policy
- Confidential data labeled with role-based access
- A two-week baseline for two workflows
- A 30-day pilot compared with the baseline
- A quarterly AI review on the calendar
HOW YOU COMPARE
AI Readiness Matrix
- Foundations
- 45
- Adoption and Value
- 77
You sit in Adopting Ahead of Guardrails: people are using AI faster than policy, tools and data are keeping up. Compared with the peer marker, you are ahead on foundations and ahead on adoption. Moving up and right means pairing clear policy, approved tools and usable data with defined use cases and training, so both scores rise together.
- You
- Peers (kovac.ai estimate)
Foundations means policy, approved tools and usable data; Adoption means leadership, skills and real use cases.
You are ahead of similar firms on both; the plan helps you keep that lead.
The peer marker is a kovac.ai estimate based on our research and client work, not an average of submitted assessments. It will be replaced by real averages as more organizations complete the assessment.
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