Where the hours go
Your time-tracking data shows how hours are spent across different areas of the business.
AI Strategy
An AI strategy built around your team's work.
Help your people do more and catch errors earlier. We help you sort through the AI choices and find low-risk places to begin, using the industry knowledge your team already has.
Talk about an AI strategyStart with the work
Your people know where the work gets stuck.
Customer Equity Labs starts with how your team works today. Time data shows where the hours go. Conversations with your people explain what takes effort, where mistakes creep in, and what needs their judgment.
Use AI as the glue between the tools and steps your people already use. Put their industry knowledge into clear instructions and reusable checks. Start with work that's easy to review, then build on what proves useful.
Allison audited our AI effectiveness, suggested a more robust AI strategy, trained our 40-person team, then built alongside us. This adds automation to almost every part of our business while honoring our ‘human first, human last’ philosophy.
Photo: Markentum
An anonymized example
What the assessment found at one agency.
An agency with 26 billable staff scored 34 out of 100 on AI readiness. Its time data showed an estimated $717,000 a year in recoverable capacity within hours already logged for clients.
$717,000Estimated annual recoverable capacity within logged client hours
Up to $1.9 millionEstimated annual capacity in a full redeployment scenario
These are two scenarios for the same agency, not amounts to add together. They describe possible capacity, not savings or new revenue the agency had already realized.
What we examine
A clearer view of the work.
What's already being used
Which AI tools teams use, how often they use them, and how useful people find them.
What happens step by step
What AI handles, where it helps, what remains manual, and what people tried and stopped using.
What the numbers need explained
Conversations with departments about where work gets stuck and what makes it difficult.
What you get
A plan for where to start.
The assessment brings the findings together so you can choose the work to take on first.
- A readiness score from 0 to 100 for each area of your business and overall.
- An estimate of the capacity AI could free up, expressed in hours and dollars.
- A comparison with industry-relevant measures where comparable data is available.
- A sequenced plan: what to do first, what comes next, and what to leave alone.
Every business can measure its current work and AI use. Outside benchmarks depend on the work being compared and the data available. Capacity is an estimate of time that could become available, not money already saved or revenue already earned.
How it runs
From work data to a decision.
Data gathering, conversations with your team, and a workflow review lead to a report and a plan.
About 4–6 weeks
From data gathering to the finished report and plan. The recommendations identify which work to change first and what to measure as it changes.
The customer connection
If AI frees up time, where should that time go?
Your people bring knowledge and judgment to customer relationships. A useful AI strategy leaves room to ask where more of that attention would matter.
Helping a customer make a difficult decision. Following up before a problem grows. Learning what customers need next. These are choices about how to use capacity, and hours saved alone cannot make them for you.
Start a conversation
What work needs a closer look?
Tell us where your team is stretched, how you're using AI now, and what you'd like to change.
Talk about an AI strategy