Portfolio AI Assessments
We help you shake the tree to find where AI will pay off most in your portfolio. We score every company on how much AI could be worth there, how ready it is to capture that value, and whether it can do so before you exit.
We weight three factors to build a prioritization score for each portfolio company
We use a systematic framework for scoring companies that weights three factors to reach their final score: value, readiness, and time-to-exit (hold period). We ask the same questions about every company, so the results can be compared side by side. The scoring model was designed by our CTO, Dr. Craig Booth, drawing on a decade of quantitative modeling as a research scientist. Certain conditions cap a company's score regardless of other factors, such as a core system migration with months left to run, a CEO or CFO transition, or contracts that pass savings to customers instead of EBITDA.
Value
We assess the company's weight in fund returns, the share of its cost base in work AI can change, its volume of repeatable work, whether the value creation plan already counts the savings, and whether AI could raise its exit multiple.
Readiness
We assess how well the company's processes are documented, whether its systems give AI reliable data to work with, whether its teams already use AI, and whether leadership will commit time to the change.
Time left in the hold
Less ready companies take longer to see a return. We compare each company's expected time to value with the months left before exit, so companies that cannot realize the value in time are not prioritized.
Every company lands in one of four places
We plot each company by the value AI could create against its ability to realize that value before exit. Ability is measured as the time to run-rate impact on the P&L, which is usually much longer than the time to a first demo. A company with high value and too little time left to capture it has a timing problem, and the answer is to build its foundations early.
Build
Fix the foundations first
Lead
Start AI projects now
Park
Defer for now
Prove
Run a focused pilot
The Portfolio AI Assessment process
Gather the facts on each company
With your deal and portfolio operations teams, we record the months left in the hold for each company and answer the same set of questions about it: how well its processes are documented, what its systems and data can support, who already uses AI, and how much capacity its leadership has for change.
Score readiness and value
We score readiness on four dimensions and value on five, each from 1 to 5. Caps apply where a known condition limits the result, such as a core system migration, a CEO or CFO transition, or contracts that pass savings to customers.
Weigh time to value against the hold
A company's readiness sets how long AI work will take to reach run-rate impact. We compare that with the months left before exit to set each company's priority.
Place every company and set next steps
Each company is placed in Lead, Build, Prove or Park, with a recommended next step. Lead companies go on to an AI Value Creation Action Plan.
The output of a Midici Portfolio AI Assessment
A portfolio AI prioritization summary
We share a portfolio AI prioritization summary that shows every company in your portfolio plotted by value against its ability to capture that value, on one chart, alongside insights about each company's AI readiness risks and advantages.
An AI impact priority score for each portco
A ranking based on value, readiness and the time left in the hold, with the reasons behind each company's place.
A recommended set of next steps for each company
For companies that land in the “Lead” category, Midici recommends having our team work with them to produce a full AI Value Creation Plan.
