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AI readiness for professional services companiesYou sell hours. Your systems can’t agree how many.

Professional services firms record time in one system, bill in another, plan people in a third and forecast in a spreadsheet. AI for utilisation, forecasting and billing needs the client, the engagement and the hour to match across all of them.

Starts with a 30-minute call. Commits you to nothing.

A Leverability read shows which AI ideas you can use now, after fixes, or not at all. Illustrative example, not a client.

The AI on the table

The AI plays proposed in professional services.

What vendors and plans put forward in professional services, what each play needs from the data, and the gap that holds it back. In a real Read, each call rests on your Truth Score™ (a score out of 100 for how far your data can be trusted) and the records behind it. The calls here are an illustrative read, not a benchmark.

  • Revenue and pipeline forecasting

    “Forecast fee income from the pipeline”

    What revenue forecasting needs
    Needs work
    Needs
    Won work that matches engagements and invoices
    Held back by
    Engagements opened with no CRM opportunity
  • Work in progress and cash forecasting

    “Predict billing and cash by week”

    What 13-week cash flow forecasting needs
    Needs work
    Needs
    Time recorded against engagements that carry to invoices
    Held back by
    Billable hours that were never invoiced
  • Engagement letter extraction

    “Read terms and rates from every engagement letter”

    What document intelligence needs
    Needs work
    Needs
    Letters that match the engagement record
    Held back by
    Rates in the letter that differ from rates billed
  • Client attrition

    “Spot clients drifting away”

    What customer churn prediction needs
    Needs work
    Needs
    One client across CRM, time and billing
    Held back by
    Clients under different names in each system
  • Ask-your-data for partners

    “Utilisation and realisation on demand”

    What natural-language analytics needs
    Blocked
    Needs
    One definition of utilisation and realisation
    Held back by
    Utilisation calculated differently by each practice
  • New business lead scoring

    “Rank proposals by likelihood to win”

    What lead scoring needs
    Deploy now
    Needs
    An outcome recorded on every proposal
    Watch for
    Lost proposals never recorded

Illustrative example, not a client. Your calls depend on your records.

The systems estate

The systems behind the plays.

Written for consultancies, accountancy, legal, engineering and IT services firms, running a CRM, a time or practice management system, a finance system and an HR system, with a lot held in spreadsheets. Each system is built to be right about one thing. None was built to agree with the others, and the plays above all run across more than one.

Typical, not exhaustive. Anything that exports to CSV or Excel can be included.

The gaps

Every system looks clean on its own. The truth is in the gaps between them.

One record traced across your time and practice system, finance and the CRM: each system right about its own part, and the three still disagree. Then the gaps that hold the plays back. Which of them exist in your data is what a Truth Score Read finds out.

Illustrative example, not a client. The systems change by industry; the method doesn’t.

Where the plays sink

  • Time ↔ Finance

    Billable time recorded but never invoiced

    SinksWIP and cash forecasting

  • CRM ↔ Practice

    Engagements with no won opportunity, or the reverse

    SinksRevenue forecasting

  • HR ↔ Time

    Time recorded by leavers, or by people missing from HR

    SinksUtilisation and capacity planning

  • Documents ↔ Finance

    Rates in engagement letters that differ from rates billed

    SinksRealisation analysis and pricing

Gaps to test in the sector, not client findings.

Regulation

The rules that shape which plays you can run.

Kept short and honest. This is not legal advice: we evidence what your data can support; your counsel decides what the rules require.

  • Client confidentiality

    Engagement letters and professional rules can restrict how client information can be used, including with AI tools. Check them before any client data reaches a model.

  • GDPR

    Time and HR records describe identifiable people. Utilisation AI that evaluates staff needs a lawful basis and a clear, stated purpose.

  • The EU AI Act and people decisions

    AI used in recruitment, promotion or allocating work to individuals is listed as high-risk. Staffing and utilisation tools can fall into that category.

Governance and compliance

Your plan, tested

Got a plan that names these plays?

Send it with your exports. A Truth Score Read tests the AI in it against your own records, within 5 working days of complete exports. Go further with an AI Investment Review: every bet ranked, your plan tested play by play, and a roadmap to hand to your own team.

  1. 01

    Send the plan, if there is one

    The business plan, growth strategy, value creation plan or the vendor proposal. We pull out the AI plays in it and the targets that lean on them.

  2. 02

    Send exports from two or more systems

    Usually CRM and time and practice management to start. Spreadsheets count. Under NDA, using the field list we send.

  3. 03

    Test each play against the records

    Each play mapped to the data it needs. Our engine matches the customers, people, deals and invoices across your exports to see whether that data is there and agrees, and every red flag is checked by hand against sample records.

  4. 04

    Get the verdict, play by play

    A signed memo: your Truth Score, a Leverability read marking each play Deploy now, Needs work or Blocked with the reason in your own records, and a verdict: sign, fix first or walk away.

What you get back

See what comes back: a real sample memo.

One fictional B2B software company, Example Co: 72,837 records in 7 exports from its CRM, finance and HR systems, run through the same engine and the same checks as a paid Truth Score Read. Each system passes its own checks. Matched across systems, only 13% of deals tie to an invoice.

Not a software company? The sample is one, but the method doesn’t change; only the systems do. For a professional services business the same match runs across your time and practice system, finance and the CRM, and every red flag is checked by hand the same way.

Real engine output on generated test data, not a client.

Questions

AI in professional services, answered plainly.

Anything else, ask on the 30-minute call. It commits you to nothing.

Book the call
Our practice management system isn’t on your list. Does that matter?

No. Anything that exports to CSV or Excel can be compared. Time and practice systems usually produce engagement, time entry and WIP reports; we send the field list after the call.

Partners trust their own spreadsheets. Why would they trust a score?

Because every red flag points to records they can check themselves, and each one is checked by hand against sample records before sign-off. The Truth Score is a score out of 100 for how far your data can be trusted, and every pillar shows what was measured and what wasn’t, so a partner can check the work.

Can you test the AI plans in our strategy?

Yes. Send the strategy or business plan with your exports; we pull out the AI plays and show, play by play, whether the data they need is there and can be trusted.

Is client data involved?

Client names and billing records, yes; client work product, no. Everything is under NDA and a data processing agreement, and we keep quality metrics, not your records.

Before professional services AI gets funded, find out what your data can carry.

Exports from two or more systems, plus the plan or proposal if there is one. A signed verdict, play by play, within 5 working days of complete exports. Starts with a 30-minute call. Commits you to nothing.

Starts with a 30-minute call. Commits you to nothing.

Get your Truth Score