AI Enablement

Decide where AI changes the work. Prove the result in the accounts.

Acrobatic decides where AI changes how your organisation works, across every function, and proves the cash result, with Finance as controller of the value. It starts with a business case your finance team will sign and ends with one that reconciles to the ledger.

Problems we solve

  • Everyone has an assistant and nothing has reached the accounts. Tools were deployed, hours were "saved", and no budget holder gave anything up.
  • Pilots multiply and none of them scales. There is no list, no funding test, no stop rule and no one person who owns the cost base the pilots are supposed to reduce.
  • Nobody has written down what AI may decide alone. So every deployment generates flags, rules and review work, and the saving is absorbed by the people checking it.
  • Posts are refilled before anyone asks whether the work still needs a post. Once a post is filled, AI only frees capacity.
  • The board cannot say what it is approving.

What we offer

  • AI Readiness and Business Case.

    The entry conditions checked, a baseline Finance reconciles to the ledger, benefits in three categories, four named routes to cash, and an opening case of at most ten pages with a target and a floor. Weeks 0 to 6, to Gate 0.

  • Scope and Portfolio.

    A process inventory across every function, a first wave of at most three domains, six funding tests, a stop rule and a one-page portfolio list. Each initiative: a one-page idea, a six-week shadow trial, a 90-day review.

  • Work, Roles and the Vacancy Gate.

    Decision rights, a role impact statement for each affected role, a workforce plan, and a vacancy gate on every post and contractor extension, signed jointly by the accountable executive and the finance lead.

  • Context, Data and Platform.

    Context in four layers, data contracts for every dataset, a buying rule no system may fail, and a small platform: one assistant, one governed store, one document store. On request we select and recommend the platform against the same rule.

  • Governance and Tolerances.

    A no-go list only the audit committee can change, three approval tiers, written tolerances the board approves as risk appetite, an audit protocol agreed with your auditors, and named people who can stop any deployment.

  • Programme and Gates.

    One accountable executive, one budget line, one 45-minute monthly review, a board briefing before Gate 1, and four gates set against your budget cycle. Expect about one initiative in five to be stopped.

  • Realisation and Closing Case.

    A full cost model including induced work, guardrail measures that hold the cash back if service falls, quarterly reconciliation of the register, and a closing case at 18 to 24 months.

How we work

  1. Frame, weeks 0 to 6.

    Purpose signed by the chief executive; vacancy gate live; baseline done; first wave chosen; opening case at Gate 0.

  2. Prove, weeks 6 to 12.

    First deployments run in shadow mode beside the manual process; flag rates measured; tolerances proposed; audit protocol agreed.

  3. First wave, months 3 to 6.

    Tolerances approved; first deployments live; next year's budget built on the case at Gate 1.

  4. Scale, months 6 to 12.

    A second wave; the first initiatives stopped; Finance validates net cash at Gate 2.

  5. Embed, months 12 to 24.

    The vacancy gate and funding tests become normal budgeting; closing case and independent review at Gate 3.

Who it is for

Chief executives, finance directors and operations directors of organisations with roughly 50 to 2,000 staff, and public bodies, who want AI to show in the accounts and are prepared to say openly how posts will be released. Larger groups apply the same method unit by unit with a group layer above.

Experience

  • A finance function built AI-first. For a newly established public-sector research body: corporate functions designed from zero with an AI-enabled operating model, a governance and controls framework, and a programme of strategic and tactical AI initiatives. In progress.
  • The data foundation AI needs. Forecasting data standardised across 120 markets for a global consumer healthcare company; a governed data platform consolidating the financial data of every UK public body.
  • Programme leadership in regulated and politically sensitive environments. Thirty years of delivering process and system change in central government and consumer goods, where an error is visible and a board can stop a programme in a week.
  • What the published evidence says. Most organisations report no effect of AI in their accounts; those that do have redesigned their work; and human review is a large, under-counted cost. The method turns those three findings into controls: redesign first, tolerances in writing, oversight costed, and cash counted only when a budget changes.

Results under this methodology are measured and reported to each client against its own baseline and reconciled to its accounts. We do not publish them.

Frequently asked questions

Do you select or implement AI products?

We select the platform on request, under the buying rule and supplier terms. We do not select or implement core systems of record; where a workflow needs one, that is a Finance Transformation engagement.

Why is saved time not counted as money?

Because it does not reach the accounts. A cash benefit counts when a post, a contract or a spend line changes. Capacity and service gains are tracked in their own categories and reported to the board beside cash.

What is a tolerance?

The written level of value, error or risk below which nobody reviews an individual item. Below it, AI decides and logs; in the middle band, AI proposes and the process owner reviews a weekly digest; above the threshold, a named person decides.

What does the vacancy gate do?

Before any post is refilled or created, or a contractor extended beyond three months, the requester shows why existing people using AI cannot do the work. Without it, AI only ever frees capacity.

How does this work with our finance systems programme?

The two lines share one process inventory, one data contract and one benefits register, and one programme claims each saving. Where the cash comes from an AI deployment inside a workflow, AI Enablement leads; where it comes from a system, process or sourcing change, Finance Transformation leads.

Start with the entry conditions: a two-week check of whether your organisation can build a baseline, name an accountable executive, and say openly how posts will be released.

Email
[email protected]
Telephone
+44 7887 742418
Location
London, United Kingdom

See also: Finance Transformation