An AI plan your board can act on.
AI board advisory turns workforce opportunity into decisions about investment and delivery. Catapulze helps leadership teams and boards see the work, readiness, ROI per function and human transition in one structured plan.
What is AI board advisory?
It connects the opportunity in your existing work with the decisions your board needs to make. Which functions have work that AI can support? What must change in the systems, processes and teams? What investment is required, and what should be measured? A board-ready plan puts those questions together rather than presenting a collection of disconnected use cases.
Our method is Measure, Build, Embed and Workforce Transition. Pulze Radar is the engine of Measure, mapping roles and processes before the first value case is selected. Leadership can align on priorities and a delivery roadmap while keeping the effects on people and ownership visible.
What evidence belongs in the investment decision?
The report brings together task-level role maps, augmentation scores and a roadmap sequenced in delivery waves. It records tooling and integration readiness for systems, alongside risks, enablers and the ROI case for each function. This makes it possible to separate work that can begin from work that needs further assessment. A high score does not remove the need to check data quality, access, connections and human review.
How is ROI per function calculated?
We use your own roles, hours and costs to build the case for each function. The roadmap connects the work that can change with the investment needed to change it. We agree what to measure, including capacity freed and changes in the quality of work. A score on its own is not a financial result. The business case must show what the time is worth, what implementation costs and where people will use the capacity.
Our separate illustrative finance model uses a six-person team at €65 per hour across seven workstreams. It shows 267 hours of monthly capacity, approximately €208,000 of annual capacity and €72,000 of year-one investment, with a 2.9x return and four-month payback. These are illustrative assumptions, not client data, realised savings or a forecast for your organisation. Capacity is not automatically a cash saving or a guaranteed P&L improvement.
What does an augmentation score tell you?
An augmentation score shows the share of the work AI can support. Pulze Radar looks at the work, not the person doing it. Each task is considered through four signals: Structure, Repetition, Tooling fit and Risk surface. These ask how clear the work is, how often it repeats, whether the tools are ready and what a mistake could cost. Scores reflect what technology can reliably do today, not a promise about future capability.
On the 0 to 100 scale, 80 and above is AI-led, 50 to 79 is hybrid and below 50 is human-led. These bands describe the balance of AI support and human involvement. They are not a percentage of a person's role that should disappear. The Adopt, Trial, Assess and Hold rings guide readiness decisions. System access and risk can keep a high-scoring task from being ready to build.
What does the case show?
Modern Milkman: 26 roles and 351 tasks mapped. AI can support 80% of tasks today, with 24 build-first tasks and a roadmap in 3 delivery waves.
The analysis identified 24 build-first tasks, 10 business epics and two foundation epics. Another 97 of the 351 tasks appeared automatable but were blocked by internal systems. That distinction matters: a promising task does not become a working solution until access, connections and the data foundation are ready.
Finance Manager work scored 87% and Accounting & Operations Manager work 86%. Proposed finance support includes draft commentary, audit working papers, consolidations and answers to finance questions, with people reviewing outputs. AI can support 67% of Customer Success Ambassador work: AI drafts replies across chat, email and social, looks up orders and delivery issues, and turns QA feedback into coaching. Escalations and complaints stay with people. AI can support 58% of Customer Success Team Lead work: reporting, QA and performance monitoring move to AI. Leading the team, 1:1s and escalations stay human. An agent over Dixa and Looker supplies team-performance summaries and moves QA from samples to full coverage, while coaching stays with people. These describe the roadmap and proposed work, not published realised results.
What happens after the roadmap?
Measure is followed by Build, Embed and Workforce Transition. Strategy consultants and AI engineers work with your people to deliver the first solution, testing through a pilot where needed and integrating it into production. Data foundations, system connections and knowledge transfer belong in the work, rather than being left for your team to solve after launch.
AI embedded. We change the culture to curiosity, so you continue to earn marginal gains. Embed sets ownership, supports adoption and develops the internal capability to keep improving. Measured results guide the next investment decisions until your organisation can run it independently. Workforce Transition looks for better work, reskilling and redeployment first. Sometimes roles end. Where they do, we support a fair, clear and human process with your HR and legal advisers. We do not provide legal advice.
Last updated: 7 November 2026