On-site AI workshop: a strategic working day with your management team
When a management team workday is worth more than a 12-week consultancy engagement
Many boards are stuck in the same discussion: we need to do something with AI, but what exactly? A twelve-week Big Four strategy engagement delivers a report, not a pilot. A hackathon delivers prototypes, but no prioritisation. An AI course for your operational staff comes too early if the strategy isn't settled yet. Our on-site workday is a structured strategy session with your management team, working towards an AI roadmap, a chosen pilot and a business case you can act on from Monday.
Plan your workday View the agendaWho this workday is for
This is not training for developers, nor a workshop for operational staff. It is a working session for the people who decide on budget and strategy.
An AI strategy day works best with a compact management team of four to eight people who have direct decision-making authority. Think of the board, the COO, the CFO, the CIO or IT director, and business unit managers with P&L responsibility. An innovation lead or digital transformation manager may join, but the group needs enough seniority to give a go/no-go on a pilot by the end of the day.
What we explicitly do not do on this day: technical deep-dives for your IT team, broad staff training or hands-on tool demonstrations. For the latter, we offer a separate AI course for businesses in which your employees learn to work with ChatGPT, Copilot and related tools. The strategy session and that training can follow one another, but they are two separate products with different audiences.
We come with two people: an AI strategist who facilitates the discussion, and an experienced technical lead who can assess feasibility and architecture. No team of consultants, no junior note-taker slowing the conversation down. A small group, short feedback loops, and a quick route to a decision.
What you take away at the end of the day
No hundred-page report that disappears into a drawer. Three concrete deliverables your management team can use straight away.
AI roadmap on A3
A single clear A3 page with all your candidate use cases, clustered by horizon (now, 6 months, 12-24 months). For each use case: a brief scope, estimated value, data-readiness score, EU AI Act risk category and dependencies. Intended as a communication document for your board, management team members who were not present and, later, your IT organisation.
Pilot selection with scope
One chosen pilot project, with clear boundaries on what is and isn't included. Includes success criteria, required data, integration touchpoints with existing systems, and a rough estimate of timeline and effort. Not a vague intention, but a defined brief that can serve directly as an RFP or internal project proposal.
90-day business case
A substantiated business case for the first 90 days of the pilot: investment, expected savings or revenue, key risks, exit scenario, and a three-year TCO estimate. Not a spreadsheet with ten tabs, but a document your CFO can approve or reject in a single meeting.
In addition, the day delivers several softer outcomes that are often just as valuable: a shared vocabulary within your leadership team (what is an LLM, what is an agent, what is RAG), explicit assumptions and risk tolerances, and clarity on who within the company will own the AI roadmap.
Schedule for the working day
Eight hours, four blocks, one deliverable per block. We work with use-case canvases, prioritisation matrices and a business case template that is completed on the spot.
AI trends and use-case mapping for your business
A brief overview of generative AI, agents, RAG, fine-tuning and multimodal models, covering only what is relevant to your sector. We then map your key processes onto a use-case canvas: where manual work sits, where turnaround times are too long, where customers drop out of the process. The goal of this block: a longlist of twenty to thirty candidate use cases.
Sector examples and analogous cases
We show what comparable organisations in healthcare, retail, finance or industry have already rolled out, and where they encountered difficulties. No fictional cases, but public examples from annual reports, conferences and open-source implementations. Your leadership team recognises which patterns are relevant and which are not, and expands or trims the longlist based on this input.
Prioritisation by ROI and feasibility
The longlist goes through a two-dimensional prioritisation matrix: business value on one axis, technical feasibility on the other. For each candidate use case we score data readiness, AI Act risk category, vendor lock-in risk, GDPR/DPIA impact and organisational readiness. The result: a prioritised shortlist of three to five use cases, with explicit justification.
Pilot selection and 90-day business case
From the shortlist we choose one pilot. Together we complete a business case template: investment, expected impact, success criteria, key risks, dependencies and a 90-day timeline. At the end of the block you have a document on which your CFO and board can give a yes or no, not two weeks later after a follow-up, but now.
There is room for lunch and coffee between the blocks. We work with whiteboards, sticky notes and a laptop, not hour-long presentations. Your leadership team is actively engaged all day, not listening.
Comparison with a Big Four AI strategy engagement
The same question, a different approach. For some organisations, an engagement with a large consultancy is the right choice. For most SMEs and mid-sized organisations, a working day is more effective.
| Aspect | Big Four AI strategy | Appfront working day on site |
|---|---|---|
| Duration | 8 to 12 weeks | 1 day, around 2 weeks of preparation beforehand |
| Consultancy staffing | Partner, manager, 2-3 consultants | 1 strategist and 1 technical lead |
| Final deliverable | Strategy report (50-100 pages) | A3 roadmap, pilot scope, business case |
| Implementation | Separate engagement, often a different party | We build the pilot ourselves, no handover |
| Decision | After presentation to the steering committee | At the end of the working day |
| Suitable for | Listed companies, >5,000 employees | SMEs and mid-sized organisations, 50-1,000 employees |
We're not better than the Big Four — we're different. A twelve-week engagement adds value when multiple business units and hundreds of processes need to be analysed, or when compliance programmes require external assurance. For a management team that wants to define an AI roadmap and a first pilot, a workshop day is faster, more affordable and hands-on. And once the workshop is done, there is a team ready to actually build the pilot — see also our pages on AI development and enterprise AI implementation.
Industry-specific approach
Use-case mapping differs by sector. We tailor the sector examples, regulatory context and common pitfalls to your industry.
Care and healthcare
Use cases around intake automation, case summarisation, scheduling and logistics optimisation. Key contextual factors: GDPR and DPIA processes for patient data, NEN 7510, BIG registration considerations for decision-support models, and the stricter AI Act risk categories that often apply. We also look at which use cases sit outside the core clinical process and can therefore be delivered more quickly.
Retail and e-commerce
Use cases around product descriptions, demand forecasting, customer segmentation, dynamic pricing and intelligent customer service. Specific points of attention: integration with PIM and ERP systems, handling seasonal effects and cold-start situations, and the trade-off between quick generic LLM solutions and longer custom builds. We also draw on our experience in e-commerce development.
Finance and insurance
Use cases around document processing, fraud detection, risk classification, customer communication and compliance monitoring. Central themes: model explainability that supervisors will accept, AI Act high-risk classification for credit scoring or claims assessment, and the trade-off between on-premises hosting and the cloud. Here, governance is almost always a separate workstream in the roadmap.
Industry and manufacturing
Use cases around predictive maintenance, quality control via computer vision, production planning optimisation and knowledge management (making technical documentation accessible via RAG). Points of attention: integration with OT systems and SCADA, handling sparse data in small production runs, and the choice between edge deployment and central models. We also look at how this connects with your IT modernisation.
AI Act, GDPR and governance in the workshop day
An AI roadmap without a governance component is not a roadmap. For every candidate use case, we explicitly weigh the legal and ethical context.
AI Act risk categories
The European AI Act distinguishes prohibited, high-risk, limited-risk and minimal-risk AI applications. For each use case on your shortlist, we map which category applies and which obligations follow — think of documentation requirements, conformity assessment and human oversight for high-risk applications.
GDPR and DPIA
Use cases that process personal data often require a DPIA (Data Protection Impact Assessment). We flag which use cases trigger one and what a realistic DPIA lead time looks like. We are not a DPO, but we make sure you schedule the legal review in good time rather than only at delivery.
Vendor lock-in and TCO
Every AI stack involves trade-offs: a Microsoft Copilot stack is quick to roll out but hard to move away from, while an in-house open-source stack demands more engineering but gives you ownership. We discuss build-or-buy, model portability and exit scenarios, and factor three-year TCO into the pilot's business case.
Data sovereignty and hosting
For some use cases, hosting within the EU or within the Netherlands is a prerequisite. We discuss which options exist for on-premises, EU cloud and US cloud models, and which trade-offs in capability and cost follow from them. We don't argue for one option, but we make sure you understand what each choice means.
Our technical lead knows the relevant frameworks — AI Act, NIS2, GDPR, NEN 7510 — and knows when you need external legal advice. We do not give legal advice, but we make sure the roadmap doesn't stall on a surprise in month three.
Frequently Asked Questions
Ready for a working day your management team can actually use?
One day, your premises, your management team, our methodology. At the end, an AI roadmap, a pilot choice and a business case. No report, but a decision.
Schedule an exploratory conversation