AI Opportunity Assessment
Identify, score and prioritise AI use cases against business value, risk, compliance fit and delivery feasibility — so you fund the bets that will actually pay back.
The problem we solve
Most regulated enterprises don't have an AI delivery problem. They have an AI portfolio problem: dozens of candidate use cases, no shared scoring, fragmented business cases, and an executive committee that cannot decide what to fund first.
The result is predictable — endless PoCs, no production deployments, and a board increasingly sceptical that AI investment is paying back.
The AI Opportunity Assessment fixes that in two to three weeks with a defensible scoring framework, quantified business cases, and a sequencing plan your CFO will accept.
Six scoring dimensions
Every candidate use case is evaluated on the same six axes. No vibes, no vendor narratives.
Business value
Hard cash impact: revenue lift, cost-out, risk reduction. Quantified per use case with sensitivity analysis.
Risk & compliance fit
Mapped against EU AI Act risk tier, DORA ICT-risk implications, GDPR data-handling, NIS2 exposure.
Data readiness
Quality, ownership, lineage, residency. Whether the data you need actually exists in a usable form.
Delivery feasibility
Build vs. buy, time-to-value, internal skills, integration complexity, MLOps maturity required.
Strategic fit
Alignment with enterprise strategy, customer outcomes, and existing platform investments.
Defensibility
Whether the use case is genuinely differentiating or a commodity workflow better served by an off-the-shelf vendor.
What you get
- ✓Use-case longlist (typically 30–80 candidates) gathered from interviews and document review
- ✓Scored shortlist with quantified business case and confidence ranges
- ✓Risk tier classification per use case under EU AI Act / DORA / GDPR
- ✓12-month sequencing plan with quick wins and strategic bets clearly separated
- ✓Build / buy / partner recommendation per use case
- ✓Executive-ready 20–25 page report and a 90-minute walkthrough
Pricing
One business unit · up to 20 use cases · 2 weeks
2–3 business units · up to 40 use cases · 2–3 weeks
Whole organisation · 60+ use cases · 3 weeks
Fixed price quoted after a 30-minute scoping call. No time-and-materials.
Frequently asked questions
How is this different from the AI Readiness assessment?
AI Readiness asks: is your organisation ready to do AI safely? AI Opportunity asks: of all the things you could do, which are worth doing first? Many engagements run them in sequence — opportunity scoping followed by readiness for the top three use cases.
How much does an AI opportunity assessment cost?
Fixed-fee engagements start at €18,000 for a focused single-domain assessment (one business unit, up to 20 use cases). Enterprise-wide assessments covering multiple domains and 60+ use cases typically run €35,000–€55,000. We quote a fixed price after a 30-minute scoping call — no time-and-materials surprises.
How long does it take?
Two to three weeks of elapsed time. Week one: stakeholder interviews and use-case discovery. Week two: scoring, business cases, risk classification. Week three: sequencing, write-up, executive walkthrough. We work in parallel with your team rather than blocking them.
Do you handle implementation after the assessment?
Optional. Roughly 60% of clients move on to a focused implementation engagement; 40% take the report to internal teams or other partners. We have no incentive to inflate the recommendation list — fixed-fee, vendor-neutral.
What if we already have a list of candidate use cases?
Even better — we score what you have rather than restarting discovery, which compresses the engagement to 1.5–2 weeks. This is typical for organisations that have run AI workshops and have a 30-item backlog they cannot prioritise.
How is regulatory fit assessed?
Each use case is mapped to the EU AI Act risk tier (minimal / limited / high / unacceptable), DORA ICT-risk implications if you are a financial entity, GDPR Article 35 DPIA need, and NIS2 sectoral obligations. The report tells you which use cases need formal compliance work-streams before they can move forward.
What criteria matter most when selecting AI infrastructure in regulated industries?
Five criteria, in order: (1) data residency and processing jurisdiction, (2) auditability and evidence pack quality, (3) model lifecycle controls and provenance, (4) deterministic isolation from existing safety-critical workloads, (5) exit and portability — can you leave the vendor without rewriting the platform. Cost matters but is typically a tie-breaker after these five.
How do enterprises manage AI infrastructure under regulatory constraints?
Three common patterns work in regulated industries: (a) sovereign-cloud landing zones with hyperscaler regional services and contractual overlays, (b) dedicated tenancy on EU-headquartered providers like OVHcloud or T-Systems for the most sensitive workloads, and (c) on-premise Kubernetes platforms (OpenShift, vanilla K8s) for workloads that cannot leave the data centre. Most enterprises end up with a hybrid of all three. The opportunity assessment maps each use case to the right pattern.
Stop funding pilots. Start funding outcomes.
A 30-minute scoping call is free. We will tell you whether an opportunity assessment is what you actually need.
Book a Scoping Call