Most companies skip the readiness question — then wonder why the initiative failed. The Blind Spot isn't a technology gap. It's an awareness gap. Your data pipelines, your team's skills, your infrastructure, your processes — any one of them can silently kill a six-figure AI investment. I've assessed AI maturity at Renault-Nissan across 39 countries. I've evaluated 30+ startups at Berkeley SkyDeck. The pattern is always the same: companies that assess first ship faster, spend less, and avoid the 87% failure rate. This 2-3 week sprint gives you the clarity to invest with confidence — or the courage to say 'not yet.'
Your leadership team assumes AI readiness means having budget approval. Budget is necessary. It's not sufficient. The Blind Spot hides in the gap between willingness and capability.
Your data exists in 14 different systems. Nobody owns the integration. The AI vendor says 'just connect to your data lake.' You don't have a data lake. You have a data swamp.
Your IT team manages infrastructure. They've never deployed a model. They've never monitored inference latency. They don't know what a feature store is. That's not a failing — it's a training gap.
Your competitors announced AI initiatives. Your board wants one too. But nobody has asked: which processes actually benefit from AI? Which ones are better solved with a spreadsheet?
You had an AI pilot last year. It worked in the lab. It never made it to production. Nobody documented why. The Blind Spot ensures you repeat the same mistakes.
A focused 2-3 week assessment that maps your actual readiness across five dimensions. No vendor bias. No theory. Just an honest snapshot of where you stand.
Audit your compute, storage, networking, and deployment infrastructure against AI workload requirements. Identify gaps between what you have and what AI needs.
Assess data quality, accessibility, governance, and pipeline reliability across your key systems. Data is the foundation — if it's broken, nothing built on top works.
Map your team's current skills against the roles AI initiatives require. Identify training needs, hiring gaps, and where external support makes sense.
Score potential AI applications by business impact, technical feasibility, and data availability. Separate real opportunities from AI theater.
Developed from assessing AI maturity across 39 countries at Renault-Nissan and 30+ startups at Berkeley SkyDeck. READY gives you a structured, repeatable way to answer the question every leadership team should ask before spending a euro on AI.
You're a leadership team at a €10M+ company considering a significant AI investment. You want honest answers about whether your organization is ready — not a vendor telling you what you want to hear. You'd rather spend 2-3 weeks on assessment than 12 months on a failed initiative.
Five dimensions: infrastructure capability (can your systems handle AI workloads?), data maturity (is your data accessible, clean, and governed?), team skills (do you have the right people or a plan to get them?), organizational culture (will your teams actually adopt AI tools?), and use case clarity (do you know which problems AI should solve?). Each dimension gets a 1-5 score with specific evidence and improvement actions.
A vendor assessment answers 'can you use our product?' This answers 'should you invest in AI at all, and if so, where?' I have zero vendor partnerships. I don't sell AI products. My job is to give you the truth about your starting position — even if that truth is 'you're not ready yet.' A vendor will never tell you that.
Then the assessment just saved you €500K and 12 months. 'Not ready' isn't a verdict — it's a starting point. The readiness roadmap shows exactly what to fix and in what order. Some gaps close in weeks (data access policies). Others take months (hiring ML engineers). Knowing the timeline prevents the most expensive mistake: starting AI before your foundation is set.
2-3 weeks from kickoff to final report. Week 1: stakeholder interviews, infrastructure audit, data quality sampling. Week 2: analysis, scoring, roadmap development. Week 3 (if needed): presentation to leadership and Q&A. You'll have your readiness score and action plan in 15 business days.
Five deliverables: (1) AI Maturity Scorecard with 25 indicators scored 1-5, (2) Data Readiness Report per system, (3) Team Skills Assessment with gap analysis, (4) Use Case Prioritization Matrix, and (5) 12-Month Readiness Roadmap. Everything is actionable. No 200-page reports. No vague recommendations like 'invest in data culture.' Specific actions, specific owners, specific timelines.
Let's discuss how this service can address your specific challenges and drive real results.