I have spent the last four years building, launching and operating AI products inside enterprise environments — the most recent of those focused on designing agentic AI systems inside complex operational settings across financial services, insurance, energy, telco and iGaming. Environments that don't get a second chance when the system breaks at 9am Monday. This paper is the diagnostic I use before any of that work begins — the set of questions I would ask if you handed me your AI portfolio tomorrow.
Ambiguity, exception frequency, decision complexity, human judgement, variability. Deterministic work should be automated, not agentified.
Structured data quality, document reliability, retrieval readiness, semantic consistency. Raw information is not knowledge.
Governance, access control, auditability, provenance, policy enforcement, human oversight. Trust is what allows scale.
Exception handling, fallback paths, escalation logic, confidence thresholds, human intervention. Production systems must fail safely.
Systems touched, APIs, dependencies, ownership, downstream impact. AI without operational integration is expensive search.
Containment, cycle time, throughput, quality, decision consistency, adoption. No measurable value, no justification.
A diagnostic that can only conclude proceed is a sales tool. One that can conclude stop is consulting. This is the latter.
You are buying time with an operator who has built this category, not a team of analysts producing a deck. The shape of the work reflects that.
I run the assessment personally. No junior consultants, no draft layers, no findings polished into vagueness on the way up. You speak to the person doing the analysis. Every recommendation has my name on it.
I start with executive interviews and workflow walk-throughs before any scoring or framework. Most production risk lives in the gaps between what is documented and what actually happens. I look for those gaps.
You will get a clear view, in writing, on every initiative — including the ones leadership is emotionally attached to. If you want a diagnostic that confirms the existing roadmap, I am the wrong choice.
I currently serve as EVP, GTM Strategy & Insights at Superbo.ai, an enterprise agentic AI platform. This assessment is platform-agnostic by design and may recommend deterministic automation, alternative vendors, or no AI at all. Where a recommendation touches platforms I am commercially involved with, the conflict is disclosed in writing and the client may request an independent second opinion.
I build and deploy enterprise AI for a living. I am EVP of GTM Strategy & Insights at Superbo.ai, where I lead go-to-market across financial services, insurance, healthcare, energy, telco, iGaming and e-commerce.
The pattern that drove me to create this assessment: I keep walking into enterprises with three to fifteen AI initiatives in flight, almost none of which have a realistic path to production — and almost none of which have ever been told so honestly. That is the gap this work fills.
I take on a small number of advisory engagements each year, independent of my Superbo role, where leadership needs an outside voice that has actually shipped this work — not described it from a slide.
— Portfolio-scale or multi-function reviews are scoped individually. If you have more than one function in play, we size the work to the decision in the first call.
Pricing reflects senior-operator time and direct delivery. Travel and on-site days are billed separately at cost. Retainer continuation available post-engagement. Indicative durations assume timely access to stakeholders and source materials — client-side delays are added to the timeline, not the fee.
— Multiple AI initiatives exist but production readiness is unclear.
— Leadership pressure to show practical AI progress is increasing.
— Vendor proposals are running ahead of internal execution readiness.
— Pilots are multiplying without measurable outcomes.
— Governance concerns are slowing decisions to a halt.
— Workflows are operationally complex, regulated, or exception-heavy.
an AI ideation workshop · a vendor selection exercise · a generic AI strategy engagement · a compliance-only review · a technology implementation project.
The challenge is not proving possibility. The challenge is identifying what can actually hold under real operational conditions.
That is the question I help organisations answer — clearly, in writing, with my name on it.