AI & Digitalization Advisory

When companies start with digitization or AI, they often jump straight to “which tool, which system.” But the more important questions are: is the problem real, is it worth the investment, and which approach costs least?

My role is not to sell technology but to help companies think the problem through — from diagnosis and option selection to low-cost validation, building a rational decision path.

A common trap is treating “adopt AI / adopt a system” as the goal, without first defining what to solve, whether it is worth it, and the cost-benefit. The result is often buying tools and launching projects while the real problem persists.

I use a standard method (8 steps): starting from the real problem, move through needs discovery, business diagnosis, problem redefinition, option selection, cost/benefit/risk analysis, MVP/POC, implementation, and review.

Option selection spans Do Nothing / Keep Current / SaaS / Low-Code / Workflow / AI / Custom Dev — no default to AI just because it is advanced; the fit decides.

I have served multiple companies and founders across strategic diagnosis, platform evaluation, AI workflow assessment, and digitalization roadmaps. The work ranges from independent diagnosis and option judgment to direction design — including enterprise-side platform evaluation and helping founding teams clarify structural product, technology, and market issues.

Delivery centers on diagnosis and judgment: diagnostic conclusions, digitization option calls, platform/product evaluations, real diagnostic reports, AI / digitalization direction design, and business-model analysis.