Case studies

Illustrative scenarios for governed AI

Fifteen examples of how organizations across industries could approach data and AI work, and how ARCHR would run it.

Illustrative scenario. Based on industry exploration and typical engagement design; not a client result or a guarantee of outcomes.

These are illustrative scenarios across industries, not client results. Each one describes a typical challenge, a sensible way to approach it through Discovery, Pilot, Build and Optimize, the governance questions to settle early, and the qualitative signals a pilot could track. We use scenarios because results depend on each organization's data, systems and rules, and we would rather show our thinking than promise outcomes.

How to read these scenarios

Every scenario follows the same structure: the situation, what the organization wants to achieve, an approach that follows our four phases, technology and governance considerations, and qualitative signals a pilot could track. Each page also includes a simple flow diagram of how data and decisions could move through the solution, and a short list of technology categories that could fit. Cloud options are always AWS, Microsoft Azure or Google Cloud, chosen to fit the organization's existing estate. Regulators named in the scenarios are examples of context from several jurisdictions, not assurance of compliance, and a person stays accountable for every consequential decision.

Financial services

Verification, advice, trading and oversight scenarios for banks, wealth firms, asset managers and fintechs.

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