Every AI programme Auron runs starts the same way: with the right question.
The question is deceptively simple: where does AI actually create value, aligned to what this organisation is trying to achieve?
Answering it first is what lets copilots, agents and governance deliver at enterprise scale, which is where the real return sits. It also shows the board what each investment is meant to return before the money is spent.
The answer comes from a clear framework for where to invest and in what sequence.
Two axes, not one programme
At Auron Advisory we think about AI adoption on two axes. Understanding the distinction is the first step to sequencing correctly.
Empowers every employee using tools the company already licenses. The goal is broad productivity — not deep transformation.
Embeds AI into 2–3 high-impact core workflows where the organisation can build a durable edge.
Auron sequences the two deliberately. Horizontal AI comes first, so adoption is under way before the first vertical use case goes live. Horizontal AI builds the muscle; Vertical AI builds the advantage.
Horizontal AI: activate what you already own
Horizontal AI starts with the tools the organisation already licenses. Auron activates them across every function in week one, so productivity gains arrive while the vertical use cases are still being scored.
The vehicle that makes this work at scale is a prompt library: a curated, co-created set of prompts that bridges the gap between a tool sitting in the toolbar and an employee actually using it. One prompt champion per function. Deployed in week one. Built with the teams, not for them.
Four prompt categories that work across every department immediately:
Beyond the general library, the highest-value prompts are function-specific. Finance needs variance narratives, board commentary, and audit responses. Procurement needs RFP generation and contract redlines. Customer service needs ticket responses and escalation summaries. Each function gets its own prompt set, built with that team's language and context, so it fits the way that team already works.
Vertical AI: where competitive advantage is built
Horizontal AI is a productivity play. Vertical AI is a strategy play. It's where you embed AI deeply enough into a core workflow that the capability becomes a structural advantage — one that compounds over time and is difficult to replicate.
Vertical AI pays back when the right use cases are chosen, so Auron makes that choice systematic and evidence based.
Auron runs a structured three-step process:
The 5 scoring criteria
Not all AI use cases are equal. Before committing resources, every candidate goes through this scoring framework. The weights reflect the reality of delivering AI in a regulated financial services environment:
| Criterion | What we look at | Weight |
|---|---|---|
| Business value | Cost savings, FTE hours recovered, error reduction | 30% |
| Technical feasibility | Data quality, SAP/Salesforce integration, build vs buy | 25% |
| Regulatory risk | FINMA, EU AI Act, Swiss nDSG — eliminative gate | 25% |
| Organisational readiness | Named sponsor, team capacity, change appetite | 10% |
| Time to value | Weeks to pilot, dependencies, quick win potential | 10% |
The regulatory criterion is an eliminative gate, not just a score. A use case that scores 100 on every other dimension but creates material FINMA or EU AI Act exposure does not make the shortlist. Building that discipline into the scoring process — rather than treating compliance as a later-stage concern — is one of the highest-leverage things a programme can do in weeks 1–3.
"Auron puts adoption discipline ahead of experimentation. Every use case has a named owner, accountable for making it land."
The framework is deliberately simple and runs on data most organisations already hold. Auron applies it in the first three weeks, so the programme starts from evidence.
Start with the right question. Sequence the axes correctly. Score use cases on what matters. Spending the first three weeks this way is what makes the delivery work faster and more predictable.