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Getting Started with AI and Enterprise Agents

All research

Plain-language briefings and whitepapers for finance and technology leaders approaching AI and enterprise agents for the first time. Each one introduces the concepts and the decisions behind a deployment that delivers, and points to the deeper research where the engineering is treated in full.

Who this is for

These briefings are for finance and technology leaders meeting enterprise AI for the first time, usually because someone above them has asked for a plan. They assume no engineering background and they sell nothing.

The sequence follows the order the questions actually arrive. Where to start when the board has mandated AI and nobody has scoped it. How to run a first pilot, what to ask a vendor, and what the economics have to prove before it scales. Who should own AI delivery, which splits into four responsibilities that no single function holds. How to go from one working agent to many without multiplying cost and risk. Whether your agent needs a semantic layer, and the one test that answers it.

Each briefing introduces the concepts and the decisions in plain language, then points at the deeper research where the engineering is treated in full. Start here if you are early. The rest of the library assumes you already have.

Briefings & Whitepapers

Start here. These pieces are the on-ramp to the rest of the library.

  1. 01 Your Board Wants AI. Where Do You Start? Turning a board mandate into a deliverable program: the architect the work turns on, how to validate, where to begin, and how to scale by function.
  2. 02 Implementing Your First AI Agent Pilot The five questions to ask a vendor, the pitfalls that sink most deployments, the economics a pilot has to prove, and how to tell when a pilot is ready to scale.
  3. 03 Is AI Part of IT? Why AI delivery splits into four responsibilities with four owners, why no single function holds them all, and where the capability should sit. A whitepaper on ownership.
  4. 04 I Have Working AI Agents. What Do I Do Next? Going from one working agent to many without multiplying cost and risk: learning from a few dissimilar pilots, when the data foundation pays off, make it right then make it fast, and why orchestration decides the economics. A whitepaper on scaling.
  5. 05 Does Your AI Agent Need a Semantic Layer? What a semantic layer actually is, the one test for whether your agent needs one, and why a governed metrics catalog is not the same thing in finance. A whitepaper on grounding agents in business meaning.

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