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Independent advisory · Idaho

Adopt AI across cloud and on-premises without losing control of identity and data.

Lencioni & Associates advises mid-market organizations of 500–3,000 users on hybrid AI adoption: which workloads belong in a vendor’s cloud, which belong on hardware you own, and how one identity-centric access model governs both. The security work is the strategy, not a review step at the end.

Built for
Mid-market organizations of 500–3,000 users
Environment
Hybrid cloud and on-premises
Anchored in
Identity-centric Zero Trust security

Who we help

Three people, usually in the same room.

At 500 to 3,000 users there is no dedicated AI function and rarely a standalone security org. The same small group carries the decision, so the work has to answer to all three of them at once.

  • IT and infrastructure leaders

    You run a hybrid estate — a cloud productivity suite alongside systems that are not moving — with a team that is already fully committed. You need an AI plan that does not assume a platform team you do not have.

  • Security and compliance leads

    You are being asked to approve AI tools faster than you can evaluate them. You need a repeatable review path, a defensible data boundary, and access controls that still hold when a model acts for a user.

  • Executives sponsoring an AI initiative

    You have committed to an AI program and it needs to produce something durable. You want an independent read on sequencing, cost and risk before a vendor selection quietly narrows your options.

What we do

Four engagements, one throughline.

Each one can stand alone. Run in order they compound, because every later decision — where a model runs, which data it reaches, who may invoke it — resolves back to identity.

How an engagement runs

Four steps, and a defined end to each one.

No open-ended retainer. Every step has a written output your team can act on without us in the room.

  1. Discover

    Interviews and environment review: where data lives, how identity is managed today, and which AI tools are already in use — sanctioned or not.

  2. Assess

    Findings measured against a defined baseline. Gaps ranked by exposure and effort, with the ones actually blocking AI adoption called out.

  3. Design

    The target architecture and access model, written to be implemented by your team: reference architecture, policy set and a phased plan.

  4. Enable

    We stay through the first phase — configuration review, rollout support and handover documentation — and then step back out.

Selected work

Identity was the smallest change on the list, and the one that unblocked everything else.

A de-identified account of a mid-market organization that brought AI workloads into a hybrid estate while consolidating identity and tightening access at the same time — what was decided, in what order, and which sequencing mistakes were avoidable. Full write-up in preparation.
Read the case study

Start with an assessment, not a tool selection.

The AI Readiness Assessment gives you a documented picture of your environment, your gaps and your sequencing, independent of any vendor. It is also the cleanest way to find out whether this practice is useful to you.