Executive Product

See why the AI journey is stuck before funding another round of theater.

This executive assessment and workshop product helps leadership teams surface the hidden conditions behind AI momentum: value clarity, decision rights, accountability integrity, trust, workflow readiness, and whether experimentation is politically safe enough to learn.

For whom

  • CEOs, CIOs, CDOs, COOs, risk leaders, and transformation sponsors.
  • Organizations that have AI energy but uneven executive alignment.
  • Leadership teams that need a usable next move, not another maturity score alone.

Purpose

Identify where the executive system is helping AI move or quietly blocking it: unclear ownership, credit without downside, workflow resistance, low trust, or fear disguised as prudence.

Outcome

Produce a concrete leadership recommendation: what to stop, what to fix first, and what to scale next, including a portfolio posture for the next set of AI use cases.

Executive Session

Each leader completes a short confidential assessment. The resulting synthesis surfaces disagreement, accountability gaps, adoption risk, and the conditions required for value realization.

Workshop with Dr. Michael Proksch

Dr. Proksch uses the findings to lead a focused executive workshop that resolves ownership seams, sharpens portfolio direction, and defines the next operating moves.

What leaders receive

1 Responsibility-accountability gap analysis showing where visibility is separated from downside ownership.
2 Executive alignment analytics highlighting where leaders disagree most on AI direction and operating reality.
3 Use-case portfolio direction: scale now, pilot with guardrails, fix accountability first, or pause and rebuild conditions.
4 A session design for the executive workshop: the tensions to resolve, the decisions to make, and the next 30-90 day moves.

Indirect diagnostics

The assessment avoids self-labeling questions. Instead, it measures observable operating behavior: who stays attached when outcomes slip, how risk decisions are made, whether people can challenge AI outputs, and whether experimentation carries career risk.

Portfolio guidance

The product does not stop at maturity language. It translates the executive signals into portfolio implications: where to concentrate, where to slow down, and which conditions must be repaired before scaling more AI work.