AI implementation partners face a major obstacle: AI adoption is already happening. It’s fast, ungoverned, and invisible. Shadow AI introduces risks that exceed anything seen in shadow IT, including data leakage, compliance failures, decision integrity risks, and hidden AI‑generated outputs influencing business strategy. An ITAM surgery can help discover AI tools already in use, build governance frameworks to control and drive AI adoption, and help provide clean starting conditions for official AI roll-outs.
1. Map the Full AI Landscape, Including Shadow AI
- What AI tools are already in use.
- Where AI generated outputs exist in workflows.
- Which AI agents or browser-based copilots are accessing sensitive data.
2. Establish AI Governance Foundations to Reduce Data Leakage, Compliance Failure and Legal Risk
- Assesses the client’s maturity against emerging frameworks (e.g., NIST AI RMF).
- Defines rules for safe AI experimentation.
- Establishes a process for evaluating and approving AI tools.
3. Reduce Data Leakage, Compliance Failure and Legal Risk
- Produces a clean inventory of sanctioned vs. unsanctioned tools.
- Identifies high‑risk use cases that must be replaced or integrated.
- Ensures AI partners can deploy their solutions into a controlled, understood environment.
4. Help AI Partners Position Themselves as Strategic
- Identify shadow AI.
- Implement guardrails and AI risk frameworks.
- Gain visibility into where AI interacts with sensitive data.
- Enable innovation without losing control.