HM
AI Operating Model · Q2 Assessment

Assessment Results

Diagnostic findings across ownership, governance, scaling, decision rights, and execution capability.

Maturity score
31
of 100 · Emerging
Critical gaps
2
ownership, data
High gaps
3
strategy, rights, exec
Required decisions
4
next 60 days

Top 5 gaps

Ranked by impact on AI operating model readiness.

5 active
  1. GAP-01Critical
    No defined AI ownership

    No accountable executive owner for enterprise AI capability.

    18/100
  2. GAP-02Critical
    Fragmented data governance

    Data ownership split across 6 functions; no single source of truth.

    24/100
  3. GAP-03High
    Unclear scaling strategy

    Pilots succeed in isolation but lack a defined path to enterprise scale.

    32/100
  4. GAP-04High
    Decision rights not defined

    RACI for AI investment, model approval, and risk escalation undefined.

    38/100
  5. GAP-05High
    Execution capability gaps

    Insufficient MLOps, change-management, and AI product delivery muscle.

    41/100

Required decisions

Generated from gap analysis.

  • DEC-2050
    Assign AI ownership

    Closes gap #1. Establishes single accountable executive.

    Sponsor · CEOTarget · 30 days
  • DEC-2051
    Approve governance model

    Closes gaps #2 and #4. Defines councils, RACI, and escalation paths.

    Sponsor · COOTarget · 45 days
  • DEC-2052
    Define data ownership

    Closes gap #2. Domain-aligned data product owners with mandate.

    Sponsor · CDOTarget · 60 days
  • DEC-2053
    Approve pilot scaling

    Closes gaps #3 and #5. Funds capability build for production scale.

    Sponsor · CIOTarget · 30 days