AI Center of Excellence
AI governance for organizations that can't afford to guess.
Most Salesforce orgs are adding AI before they're ready. The problems don't show up in the demo. They show up in production, in audit, and in board meetings. CCC's AI CoE practice builds the governance layer before the AI layer.
74% of nonprofits are using AI. Formal governance still lags.
Adoption alone does not establish readiness. Wrong donor data can distort predictions, generated grant language can contradict program reality, and automated outreach can bypass consent records.
These are foreseeable failure patterns when AI is deployed on weak data, access, documentation, and review controls.
AI adoption is not the same as AI readiness. Governance should define data ownership, access boundaries, human review, and incident response before production.
Three tools. One principle: clean data first, AI second.
AI Readiness Scorecard
15 questions. Five categories. A weighted score in under 2 minutes. Evaluates Data Quality, Governance Readiness, Automation Maturity, AI Preparedness, and Documentation Health.
Take the ScorecardHuman Validation Framework
Human review gates before AI outputs reach production. Defines who reviews, what escalation looks like, and how overrides get recorded. No handwave governance, no checkbox compliance.
Request an AssessmentAI Decision Log
A Salesforce-native custom object designed to record defined AI-assisted decisions, confidence scores, human review status, and override history. It supports audit, compliance, and board reporting when included in the approved implementation scope.
Request an AssessmentBuilt for organizations where AI errors have real consequences.
Nonprofit
Donor data, grant reporting, and constituent outreach all carry trust obligations. AI without governance is a compliance and reputational risk, not just a technical one.
Government
OMB M-25-21 governs federal AI use and public trust, while M-25-22 addresses AI acquisition. GovCloud implementations need governance documentation that holds up to audit.
Healthcare
Patient data, clinical workflows, and billing systems are high-stakes. AI outputs touching these areas require human review gates and documented override protocols.
Enterprise
Large orgs with multiple Salesforce clouds and AI features activated across business units need a governance layer that works at scale, not just in a single sandbox.
- NIST AI RMF AI Risk Management Framework
- ISO 42001 AI Management Systems Standard
- Salesforce Trusted AI Einstein Trust Layer Principles
- OECD AI Principles on Artificial Intelligence
- EU AI Act High-Risk System Requirements
CCC's Six Salesforce AI Governance Gates, Mapped to NIST AI RMF.
The NIST AI RMF functions are adaptable governance functions, not a mandatory linear checklist. CCC maps them to six Salesforce delivery gates for operational use.
01
NIST: MAPData Readiness
Data quality score of 7 of 10 or higher on the 10-metric SOQL audit. Sharing model documented. Data ownership confirmed.
Pass/Fail Gate02
NIST: GOVERNPermission and Access
Field-level security verified on every object the agent touches. Trust Layer configured. Integration user scoped to least privilege.
Pass/Fail Gate03
NIST: MAP + GOVERNDesign Review
Use case risk classified. Human oversight defined. Four-audience documentation drafted. Accountability assigned.
Pass/Fail Gate04
NIST: GOVERN + MAPAgentic Governance Review
Agent action boundaries documented and tested. Session Tracing enabled. Topic restrictions and tool authorization scoped.
Pass/Fail Gate05
NIST: MEASUREPre-Production Validation
Bias and fairness testing on a representative sample. Rollback drill executed in a Full sandbox. Pilot testing with named reviewers.
Pass/Fail Gate06
NIST: MANAGEPost-Launch Governance
30-day review scheduled. Drift indicators baselined. Incident response runbook published. Quarterly review cadence committed.
Pass/Fail GateSix gates. Fifteen cells. One operational reference.
The gates above are six checkpoints mapped to NIST AI RMF. The full practice has fifteen cells across three layers and seven roles. Click any cell to see the deliverable, the named owner, and the cited source. Built as a working reference for scoping calls.
See the Full Practice MapGovernance Scenario
Illustrative healthcare AI governance scenario.
Consider a Service Cloud org where AI-generated case summaries reach agents without defined human review or override records. A billing discrepancy could become difficult to trace when the recommendation, approval, and exception path are not documented.
A governance response would define review gates, record approval and override decisions, and document escalation paths before expanding the use case.
Fixed-scope engagements. No hourly surprises.
Every engagement is scoped before it starts. You know the deliverable, the timeline, and the cost before signing.
| Service | What's Included | Who It's For | Investment |
|---|---|---|---|
| AI Readiness Scorecard | Free self-assessment, five-category weighted report | Any org exploring AI | Free |
| Governance Assessment | Scored audit across NIST AI RMF, gap report, priority roadmap | Orgs pre-Agentforce or post-Einstein activation | $8,000 |
| AI CoE Setup | Human Validation Framework, AI Decision Log, governance documentation, training | Orgs ready to build governance infrastructure | $18,000 |
| Agentforce Governance | Agent scope review, guardrails configuration, escalation design, audit trail | Orgs deploying or evaluating Agentforce | Custom scoped |
| Data Quality Baseline | Field completeness audit, deduplication, standardization, documentation | Orgs with data quality gaps blocking AI adoption | Custom scoped |
| Board-Ready AI Report | Executive summary of AI usage, risks, governance status, and recommendations | Orgs needing to report AI activity to leadership | $3,500 |
| Governance Training | Half-day workshop for admin and technical teams on governance principles and tools | Teams being handed AI tools without training | $2,500 |
All engagements include a scoping document before work begins. No retainers. No surprises.