AI TrustX™ Engagement Pathway

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PURPOSE

A focused executive assessment that establishes the current position, identifies material exposures, and defines the most practical next step.

BEST SUITED TO

· Leaders beginning or resetting an AI initiative

· Organizations seeking an independent view before further investment

· A specific AI use case, platform, change, or concern requiring rapid orientation

ACTIVITIES

· Leadership and stakeholder discussions

 · Qualitative assessment questionnaire, with response clarification where required.  

· High-level capability, dependency, risk, reported workforce, process, skills, and automation opportunities and value assessment

· Priority findings and next-step calibration

OUTPUTS

· Executive AI Trust Snapshot

· Priority risk and opportunity view

· Indicative AI Trust Scorecard based on questionnaire response

· Recommended Deep Dive, remediation or implementation scope

Typical duration: 1 to 2 weeks 

PURPOSE

A detailed examination of selected capabilities, platforms, use cases, or material changes that require stronger evidence and deeper diagnostic insight.

BEST SUITED TO

· Material AI programs moving towards production or scale

· Underperforming RAG, GenAI or agentic solutions

· Sovereign, private or regulated AI deployments

· Specific governance, data, architecture, resilience or value concerns

ACTIVITIES

· Detailed stakeholder, architecture, process and control review

· Capability and dependency analysis

· Evidence testing and alignment to applicable requirements

· Root-cause, operating-model and technical analysis

OUTPUTS

· Detailed findings and AI Trust Scorecard

· Capability and dependency heatmap

· Prioritized remediation backlog

· Automation, workforce and resourcing recommendations, with benefits assumptions and implementation dependencies. 

· Ownership, architecture and control recommendations

· Investment and implementation roadmap

Typical duration: 3 to 6 weeks

PURPOSE

Translate findings into implemented operating, governance, architectural, and engineering capabilities.  Based on scope, it may include process redesign, workforce mobilization, agent deployment, reskilling, and adoption support. 

TYPICAL SCOPE

· AI operating model, ownership, and decision rights

· Governance, controls, standards, and evidence workflows

· Sovereign or private AI architecture

· Data, knowledge, RAG and ontology foundations

· Coding and automation harness engineering

· Agent architecture, guardrails, evaluation and observability

· Resilience, fallback and incident readiness

OUTPUTS

· Implemented remediation plan

· Operating procedures, controls and ownership model

· Configured or engineered technical components

· Testing, evaluation and validation evidence

   · Defined human and agent responsibilities, mobilized delivery capacity and updated workflows.

· Transition, training and operational handover

Typical duration: 6 to 16 weeks, depending on scope

PURPOSE

Maintain AI trust, value, and resilience as models, data, platforms, vendors, regulations, and business requirements evolve.

TYPICAL ACTIVITIES

· Scheduled assurance and evidence review

· Control, performance, cost, and outcome monitoring

· Material-change assessment

· Incident and continuity readiness

· Backlog reprioritization and improvement planning

· Progressive control automation and code-based enforcement where appropriate

 · Adoption, human and agent performance, skills needs and workforce impact. 

OUTPUTS

· Ongoing assurance view and executive reporting

· Updated scorecard and priority backlog

· Change, incident and improvement recommendations

· Evidence of control operation and business outcomes

 · Capacity released, capacity redeployed, and financial savings realized. 

Delivery model: Monthly or quarterly