Turning a technology decision into a business decision

The AI Decision Framework™ (AIDF) is a proprietary methodology that enables organizations to make informed decisions about their artificial intelligence investments.

Unlike traditional approaches that seek only to answer the question “Build or Buy?”, the QBADF™ treats artificial intelligence as a strategic asset to be evaluated against technological, financial, human, operational, regulatory, and competitive criteria.

The goal: recommend the best decision, through the 10 pillars of the AIDF™

1. Business Alignment

Does the AI truly serve a strategic objective?

Evaluation of:

• Corporate vision
• Strategic priorities
• Desired competitive advantage
• Value creation
• Business case
• Success indicators

Deliverable: Business AI Alignment Score

2. Organizational Readiness

Is the organization ready?

Evaluation of:

• Organizational culture
• Governance
• Digital maturity
• Leadership
• Change management
• Resource availability

Deliverable: AI Readiness Index

3. Data & Knowledge Readiness

Is the data usable?

Evaluation of:

• Document quality
• Taxonomies
• Metadata
• Knowledge structuring
• Duplication
• Sensitive data
• Document governance

Deliverable: Knowledge Readiness Score (entry point to the QKS)

4. Architecture & Technology

Is the architecture sustainable?

Analysis of:

• Cloud
• On-premise
• Hybrid
• APIs
• Integrations
• Interoperability
• Scalability
• Performance
• Observability

Deliverable: Technology Sustainability Index

5. Cybersecurity & Sovereignty

What are the risks?

Evaluation of:

• Zero Trust
• IAM
• Encryption
• Sovereignty
• Data residency
• Resilience
• Exfiltration protection
• Post-quantum readiness

Deliverable: Cyber Trust Score by the Q-Carbon service

6. AI Governance

Can the AI be governed?

Analysis of:

• Traceability
• Explainability
• Auditability
• Model management
• Versioning
• Human oversight
• Bias management
• Model lifecycle

Deliverable: Responsible AI Index

7. Financial Sustainability

Is the project economically viable?

Complete analysis:

• CAPEX
• OPEX
• TCO
• ROI
• Operating costs
• Maintenance costs
• Technical debt
• Licensing costs
• Model costs

Deliverable: AI Financial Sustainability Score

8. Vendor Dependency Assessment

How dependent will you become?

Analysis of:

• Vendor lock-in
• Reversibility
• Portability
• Open standards
• Intellectual property
• Migration options

Deliverable: Vendor Independence Index

9. Decision Matrix

Building on the eight preceding analyses, the QBADF™ objectively evaluates the different possible approaches:

• Build
• Buy
• Partnership
• Open Source
• Hybrid
• Private AI
• Sovereign AI
• Progressive development

Each scenario receives an objective score. The client understands why an approach is recommended.

10. Executive Roadmap

The final deliverable, which includes:

• 12-month roadmap
• 3-year vision
• 5-year vision
• Target architecture
• Priorities
• Risks
• Recommended budget
• Phases
• Expected gains
• Recommended governance

The five maturity levels

1. Reactive → AI is experimental.
2. Emerging → A few pilot projects.
3. Operational → AI delivers value.
4. Strategic → AI becomes a competitive lever.
5. Transformational → The business operates as an AI-First organization.

The Quantum Beyond AI Decision Framework™ deliverables:

• Executive report
• Complete assessment
• Risk dashboard
• Build vs Buy vs Hybrid matrix
• Financial analysis
• Ten-pillar scorecard
• Dependency mapping
• Target architecture
• Executive roadmap
• Investment prioritization
• Strategic committee recommendations

The Quantum Beyond philosophy

The AI Decision Framework™ is not about selling a technology. It is about protecting its clients' investments.

A good decision is not the one that costs the least today, but the one that will still allow the organization to be competitive, secure, and sovereign five or ten years from now.