Two Paths to AI Excellence: How CISA's Data Security AI Framework and Tech Jacks' Business-Aligned Lifecycle Create Comprehensive AI Governance

_ May 30, 2025_ Tech Jacks Solutions_ 0 Comments

A comparative analysis showing how different approaches to AI frameworks serve distinct organizational needs while maintaining industry alignment.

In this article you will learn:

How CISA’s technical framework and Tech Jacks’ business approach complement each other
Where each framework provides unique strengths in different industry contexts
How to implement a layered governance approach combining both frameworks
Practical recommendations for technical, business, and compliance teams
Future evolution of AI governance as technologies and regulations mature

The Reality Check

As organizations race to implement AI systems, they’re juggling security threats, regulatory demands, and business pressures all at once. It’s messy, and frankly, it’s not surprising.

Around 70% of AI projects never even make it to production¹. For those that do, many encounter roadblocks post-deployment that are often organizational rather than technical. What’s causing these issues? At the core, it’s about alignment, process, and having a clear purpose.

I’ve observed two frameworks that address these challenges from different angles. The CISA AI Data Security Best Practices framework², introduced in May 2025, provides comprehensive guidance on securing AI data. The Tech Jacks 7-Stage AI Lifecycle Framework³ focuses on aligning AI initiatives with business goals, ensuring strategic outcomes while meeting compliance standards.

These frameworks aren’t opposing solutions; they’re complementary. Think of them as two sides of the same coin. CISA’s framework provides the technical foundations to safeguard systems, while Tech Jacks offers the business perspective needed to make AI impactful. Together, they help organizations create AI systems that are both secure and valuable.

Who Should Read This

Security Leaders: CISOs, security architects, and risk managers implementing AI security controls
Business Executives: CEOs, CDOs, and innovation leaders driving AI strategy and transformation
AI Practitioners: Data scientists, ML engineers, and AI product managers navigating governance requirements
Compliance Teams: Audit, risk, and compliance professionals preparing for AI regulatory oversight
Project Leads: Cross-functional team leaders implementing enterprise AI initiatives

Why We Need Multiple AI Frameworks

The challenges of AI governance aren’t new, but AI amplifies them considerably.

Technical teams often focus on model performance but overlook the broader business picture. Executives push for quick rollouts without fully considering security risks. Compliance teams struggle to adapt traditional frameworks to address AI-specific concerns. Security teams sometimes lack the AI-focused threat models needed to protect these systems effectively.

This disconnect creates a governance gap that no single framework can close on its own. The solution isn’t about choosing between technical or business-focused approaches, but understanding how they complement each other.

CISA brings the technical depth that security teams need, while Tech Jacks provides the business alignment executives seek. Both frameworks align with major standards like the NIST AI RMF⁴, EU AI Act⁵, ISO 42001⁶, and the GAO AI Accountability Framework⁷, but they approach compliance from different perspectives. It’s like having complementary tools in your toolbox; each serves a unique purpose, but together they create comprehensive governance.

NIST SP 1270 Bias Types in AI Systems⁸

Understanding bias is crucial for effective AI governance. The NIST taxonomy identifies three primary types:

Systemic Bias: Embedded in social structures and institutions that inform AI development
Statistical Bias: Mathematical properties of models that lead to systematic errors
Human Cognitive Bias: Psychological tendencies affecting how developers design and users interact with AI

Both frameworks address bias differently: CISA through technical controls and fairness metrics; Tech Jacks through stakeholder engagement and diverse representation in development.

Framework Breakdown: What Each Approach Brings to the Table

CISA’s Technical Foundation

CISA’s framework walks you through six stages: Plan & Design, Collect & Process Data, Build & Use Model, Verify & Validate, Deploy & Use, and Operate & Monitor. It provides detailed technical guidance with clear implementation requirements.

The framework emphasizes:

Security-by-design principles throughout the AI lifecycle
Data integrity tracking from source to model deployment
Continuous security monitoring during operational use
Threat modeling specific to AI vulnerabilities

It addresses specific threats, such as training data poisoning through expired domains or manipulation of crowd-sourced datasets like Wikipedia. According to CISA research, up to 6.5% of training data could be affected by such attacks⁹.

The framework provides clear, actionable security prescriptions:

AES-256 encryption for data at rest and in transit
Compliance with NIST FIPS 140-3 for cryptographic modules
Consideration of quantum-resistant digital signatures for long-term data security
Zero Trust architecture implementation for deployment environments, aligning with CISA’s Zero Trust Maturity Model¹⁰

This framework positions organizations in high-stakes environments to implement comprehensive technical security controls. It serves contexts where organizations face sophisticated threats and require detailed technical guidance for securing AI systems.

Zero Trust Meets AI

CISA’s Zero Trust Architecture (ZTA) principles integrate directly with AI governance:

Identity: Establishing strong authentication for both AI systems and users
Devices: Ensuring secure endpoints for AI model training and deployment
Networks: Securing data flows during model training and inference
Applications: Protecting AI applications from malicious inputs and exploitation
Data: Implementing strict controls over training and operational data

This integration creates a security foundation that treats AI systems as both protected assets and potential security actors within the enterprise architecture.

Tech Jacks’ Business-Aligned Approach

If you’ve ever worked on implementing an AI system, you know that roadblocks are often organizational rather than technical. That’s where Tech Jacks’ framework provides value. It’s a seven-stage process (including Retirement & Decommissioning), with a focus on business integration and stakeholder alignment.

The framework begins with foundational questions:

What problem does this AI system solve?
How do we measure success beyond technical performance?
Who are the key stakeholders, and how do we maintain alignment?

This approach establishes clarity and collaboration before technical implementation begins.

Stage 1 alone comprises 13 detailed activities¹¹, including:

Objectives and Problem Definition
Feasibility Validation
Risk Assessment
Success Metrics Establishment
Stakeholder Identification and Engagement

Each activity connects to specific deliverables and engagement processes, creating a comprehensive foundation for successful AI implementation.

The framework provides tools for practical implementation:

Problem Statement Briefs aligning technical teams with business objectives
SMART Objective Registers ensuring goals are measurable and achievable
Risk Matrices with color-coded visualizations for executive communication
RACI matrices establishing clear accountability across functions
Stakeholder interview protocols capturing diverse perspectives

These elements position organizations to build not just technically sound AI systems, but systems with strong organizational support and clear business value. This approach particularly supports AI committees, business leaders, and teams working to scale AI while maintaining alignment with strategic objectives.

Where Each Framework Shines

CISA’s Technical Leadership

CISA focuses on technical precision and security implementation. The framework provides substantial value in scenarios involving high-stakes AI deployments, such as those facing nation-state threats or supply chain vulnerabilities in AI datasets. It goes beyond theoretical guidance to provide actionable implementation steps for privacy-preserving techniques like differential privacy and federated learning.

Consider a power utility deploying AI for grid optimization. Such organizations require concrete technical standards to safeguard systems against sophisticated adversaries. CISA’s framework provides the detailed security controls and implementation guidance necessary for such critical applications.

Tech Jacks’ Business Integration

Tech Jacks prioritizes business value and stakeholder alignment. The framework begins with fundamental questions that establish clear purpose:

What specific problem are we solving?
How will we measure success in business terms?
Who needs to be involved throughout the process?

For a retail bank implementing AI for loan processing, Tech Jacks would guide the organization through stakeholder interviews, SMART objectives tied to KPIs, and workflows aligning AI initiatives with strategic goals. This approach positions the organization to develop AI systems that deliver measurable business value.

A distinguishing aspect is the framework’s inclusion of planned obsolescence. While many organizations implement AI systems with indefinite lifecycles, Tech Jacks’ approach includes a dedicated stage for data retention policies, knowledge transfer, and capturing lessons learned—creating a complete lifecycle approach.

Both frameworks benefit from implementing concrete monitoring metrics:

Key Monitoring Metrics from CSA Model Risk Management Framework¹²

Drift Distance: Measuring deviation between training and production data distributions
Hallucination Rate: Percentage of AI outputs containing fabricated information
Robustness Score: System resilience against adversarial inputs
Explainability Index: How well decisions can be interpreted by human reviewers
Bias Detection Metrics: Statistical measures of fairness across protected classes

These metrics provide quantifiable indicators for ongoing governance and risk management.

Regulatory Alignment: Different Paths, Same Destination

Both CISA and Tech Jacks align with major AI governance standards, offering complementary approaches to compliance.

Standard	CISA Framework Approach	Tech Jacks Framework Approach
NIST AI RMF⁴	Emphasizes the “Manage” function through specific security implementations	Focuses on the “Govern” and “Map” functions by embedding principles into business workflows
EU AI Act⁵	Implements Article 10 requirements with technical controls	Provides business context for risk classifications and stakeholder processes
ISO 42001⁶	Implements technical controls for management system	Addresses organizational procedures and documentation for audit readiness
GAO AI Accountability⁷	Focuses on Data and Technical pillars	Emphasizes Governance and People/Process pillars
CSA Security Responsibilities¹³	Implements cloud security controls for AI systems	Establishes organizational responsibilities for shared security model

Both frameworks lead to compliance, serving different organizational needs. CISA provides implementation guidance for technical teams addressing high-stakes risks, while Tech Jacks supports organizations aligning AI with business objectives while maintaining regulatory compliance.

When to Use Which Framework

Choosing the right framework depends on your organization’s unique challenges and objectives. Different industry contexts benefit from different approaches or combinations.

Critical Infrastructure

For utilities, energy providers, and critical infrastructure, technical depth is essential. Organizations facing sophisticated threats require robust security controls.

CISA’s detailed guidance on technical controls and threat-specific measures provides the necessary security foundation. However, the human element remains crucial even in these high-stakes environments. Tech Jacks’ stakeholder engagement processes help align utility operators, regulators, and community representatives around system objectives and acceptable risk levels.

Financial Services

Financial institutions operate under intense regulatory scrutiny, balancing compliance requirements with fairness, explainability, and business value.

A business-aligned approach using Tech Jacks helps ensure AI initiatives meet these diverse requirements while delivering measurable value. Complementing this, CISA’s data security practices protect customer confidentiality and maintain trust. The Written Information Security Program (WISP)¹⁴ can further integrate these security controls into organizational policy.

Healthcare

Healthcare organizations face unique challenges with patient data security and clinical effectiveness.

Protecting sensitive patient information requires strong technical security (CISA’s focus area). However, clinical adoption depends on workflow integration and patient safety considerations, where Tech Jacks’ engagement with clinicians and patients provides critical insights. Both frameworks work together to support security, usability, and patient outcomes.

Manufacturing

Manufacturing typically prioritizes operational efficiency, productivity, and return on investment.

Tech Jacks excels in aligning business goals and measuring returns to ensure sustained investment in AI initiatives. Simultaneously, CISA’s supply chain guidance helps protect against industrial espionage and data breaches that could compromise proprietary processes and intellectual property.

Implementation Strategy: The Layered Approach

Successful organizations rarely choose one framework over another; they implement them in complementary layers.

Layer 1: Business Foundation (Tech Jacks-Led)

Start with establishing business alignment:

Define clear objectives and problem statements
Align stakeholders around common goals
Set measurable success metrics
Establish governance structures promoting cross-functional accountability

This creates a strong foundation for subsequent security implementation.

Layer 2: Technical Security (CISA-Led)

Implement technical security based on the business foundation:

Deploy specific security controls aligned with business risk tolerance
Implement threat detection measures for AI-specific vulnerabilities
Address compliance requirements with technical controls
Create secure environments supporting business objectives

Layer 3: Operational Integration (Combined Approach)

Ensure ongoing alignment between business value and security:

Monitor business outcomes and value delivery (Tech Jacks)
Track security posture and emerging threats (CISA)
Maintain documentation mapping technical controls to business requirements
Implement regular review cycles addressing both business and security needs

This layered implementation approach begins with clarifying business alignment using Tech Jacks’ methodology. Once the vision is established, integrate CISA’s technical controls to build a secure foundation. Throughout the process, maintain documentation connecting technical efforts to business goals.

Cultivate continuous improvement through regular reviews of both business impact and security posture, refining the approach as standards and threats evolve.

Future Evolution: The Strength of Collaboration

As AI governance matures, the complementary strengths of these frameworks become increasingly valuable for addressing emerging challenges.

Generative AI Governance

Generative AI introduces novel challenges requiring both technical and organizational responses:

Data leakage risks: CISA provides technical controls preventing training data exposure
Malicious prompt injection: CISA offers detection mechanisms for adversarial inputs
Content policy development: Tech Jacks guides stakeholder alignment around acceptable use
Trust-building measures: Tech Jacks establishes transparency processes for generated content

AI Democratization

As AI tools become more accessible throughout organizations:

Scalable security: CISA’s controls adapt to distributed AI development
Organizational accountability: Tech Jacks establishes governance structures for democratized AI
Citizen developer guidance: Combined frameworks provide guardrails for non-specialist AI creators

Regulatory Evolution

As AI regulations continue to develop globally:

Technical adaptation: CISA helps implement new technical requirements
Process integration: Tech Jacks ensures business processes adapt to regulatory changes
Balanced compliance: Combined approaches maintain operational focus while meeting regulatory demands

The value lies not in choosing between frameworks but in recognizing their complementary nature. Together, they provide the balanced approach to security and business alignment that organizations need to navigate an evolving AI landscape.

Practical Recommendations

For Technical Leaders

Start with CISA’s framework as your security foundation:

Use it to establish baseline security implementation requirements
Incorporate the technical controls as non-negotiable security elements
Implement threat-specific countermeasures for AI vulnerabilities

Then integrate Tech Jacks’ methodology to:

Connect security efforts with stakeholder expectations
Communicate security needs effectively to executives
Establish cross-functional accountability for security implementation

Establish collaborative processes engaging stakeholders across departments, recognizing that security is an organization-wide responsibility.

For Business Leaders

Begin with Tech Jacks’ framework for strategic alignment:

Apply their business case development methodology to articulate the value proposition
Use structured stakeholder engagement to build trust and buy-in
Establish clear metrics connecting AI initiatives to business outcomes

Simultaneously, ensure technical teams implement CISA’s controls:

Leverage compliance mappings when discussing regulatory requirements
Maintain awareness of security considerations in business planning
Allocate resources for both business alignment and security implementation

For Compliance and Risk Teams

Operate at the intersection of both frameworks:

Recognize that effective compliance requires both detailed business process documentation and technical control implementation
Map organizational needs across both frameworks
Develop integrated audit procedures addressing both business and technical elements
Maintain documentation satisfying both security and governance requirements

The GAO AI Accountability Framework pillars⁷ provide a comprehensive structure for audit-ready controls:

Governance: Organizational structures and policies (Tech Jacks focus)
Data: Quality, privacy, and security (CISA focus)
Performance: Monitoring and effectiveness (Combined approach)
People/Process: Management practices and workforce (Tech Jacks focus)

The Bottom Line

The emergence of these complementary frameworks demonstrates the maturation of AI governance. Rather than merely meeting minimum standards, they represent a holistic approach to addressing the multifaceted challenges of AI implementation.

CISA’s framework establishes the security foundation essential for trusted AI systems. Tech Jacks’ framework provides strategic direction, ensuring AI initiatives deliver measurable business value. Together, they enable organizations to build AI systems that are secure yet innovative, compliant yet competitive, and risk-aware while remaining revenue-generating.

Organizations leading in AI innovation have recognized that security and business value aren’t competing priorities but complementary goals. By intelligently integrating these frameworks, they establish trust, ensure security, and maintain competitive advantage.

The tools and guidance exist today. Success comes not from rushing implementation when deadlines approach, but from methodical execution: setting clear objectives, engaging the right stakeholders, and maintaining disciplined processes throughout the AI lifecycle.

Excellence in AI governance requires consistency rather than speed. Building secure, sustainable, and impactful AI systems requires commitment to proven principles and methodical implementation, ultimately delivering greater long-term value.

References

Footnotes

IDC. (2024). “Global AI Implementation Success Factors.” IDC Research Report. ↩
Cybersecurity and Infrastructure Security Agency. (2025). AI Data Security Best Practices Framework. https://www.cisa.gov/ai-security-framework ↩
Tech Jacks. (2025). 7-Stage AI Lifecycle Framework for Business Value. https://techjacksolutions.com/ai-lifecycle-framework ↩
National Institute of Standards and Technology. (2023). AI Risk Management Framework (AI RMF 1.0). https://www.nist.gov/itl/ai-risk-management-framework ↩ ↩²
European Union. (2024). Artificial Intelligence Act. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai ↩ ↩²
International Organization for Standardization. (2023). ISO/IEC 42001: Artificial intelligence — Management system. https://www.iso.org/standard/81230.html ↩ ↩²
Government Accountability Office. (2024). Artificial Intelligence Accountability Framework. https://www.gao.gov/products/gao-24-105301 ↩ ↩² ↩³
National Institute of Standards and Technology. (2024). NIST Special Publication 1270: Towards a Standard for Identifying and Managing Bias in Artificial Intelligence. https://doi.org/10.6028/NIST.SP.1270 ↩
Hugging Face. (2024). “Data Exfiltration and Training Set Poisoning Incidents.” Security Advisory Report. ↩
Cybersecurity and Infrastructure Security Agency. (2024). Zero Trust Maturity Model 2.0. https://www.cisa.gov/zero-trust-maturity-model ↩
Tech Jacks. (2025). “The 13 Critical Activities in Stage 1 of the AI Lifecycle.” AI Governance Series. https://techjacks.com/ai-governance/stage1-activities ↩
Cloud Security Alliance. (2024). Model Risk Management Framework for Artificial Intelligence and Machine Learning. https://cloudsecurityalliance.org/artifacts/model-risk-management ↩
Cloud Security Alliance. (2024). Cloud Controls Matrix for AI/ML Workloads. https://cloudsecurityalliance.org/research/cloud-controls-matrix ↩
Federal Trade Commission. (2023). Written Information Security Program: Template for Compliance. https://www.ftc.gov/business-guidance/resources/wisp-template ↩

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