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You have been given a mandate to govern how you will responsibly deliver on your roadmap and strategy for AI technologies:

Develop policies that clarify appropriate use of data and AI models, and limit organizational risk.
Create processes that support the design, development, deployment and operation of AI models.
Identify how you’ll make strategic, tactical, and operational decisions that ensure the use of AI aligns to your organization’s goals and values.

Our Advice

Critical Insight

Most organizations default accountability for AI to IT, or don’t assign accountability at all. Responsible governance requires the business to take accountability for their approach to AI.
Very few organizations have a formal and structured approach to AI governance:
- AI can introduce or intensify risks that affect the entire organization, but most organizations haven’t integrated AI risks in their enterprise risk management framework.
- Most organizations don’t assign accountability for AI or it defaults to the CIO – and yet authority and true accountability remain with the business.
- Policies are published without any controls to monitor and enforce compliance.

Impact and Result

Start to govern AI responsibly by following Info-Tech’s structured approach:
- Identify key risks related to AI.
- Identify a set of responsible AI principles.
- Create an AI governance structure: identify key governing organizations, their mandate, key roles and responsibilities.
- Design an AI governance operating model.
- Evaluate policy gaps using a policy framework.
Use your findings to develop a roadmap and communication plan to govern AI in your organization.

Govern the Use of AI Responsibly With a Fit-for-Purpose Structure Research & Tools

1. Govern the Use of AI Responsibly Deck – A step-by-step document that walks you through how to implement a governance structure for AI for the long term.

Use this deck to build a fit-for-purpose AI governance structure to deliver AI benefits, reduce risk, and ensure compliance.

2. AI Governance and Risk Presentation – A best-of-breed template to help you build a clear, concise and compelling document outlining your AI governance strategy.

A best-of-breed template to help you build a clear, concise and compelling document outlining your AI governance strategy. The key outputs will be:

Proposed AI governance structure
Operating model
Guiding principles
Roadmap

3. AI Governance Assessment Tool – A tool to help you conduct a structured review of your current and target risk governance capabilities.

This self-assessment tool will allow you to conduct a structured review of your current and target risk governance capabilities. The results will inform your governance approach and roadmap.

4. AI Risk Assessment Tool – A tool to help you structure a risk assessment for all of your potential AI risks.

This support tool will help you structure a risk assessment for all of your potential AI risks. The results will inform the outputs in your AI Governance and Risk Presentation.

5. Enterprise AI Governance Committee Charter Example – An example charter for the executive-level Enterprise AI Governance Committee.

This example document will help you get started when defining your AI Governance Committee Charter.

Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.

9.7/10

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$15,469

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CAF - Corporacion Andina de Fomento

Guided Implementation

9/10

$30,549

Natalia has been a great asset in the data, analytics and AI architecture counseling. She's very knowledgable and precise with her advice

Benchmade

Guided Implementation

10/10

N/A

This was an analyst call for AI Governance and I found it very informative. I would like to consider a potential speaking engagement with our Boar... Read More

State Universities Retirement System Of Illinois

Guided Implementation

10/10

N/A

Milena had a clear grasp of the domain and was able to discuss our concerns in earnest.

Workshop: Govern the Use of AI Responsibly With a Fit-for-Purpose Structure

Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.

Module 1: Address Responsible AI and AI Risk

The Purpose

Understand the scope and principles around responsible AI and AI risk.

Key Benefits Achieved

A clear view of principles and risks that will provide a foundation for governance, and operating model choices.

Activities

Outputs

1.1

Document the benefits of AI governance.

List of benefits of AI governance

1.2

Assess your AI risk governance practices.

Assessment of key gaps in AI governance today

1.3

Create an AI risk taxonomy.

Draft of AI risk taxonomy

1.4

Identify relevant AI risks.

A list of key AI risks, aligned to your defined AI risk taxonomy

1.5

(Optional) Conduct an initial AI risk assessment for one use case.

An initial risk assessment for a single AI use case

1.6

Identify risk management objectives, metrics, and targets.

List of risk management objectives, metrics, and targets

1.7

Establish or validate responsible AI guiding principles.

Draft responsible AI principles specific to your organization

Module 2: Define AI Governance Structure

The Purpose

Define the foundation for your AI governance structure.

Key Benefits Achieved

Align the team on the AI governance structure, articulating mandate, roles, responsibilities, and integration points.

Activities

Outputs

2.1

Draft your AI governance structure.

Draft view of AI governance structure

2.2

Define mandates, roles, responsibilities, and membership of AI governance committees.

Updated mandate, role and responsibilities for AI governance committees

2.3

Visualize AI governance position vs. other enterprise governance structures.

AI governance visualization vs. other enterprise governance structures

2.4

Confirm AI governance mandate and membership.

Outline of your new AI governance structure and committees

2.5

Identify integration points between AI governance and other governance structures.

List of points of integration between AI governance and other governance structures

Module 3: Define AI Governance Operating Model

The Purpose

Detail the elements of your AI Governance Operating Model.

Key Benefits Achieved

Enable the organization to apply the right level of AI governance to their initiatives.

Activities

Outputs

3.1

Define the evaluation criteria across the AI lifecycle.

Evaluation criteria for all AI lifecycle steps

3.2

Define core AI governance processes.

Name and description of core AI governance processes

3.3

Compile Executive AI Council Charter.

An initial draft of the AI Council Charter

3.4

Identify and prioritize policy gaps.

A prioritized list of policy gaps to be addressed

3.5

Identify how your AI governance structure will support key policies.

A RACI chart that identifies the roles of different committees in supporting your AI governance initiatives

Module 4: Build an AI Governance Implementation Roadmap

The Purpose

Create an AI governance implementation roadmap.

Key Benefits Achieved

Align the organization on the plans for implementation of AI governance.

Activities

Outputs

4.1

Create your AI governance roadmap.

A completed draft of an AI governance roadmap

4.2

Build your communication plan.

A completed communication plan for the AI governance roadmap

it-Govern-the-Use-of-AI-Responsibly-With-a-Fit-for-Purpose-Structure-Phases 1-4

Govern the Use of AI Responsibly With a Fit-for-Purpose Structure

Enable your organization to transparently deliver effective and human-centric AI.

Analyst Perspective

You can buy an AI solution, but you can't outsource accountability!

AI governance provides a framework for the responsible deployment and use of AI, ensuring alignment with the organization's objectives and values while also adhering to ethical standards and regulatory requirements. It provides a structured approach to managing, monitoring, and controlling the effective and human-centric use and development of AI systems.

AI governance is a subset of enterprise governance, a strategic practice that not only allows the organization to mitigate potential risks but also drives innovation and value creation.

Remember that the AI governance framework and its components are the same whether you're developing your own AI systems or integrating AI tools and technologies with AI built into the tool. Organizations believe that if they adopt a "buy" approach for AI systems, AI governance is not required because they have no control over the technology embedded in the products and systems they acquire. However, this is not the case.

Packaged or integrated AI tools do come with risks, including biases in the AI models, data privacy issues, and the potential for misuse. A robust AI governance framework helps mitigate these risks by establishing guidelines and controls that align with the ethical standards and values of the organization. It promotes transparency and fairness.

Implement AI governance to ensure the investments you make, the risks you accept, and the resources you apply to AI projects are aligned to business value.

A picture of Irina Sedenko

Irina Sedenko
Research Director
Info-Tech Research Group

A picture of Andrew Sharp

Andrew Sharp
Research Director
Info-Tech Research Group

A picture of Swapnil Awasthi

Swapnil Awasthi
Workshop Quality Director
Info-Tech Research Group

Executive Summary

Your Challenge

You have been given a mandate to govern how you will responsibly deliver on your roadmap and strategy for AI technologies. You must:

Develop policies that clarify appropriate use of data and AI models, and limit organizational risk.
Create processes that support the design, development, deployment, and operation of AI models.
Identify how you'll make strategic, tactical, and operational decisions that ensure the use of AI aligns to your organization's goals and values.

Common Obstacles

Very few organizations have a formal and structured approach to AI governance:

AI can introduce or intensify risks that affect the entire organization, but most organizations haven't integrated AI risks in their enterprise risk management framework.
Most organizations don't assign accountability for AI or it defaults to the CIO – and yet authority and true accountability remain with the business.
Policies are published without any controls to monitor and enforce compliance.

Info-Tech's Approach

Start to govern AI responsibly by following Info-Tech's structured approach:

Identify key risks related to AI.
Identify a set of responsible AI principles.
Create an AI governance structure: identify key governing organizations, their mandate, and key roles and responsibilities.
Design an AI governance operating model.
Evaluate policy gaps using a policy framework.

Use your findings to develop a roadmap and communication plan to govern AI in your organization.

Overarching Info-Tech Insight

Whether you're going to market to buy AI-enabled applications, partnering with an integrator, or building models from scratch, you need effective AI governance to ensure you're using the technology in the best interest of the organization. You can buy an AI solution, but you can't outsource accountability.

Session 1: Goals of AI governance
Leverage Info-Tech's AI Governance Framework

Our framework helps guide organizations through the process of formalizing governance to help them meet their goals.

Set goals for the organization related to AI, and monitor progress toward those goals.
Define accountability and responsibility for AI.
Define the AI risk management framework, in line with the existing enterprise risk management framework.
Support the use of AI in a manner consistent with organizational values.
Define a framework to support ML/AI model governance.

An image of Info-Tech’s AI Governance Framework

Take the lead in your AI transformation. Scalable capabilities, strategic alignment, change adoption, governed foundations, and change adoption will help your transformation succeed so you can become the disruptor, not the disrupted.

Govern the Use of AI Responsibly With a Fit-for-Purpose Structure

Info-Tech Insight

Most organizations default accountability for AI to IT, or don't assign accountability at all. Responsible governance requires the business to take accountability for AI.

AI governance is informed by	Your AI governance operating model has the following elements			To implement, you will need to create
Organization Goals	Governance Processes			AI policy framework
Organization Goals	Model Governance	Monitoring	Tools and Technologies	AI policy framework
AI Risks	The operating model is built on a foundation of			AI governance roadmap
AI Risks	Responsible AI guiding principles	Mandates, roles, responsibilities	Governance structure	AI governance roadmap

Info-Tech's methodology for Govern the Use of AI Responsibly With a Fit-for-Purpose Structure

	1. Address Responsible AI and AI Risk	2. Define AI Governance Structure	3. Define AI Governance Operating Model	4. Build an AI Governance Implementation Roadmap
Phase Steps	1.1 Level set on the goals of AI governance, AI risks, and risk management frameworks. 1.2 Assess whether proper AI risk controls are in place. 1.3 Identify AI risk management objectives, metrics, and targets. 1.4 Determine and define responsible AI principles for the organization.	2.1 Identify key elements of the organization's AI governance structure: strategic, tactical, and operational. 2.2 Define mandate, roles, and responsibilities. 2.3 Identify integration points between AI governance and other governance structures.	3.1 Define key AI governance operating model elements. 3.2 Develop first draft of the AI governance charter. 3.3 Recommend AI governance procedure and policy framework.	4.1 Identify AI governance implementation initiatives.
Phase Outcomes	A set of responsible AI principles List of AI risks	AI governance structure AI governance mandates, roles, and responsibilities	AI governance operating model First draft of AI governance policy and procedure framework	AI governance implementation roadmap

1. Address Responsible AI and AI Risk

2. Define AI Governance Structure

3. Define AI Governance Operating Model

4. Build an AI Governance Implementation Roadmap

Phase Steps

1.1 Level set on the goals of AI governance, AI risks, and risk management frameworks.

1.2 Assess whether proper AI risk controls are in place.

1.3 Identify AI risk management objectives, metrics, and targets.

1.4 Determine and define responsible AI principles for the organization.

2.1 Identify key elements of the organization's AI governance structure: strategic, tactical, and operational.

2.2 Define mandate, roles, and responsibilities.

2.3 Identify integration points between AI governance and other governance structures.

3.1 Define key AI governance operating model elements.

3.2 Develop first draft of the AI governance charter.

3.3 Recommend AI governance procedure and policy framework.

4.1 Identify AI governance implementation initiatives.

Phase Outcomes

A set of responsible AI principles
List of AI risks

AI governance structure
AI governance mandates, roles, and responsibilities

AI governance operating model
First draft of AI governance policy and procedure framework

AI governance implementation roadmap

Leverage these supporting tools to inform the key deliverable:

AI Governance Assessment Tool

This self-assessment tool will allow you to conduct a structured review of your current and target risk governance capabilities. The results will inform your governance approach and roadmap.

AI Risk Assessment Tool

This supporting tool will help you structure a risk assessment for critical AI risks.

The results will inform the outputs in your AI Governance and Risk Presentation.

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

“Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.”

Guided Implementation

“Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.”

Workshop

“We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.”

Consulting

“Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”

Diagnostics and consistent frameworks used throughout all four options

	Prework	Session 1	Session 2	Session 3	Session 4
	Review the current AI strategy & governance	Address responsible AI and AI risk	Define AI governance structure	Define AI governance operating model	Build an AI governance implementation roadmap
Attendees	CIO	CIO and direct reports Selected members of the ELT	CIO and direct reports Selected directors and above from business depts	CIO and direct reports	CIO and direct reports
Activities	Understand the organization's current AI governance model. Review existing AI strategy and roadmap. Draw an inventory of applicable legal and regulatory requirements	Level set on the goals of AI governance, AI risks, and risk management frameworks. Assess whether proper AI risk controls are in place (using a standard risk management framework). Identify AI risk management objectives, metrics & targets. Determine and define responsible AI principles for the organization.	Identify key elements of the organization's AI governance structure: strategic, tactical, and operational. Define mandate, roles, and responsibilities. Identify integration points between AI governance and other governance structures, e.g. corporate governance, IT governance, data governance.	Define key AI governance operating model elements and key collaborators. Develop first draft of the AI governance charter. Recommend AI governance procedure and policy framework. Develop a sample procedure and policy outline from the framework.	Identify AI governance implementation initiatives. Develop high-level AI governance implementation roadmap.
Outcomes		Responsible AI principles for the organization List of AI risks	AI governance structure AI governance mandates, roles, and responsibilities	AI governance operating model First draft of AI governance policy and procedure framework	AI governance implementation roadmap

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

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