Accelerate Innovation, Manage Risks, and Scale:

An Introduction to
‍AI Governance

Unlocking the transformational value of Enterprise AI requires effective AI Governance that delivers on business demands while safeguarding the organization from the technology's inherent risks without stifling innovation

The Dual Role of AI Governance in Growth and Risk Mitigation

The goal of effective AI Governance is to accelerate innovation and business growth by 1) increasing the efficiency and efficacy of an organization's AI initiatives and 2) mitigating potential risks with safeguards that help an enterprise enforce policy, regulatory compliance, and ethical standards. AI Governance enables organizations to scale their AI initiatives and operate in a way that is transparent, accountable, robust, safe, fair, compliant, and aligned with societal values such as non-discrimination.

Effective AI Governance will safeguard an organization from AI-related risks, enforce policy and regulatory compliance without stifling innovation, and enable the business to quickly measure and report on governance metrics and key performance indicators (KPIs) related to the risks, performance, health, value, and quantifiable return on investment (ROI) of all AI initiatives across the enterprise. Successfully implementing an AI Governance framework helps organizations deliver responsible AI at scale.

What Is AI Governance?

Artificial Intelligence (AI) Governance is a framework for assigning and assuring organizational accountability, decision rights, risks, policies, and investment decisions for applying AI. In short, AI Governance is asking the right questions and giving the answers to put the right safeguards in place (Source: Gartner). The framework applies to all decision-making models including AI, generative AI (GenAI), Machine Learning (ML), statistical, regression, rules-based, in-house, third-party vendor, open source, and cloud-based. In this context, “AI” is used as a short-hand for the comprehensive list of decision-making models and technology.

In the era of GenAI, traditional governance practices and oversight mechanisms built for software, data, and corporate assets don’t adapt well for supporting AI initiatives. For example, traditional governance may lead to operational bottlenecks that stifle innovation because they can’t keep up with business demands and the inherent risks that AI presents, which may require reviewing constantly changing model outputs that change within a day, hour, or even minute.

This is causing a seismic shift in governance frameworks and means effective AI Governance must be adaptive — meaning it must be dynamic, enterprise-wide, and real-time in order to handle the unique challenges of AI, including explainability. AI Governance leverages best practices and policies to guide the development and use of AI initiatives, ensuring that these technologies can be brought to market efficiently, responsibly, and conform to all ethical principles.

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Why Enterprises Need
AI Governance Software

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Streamlining AI Governance in the Generative AI Era

AI Governance software allows organizations to streamline model operations, provide on-going monitoring of AI initiatives, enforce policy and regulatory compliance consistently, and track the integrity of AI and ML models, data, and digital assets across the entire model lifecycle. Business risk, security risk, regulatory risk, legal risk, and ethical AI concerns will intensify as GenAI solutions grow in power and scope. By 2030, off-the-shelf AI Governance software spend will more than quadruple from 2024, capturing 7% of AI software spend and reaching $15.8 billion (Source: Forrester).

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The Shift from Manual Processes and DIY Systems to Purpose-Built AI Governance Platforms

Historically, enterprises have used manual spreadsheets or developed in-house systems to address burgeoning AI governance needs. But as AI transforms business landscapes, organizations are confronted with the need for robust governance platforms that ensure models are compliant, ethical, secure, and aligned with business objectives. This is especially true for Fortune 500 companies, where the stakes and scale of governance are exponentially higher. For Chief AI Officers, Chief Data and Analytics Officers (CDAOs), and heads of innovation, the decision to buy or build an AI governance platform can shape the speed and success of the company's AI initiatives.

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Hidden Costs of Manual and In-House Solutions

Using manual spreadsheets or building a governance solution in-house might seem practical at first, but the steep cost—both direct and hidden—could derail AI-driven growth and delay returns on AI investments.

Accelerating AI Initiatives with Commercial AI Governance Software

Commercial AI Governance software offers a purpose-built solution that enables Fortune 500 companies to implement a scalable, compliant, and efficient governance framework out of the box. AI Governance software can accelerate your AI journey, minimize AI-related risks, ensure regulatory compliance, and keep teams focused on core-competencies.

Why Effective
‍AI Governance Matters

Generative AI ushered in a new era of AI model development. Recent years have seen a massive increase in AI investment and related innovation. Alongside the growth in AI has come increasing concerns over ethical and responsible AI use.

Today’s Enterprise AI Portfolio

R&D Investment

Makes up a significant part of the enterprise application portfolio

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Growth Opportunities

Are tied to substantial revenue generation initiatives

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Societal Impact

Drives business decisions that can have huge impacts on the lives of customers

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Regulatory Environment

Is evolving at the industry, local, state, federal, and international levels

The Changing AI Landscape

The size of enterprise investments associated with AI use is growing rapidly.

These numbers fail to account for the fury of investments that kicked off late in 2022 following the introduction of ChatGPT.

At the same time, the pervasive use of AI models combined with their potential impact on society is increasingly becoming the concern of regulatory bodies.

$92B

global corporate AI spend in 2021

a sixfold increase over the level of investment seen in 2016

20% to 30%

the number of AI models in the enterprise is increasing by 20 to 30% each year

From Guidance to Regulation

The EU AI Act of 2024 began its life as a set of guidelines released in 2019 by the EU High Level Expert Group on AI. The Act is the world’s first comprehensive legal framework targeting AI use in business. The passage of this Act ushers in a new world of legal regulation specific to AI use.

With so many AI use guidance documents being issued by so many governmental entities around the globe, it seems certain that more governments will follow the path taken in the EU - evolving guidance into AI specific regulations that will have the force of law.

Non-AI specific regulations such as GDPR, HIPAA and PCI are also likely to play a big role in regulating AI use. These regulations focus on sensitive data and data privacy rights. The data intensive nature of AI model building means that there will likely be overlap between data governance and AI governance regulations

Published In Last 5 Years

EU - Artificial Intelligence Act

US - NIST AI Risk Management Framework

US - Executive Order 13960 | Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government

US - California Attorney General AI/ML Governance | Request to all California Healthcare Providers

UK - AI in the UK | Ready, Willing, and Able

Canada - Directive on Automated Decision-Making

Japan - Social Principles of Human-Centric AI

Singapore - Model AI Governance Framework

Australia - AI Ethics Framework

ISO/IEC 42001 - International standard that specifies requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System (AIMS) within organizations

Top AI Governance Challenges

Until recently, within most enterprises, the use of AI has been limited to a small number of applications and related models. In this world, AI governance practices, if they existed at all, meant using spreadsheets to manually keep track of their AI models.

The expected growth in AI use along with the increased interest of governments looking to regulate this space is forcing enterprises to take a fresh look at their ability to deal with comprehensive regulations related to AI use.

Lack of Visibility

Into what is being built, for what purpose, who owns it and whether it conforms to all internal and external requirements

Manual, time-consuming

Efforts associated with ensuring that AI meets internal and external standards

Reactive

Responses to both internal and external inquiries for information related to the portfolio of AI initiatives

Inconsistent

Processes and policy enforcement across teams leading to increased complexity and associated risks

The High Cost of
‍Failed Governance

The risks associated with having an inadequate approach to the governance of AI use can be catastrophic

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Fines and Penalties

Regulations that are being adopted by governmental entities can have significant penalties for incidents of non-compliance

Litigation and Lawsuits

Customers that are negatively impacted or harmed by a business application using AI pose a risk of expensive litigation.

Loss of Reputation

Ungoverned AI model development presents significant risks to brand equity that may have been earned over many years.

Missed Market Opportunities

When the validity and accuracy of AI models is not appropriately proven, organizations risk the failure of major revenue generation or cost reduction initiatives.

Build The Right Governance Framework

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Visibility

Robust inventory management capability to keep track of all essential meta and artifactual data associated for each AI model

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Orchestration

An overarching control function that ensures the continuous and automatic enforcement of all relevant compliance requirement

Transparency

Routine and systematic reporting on AI performance relative to performance, value, security, validity, fairness, and bias

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Automation

Integration of the AI tool chain and tech stack to support the standartization and automation of the compliance process

ModelOp Center

Govern and Scale All Your Enterprise AI Initiatives with ModelOp Center

ModelOp is the leading AI Governance software for enterprises and helps safeguard all AI initiatives — including both traditional and generative AI, whether built in-house or by third-party vendors — without stifling innovation.
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Through automation and integrations, ModelOp empowers enterprises to quickly address the critical governance and scale challenges necessary to protect and fully unlock the transformational value of enterprise AI — resulting in effective and responsible AI systems.