Why AI governance is good for the bottom line

‍Written by Veera Siivonen, CCO and Co-Founder of Saidot.

AI tools can unlock significant business value, enabling people and companies to become more efficient, productive, and innovative. So, how can that value be harnessed? The answer is AI governance. It is how to ensure your AI is safe, ethical, transparent, and performs as it should—at a high quality. 

McKinsey and Accenture reports both argue that AI governance and responsible AI are good for business:

Higher bottom-line impact: According to McKinsey's State of AI research published in March 2025, the CEO's oversight of AI governance, policies, processes, and technology necessary to develop and deploy AI systems responsibly is one element most correlated with higher self-reported bottom-line impact from an organisation's use of generative AI.

Key revenue growth contributor: Accenture's December 2024 report, Responsible AI: From compliance to confidence, revealed that 49% of companies view responsible AI as a key contributor to their AI-related revenue growth. They also predicted that when a company becomes a pioneer in responsible AI, its AI-related revenue will increase, on average, by 18 percent.

So, it's not surprising that 42% of companies have already devoted more than 10% of their overall AI budget to responsible AI initiatives, and 79% plan to hit this spending target over the next two years (Accenture, Dec 2024).

Next, I'll share four reasons AI governance is good for the bottom line.‍

1. AI governance unlocks better-quality AI products and experiences

AI governance isn't just about compliance—it's a strategic approach that leads to higher-quality AI products and experiences. Companies embedding responsible AI governance practices expect tangible business outcomes: 

Improvements in product quality and shortened development cycles: According to joint research by Accenture and AWS (Nov, 2024) 70% of executives expect strong improvements in product quality and 67% expect improvements in process industrialisation or shortened development cycles.

Enhanced customer loyalty and satisfaction: Executives anticipate a 25% increase in customer loyalty and satisfaction from responsibly developed AI products and services. (Accenture & AWS, Nov. 2024)

Brand impact: 78% of companies believe that communicating their responsible AI efforts will improve brand perception significantly (Accenture & AWS, Nov. 2024).

Competitive differentiation: PwC's 2024 survey on US responsible AI reveals that competitive differentiation (46%) is the primary outcome companies attribute directly to responsible AI practices.

By embedding responsible AI practices into product development, companies significantly enhance product quality, customer experiences, and overall competitive advantage, ultimately boosting their bottom line. 

2. AI governance helps to avoid big fines for non-compliance

The EU AI Act aims to ensure AI's safe, ethical, and trustworthy development and use. Steep fines are involved for not complying with its rules: 

Non-compliance with prohibited AI practices: Up to 35 million euros or 7% of global annual turnover

Non-compliance with AI Act's obligations: Up to 15 million euros or 3% of global annual turnover

Supplying incorrect, incomplete or misleading information: Up to 7.5 million euros or 1.5% of global annual turnover

This is a significant financial risk. And if compliance preparations start only when AI systems are already far in their implementation, compliance might require substantial changes to the systems, causing double work on development. 

Organisations can avoid unexpected costs by building and adopting AI systems with AI Act compliance in mind.  

The AI Act came into force on 1 August 2024, and most penalties apply on 1 August 2026. Below, you can see when the rules of the AI Act apply. 

3. AI governance helps to avoid risks

AI-related risks are a major concern: 56% of Fortune 500 companies cite AI as a "risk factor" in their annual reports, up from just 9% a year ago (Accenture & AWS, Nov. 2024).

Risks are also slowing down scaling of AI: 74% of companies temporarily paused AI projects this past year due to risks (Accenture & AWS, Nov. 2024).

According to the Accenture Stanford Executive Survey (Dec. 2024), the top AI-related risks company executives see include, for example: 

Privacy and data governance-related risks (a concern for 51% of executives)

Security (47%)

Reliability risks such as output errors, hallucinations and model failure (45%)

Transparency and the challenge of "black box" models (44%)

Although only 26% of executives are concerned about reputational harm, all the above risks could damage both the brand and the business. 

Having AI governance in place on time can help build and foster trust with stakeholders and (potential) clients. In the AI era, following responsible AI practices, managing AI risks, and being transparent about AI are essential in establishing and maintaining trust. 

In IBM's 2024 CEO Study, 71% of CEOs say establishing and maintaining customer trust will have a greater impact on their organisation's success than any specific product or service.  

It comes as no surprise that many organisations are ramping up mitigations for generative AI's risks. McKinsey's State of AI report also finds that companies are more likely in 2025 than in early 2024 to say they are actively managing risks related to inaccuracy, cyber security, and intellectual property infringement. 

4. AI governance is a must for employee trust

Responsible use of AI also helps in getting the personnel onboard in AI transformation: 82% of organisations believe that a mature approach to responsible AI will improve employee trust in AI adoption (Accenture & AWS, Nov. 2024).

In addition, responsible AI helps both in recruitment and retention: companies expect a 20% improvement in time-to-hire, a 21% increase in the quality of recruits and a 21% boost in talent retention with responsible AI (Accenture & AWS, Nov. 2024).

If companies use AI responsibly, they can give a good impression to future and current top talent. When AI tools work as they're supposed to, employees can do their jobs more efficiently and become more productive.  

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AI Governance Handbook: Your guide for scaling AI responsibly 

As AI adoption accelerates, so does the need for robust governance to ensure risk management, compliance, and ethical use. There is no one-size-fits-all approach; each organisation must shape its governance practices to align with its unique goals, risks, and regulatory landscape.  

Our AI Governance Handbook is designed to guide you—whether you're a Chief Data Officer, AI lead, legal counsel, or business leader—on the journey of AI governance. 

This handbook offers you insights to help you scale AI responsibly, keeping risks under control, avoiding fines for non-compliance, and maintaining your customers' trust. 

Why AI governance is good for the bottom line

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