Why AI Governance is important for better Business Outcomes

Around the world, new use cases for AI are making the headlines, and the regulatory landscape follows suit. As the use of AI expands, so do the potential benefits and risks associated with it. In this novel environment, the success of AI projects is inextricably tied to their trustworthiness. This extends beyond the project scope and, on an organizational level, encompasses governance, risk management, compliance (GRC), product liability, and data standards. 

AI GRC is often viewed as a set of tasks focused on risk management and regulatory compliance. However, its significance goes beyond these aspects, playing a vital role in driving the quality of AI adoption, organizational alignment, and achieving better outcomes guided by trust. As such, AI governance lays the foundation for faster and safer scalability of AI projects within companies and on the market. Accordingly, the importance of implementing trustworthy AI practices to protect businesses, enhance customer trust, and foster holistic value creation for profitable growth cannot be understated.

Operationalizing Trustworthy AI

To achieve trustworthy AI systems at the use case level, organizations need to implement measures that pursue the AI quality objectives throughout a system’s lifecycle and are applied consistently across all use cases within an organization. Through strong and continuous integration into the lifecycle, trustworthy AI practices become self-reinforcing and unleash a positive innovation cycle that serves as the foundation for better business outcomes.

Business Objective: Clearly define the business objective and align AI projects with strategic goals. Adequate funding and the involvement of the right people are essential.

Data Preparation: High-quality data is crucial for AI systems. Ensure data privacy, labeling quality, pipeline development, and evaluation of data quality to enhance the accuracy and reliability of AI models.

Model Development: Assess the complexity of the AI models being developed and adhere to the best software practices to ensure robustness and reliability. Poor development processes can lead to inefficiencies and failures in AI projects, reinforcing the need for robust governance practices.

Deployment & Operation: Ensure the deployment environment meets expectations, detects drift, outliers, and prevents unauthorized updates or intrusions. Address bias throughout the AI lifecycle, promoting objectivity, fair evaluation of training data, and ongoing monitoring.

On an organizational level, best practices at the system level require adequate guidelines, controls, and resources to serve as guardrails for the adoption and implementation of trustworthy AI. This includes quality controls that reflect internal policies on the responsible use of AI and legal requirements that need to be implemented to ensure compliance and risk mitigation for the organization. In addition, employees need to be informed, educated, and trained to enable them to make the right decisions when using, developing, or operating AI systems. 

Core Elements for Effective Governance

With the advent of increasingly complex AI systems, a holistic, end-to-end approach to trustworthy AI is required. PwC offers the expertise necessary to address AI governance challenges effectively and increase AI maturity at all organizational levels.

AI governance tools are an integral part of this approach and vital for providing efficient solutions to companies. These tools support organizations by providing visibility across teams, as well as enabling technical and non-technical stakeholders to collaborate effectively. They help build robust policies, establish collaborative workflows, require objective reviews, and enable agility through governance as a layer for successful strategies. 

Additionally, AI governance tools can offer transparency through a system of record and proactive demonstrations of governance to further strengthen trust and assurance. To provide our clients with best-of-its-kind services, PwC is pursuing an ecosystem approach and is partnering with Monitaur to leverage our collective capabilities. As an AI tool provider, Monitaur offers a solution suite that operationalizes aspects of AI governance, monitoring, performance & bias testing, explainability, and many more essentials to define, manage and automate trustworthy AI in any organization – all in one place. By turning these principles into practice, you achieve better business outcomes with AI while preparing for regulatory requirements. 

The Outlook

Implementing effective AI governance practices is crucial for businesses to ensure trustworthiness, protect their interests, and foster better outcomes. By embracing trustworthy and responsible AI principles, organizations can build customer trust, reduce legal liabilities, and create holistic and continuous value for profitable growth. Collaboration with trusted partners like PwC and leveraging solutions like Monitaur’s can further enhance AI governance efforts. 

Are you interested in learning more about how you can transform your business with AI governance? - Contact us and join our exclusive webinar on 18 July 16:00 to 17:00 CET!