AI Governance and compliance services

What EY can do for you

AI horizons: pioneering responsible development and deployment

Artificial intelligence (AI) is redefining the competitive business landscape. Responsible AI adoption allows an organization to cultivate confidence in its data, adopting technology and processes that form the infrastructure of an AI ecosystem while protecting proprietary information for an approach that fosters stakeholder confidence and business growth.

The implications for business are profound, the possibilities are limitless, and the risks are real. The explosive growth of generative AI (GenAI) can now channel vast stores of data, collecting, synthesizing and repurposing information in unimagined ways to drive business performance. An organization’s AI inventory of assets – how it’s being used across the enterprise – can be difficult to see, track and align to remain in compliance with rapidly emerging AI regulatory standards and policies.

A responsible AI framework provides visibility into AI across the enterprise and helps manage risks and keep ethical standards like transparency, accountability and fairness at the forefront. Risks can be managed and addressed throughout the life cycle, from the intake of a use case through the deployment and use of an AI asset, including how that AI asset evolves in response to the changing needs of the business.

Reaching your AI potential with EY Teams and ServiceNow

The AI Governance and Compliance Services, developed specifically for the ServiceNow platform, helps businesses establish a connected, end-to-end process for responsible AI, including integrating governance, managing associated risks, driving collaboration across key stakeholders and applying the most current practices for the development, deployment and use of AI systems.

Collaboration advantages:

• Defined risk frameworks for managing and developing AI technologies
• Adherence to cross-channel regulatory compliance based on latest global updates
• Facilitation on the collection of an AI solution inventory
• Visibility into pre-built AI assets, risk profiling, control and policy libraries
• Data controls and models that scale the governance needed to manage risk
• Operationalization of AI through cross-functional stakeholder governance