Streamline AI governance with AWS and IBM

Artificial intelligence (AI) has become a driving force in business, reshaping how organizations everywhere operate. As AI’s influence grows, however, so does the need for strong governance.

Companies must mitigate the ethical and social risks of AI, navigate complex and evolving regulations, and prevent operational and security failures. Without robust governance, they risk deploying AI that could erode public trust, cause reputational damage or financial penalties, and result in security vulnerabilities and cyberattacks. Today, business leaders play a pivotal role in driving the conversation around AI governance.

In highly regulated industries such as financial services and healthcare, the stakes are even higher. To remain agile, organizations must balance innovation with compliance — and manage risks — while adapting to constantly changing AI regulations and standards.

To address these challenges, companies need to take a structured governance approach that supports the development, deployment, and monitoring of AI models, and conforms with regulations, internal policies, and standard practices.

The SageMaker and watsonx.governance partnership

Amazon Web Services (AWS) and IBM have partnered to provide an AI governance integrated service that helps organizations scale and streamline AI, build responsible AI products, and meet business, regulatory, and compliance obligations .

The integration of IBM’s watsonx.governance platform — which helps organization manage, monitor, and govern AI models — with Amazon SageMaker, a machine learning (ML) service to build, train, and deploy ML models, enables users to automate risk management and regulatory compliance for their AI/ML models and use cases.

This integrated offering provides several benefits. Organizations can catalog, govern, and monitor AI models throughout the AI life cycle, including mapping policies, metrics, and models using a centralized console to organize, document, and maintain an enterprise-wide view of their AI inventory. Users can also proactively identify and manage risk by automating workflows to ensure accountability and ownership of controls associated with the risks. In addition, this offering manages AI for safety and transparency alongside its regulatory library. This helps to translate external AI regulations into enforceable policies for automated enforcement.

The IBM-AWS partnership delivers the power of a two-in-one unified offering, seamlessly integrating AI governance capabilities within your existing AI/ML operations and processes. Organizations will realize more streamlined workflows through the direct integration of the watsonx.governance console with SageMaker, for instance, enabling a customizable risk assessment and model approval workflow. Users can share vital information about models from Amazon SageMaker directly to create a unified workflow for governing AI operations. The partnership also addresses AI governance challenges while maintaining agility, and optimizes AI development and deployment costs, ensuring a faster time to production.

If businesses want to adopt AI at scale, they must build an AI governance strategy that integrates into their existing systems and a partnership that addresses the same. IBM and AWS are ready to help.

To learn more, visit the IBM watsonx.governance SaaS offering page on the AWS marketplace.