At IBM’s Think Conference last week the company announced that it is collaborating with Amazon Web Services AWS to integrate the entire suite of its watsonx AI and data platform offerings with AWS services to scale responsible artificial intelligence (AI). Since the launch of ChatGPT, AI has been all the rage, with almost every company I talk to looking at it in some form. One of the biggest concerns is ensuring it’s used accurately and responsibly.

IBM says it aims to facilitate the scalable deployment of AI in enterprises through an open, hybrid model enhanced by comprehensive governance. The companies intend to integrate IBM watsonx.governance with Amazon SageMaker. This service is designed to provide fully managed infrastructure, tools and workflows for building, training and deploying machine learning and generative AI models at scale.

This integration should help Amazon SageMaker and watsonx customers manage model risk and meet compliance requirements related to recent regulations like the EU AI Act. It also completes the offering of the watsonx platform in the AWS Marketplace, which already features IBM watsonx.ai and watsonx.data as customer-managed options.

In the announcement, Ritika Gunnar, IBM’s general manager of product management for data and AI, said that the company’s open AI and hybrid cloud strategy aims to help businesses extract value from AI using their data.

“Watsonx.governance enables them to manage and govern their AI solutions in an automated way, with the ability to customize solutions to their unique needs as they bring on more AI capability and respond to evolving AI regulations around the world,” she said. “Our expanded relationship with AWS combines IBM’s leading AI governance with Amazon SageMaker, offering customers flexibility, scalability and integration with other AWS services.”

Optimizing workflows and speeding AI deployments

When they become available in June, IBM said that watsonx.governance and Amazon SageMaker should help clients optimize workflows, speed up AI project deployment, and manage AI in complex IT environments. Clients will be able to configure and monitor customizable risk assessment and model approval workflows involving multiple stakeholders, ensuring an audit trail within both watsonx and Amazon SageMaker.

Intending to get genAI solutions to their mutual customers, this deal is hitting all the right notes. “By combining the strengths of Amazon SageMaker and watsonx.governance, we are empowering businesses to leverage generative AI effectively and securely, drive workflow improvements, and ultimately deliver greater value,” said Ankur Mehrotra, General Manager of Amazon SageMaker at AWS. “We look forward to continuing to innovate together on meaningful AI solutions for our customers.”

Governance is a challenge In the announcement, Chris Konow, CEO of AWS and IBM business partner CleanSlate Technology Group, endorsed the partnership.

“Balancing the rapid progression of generative AI with growing governance and regulatory concerns is a delicate challenge all organizations are concerned about,” he said. “The ability to seamlessly combine the power of AWS SageMaker with watsonx.governance will help address governance at the very foundation layer of AI projects.”

Adi Paz, CEO of GigaSpaces Technologies, thinks this partnership will be fruitful for those looking to query enterprise data. “IBM watsonx.governance on AWS provides fit-for-purpose AI governance capabilities that allow us to leverage the power of Amazon SageMaker,” he said in the announcement. “Together, these technologies create a highly trusted foundation for our Retrieval Augmented Generation Solution, GigaSpaces era.”

Some final thoughts AI has been a landscape changer. AWS has been and remains the cloud king despite competition from all angles. Their innovation in the cloud space has given it a significant competitive advantage. In AI, its advantage in the cloud doesn’t translate, and it faces much stiffer competition.

AI has changed things forever. So, the more partnerships AWS can forge, the better. IBM had an early edge in the long-ago early days of AI with its focus on enterprise AI, which was eclipsed by upstart consumer-centric technology applications. Both AWS and IBM have a common goal: to maximize customer choice. Vendors doing what’s best for customers typically leads to success.