IBM, Google Cloud join forces to push enterprise AI from pilot projects into real production

Most enterprise AI projects never make it past the pilot stage. IBM and Google Cloud are betting they can change that.

The two companies announced Wednesday the launch of a joint Google Cloud Practice, built specifically to help large organizations move AI out of testing environments and into actual business operations. The collaboration pairs IBM’s consulting depth and its AI delivery platform, IBM Consulting Advantage, with Google Cloud’s Gemini Enterprise Agent Platform, data infrastructure, and cybersecurity tools.

The scope is notable. IBM has thousands of Google Cloud-certified consultants and engineers ready to deploy through the practice, and the companies describe the commercial opportunity as running into the billions. IBM is also building a library of industry-specific AI agents, covering sectors like banking, insurance, retail, telecommunications, government, and life sciences, each designed around real operational workflows rather than generic templates.

One early example of what this kind of work looks like in practice: IBM consultants and Google Cloud helped Airbus separate two aerospace businesses into independent operations in under 18 months. That effort touched more than 100 systems across engineering, manufacturing, and customer service. It is the type of complex, regulated environment where most technology partnerships quietly struggle.

The practice prioritizes a few areas: getting AI into production with proper data foundations, modernizing aging infrastructure across both on-premises and cloud environments, and strengthening security operations with AI-driven tools. Red Hat OpenShift, an IBM product, is now available directly within the Google Cloud Console, which simplifies hybrid deployments for clients working across both environments.

IBM is also integrating Google’s Gemini with its own watsonx products, including watsonx Orchestrate for decision automation and watsonx.data for analytics, giving enterprise clients more flexibility in how they connect AI to their existing systems.

The timing reflects a broader shift. Demand for production-grade AI consulting has accelerated considerably, and neither company wants to leave that market to competitors. For IBM, this deepens an existing relationship. For Google Cloud, it significantly expands the network of credentialed experts selling and deploying its platform inside large enterprises.