IBM, Google Cloud launch new practice to accelerate enterprise AI adoption

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Teddy Cambosa

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5 minutes ago

IBM, Google Cloud launch new practice to accelerate enterprise AI adoption

California, USA – IBM and Google Cloud have announced a strategic partnership aimed at helping organisations accelerate artificial intelligence (AI) adoption and modernise core technology systems through the launch of a new Google Cloud Practice.

The initiative combines IBM’s consulting capabilities, including its AI-powered IBM Consulting Advantage platform, with Google Cloud’s Gemini Enterprise Agent Platform, cybersecurity offerings, and data technologies. The companies said the practice is designed to support enterprises in deploying AI solutions, modernising legacy infrastructure, and managing complex hybrid technology environments.

According to the companies, the collaboration represents a multi-billion-dollar opportunity and will leverage IBM’s network of Google Cloud-certified consultants and engineers to assist organisations in scaling AI initiatives beyond pilot stages.

As part of the partnership, IBM is developing a portfolio of industry-specific AI agents optimised for Gemini Enterprise. These agents are intended for use across sectors including banking, government, retail, telecommunications, energy, security, insurance, and life sciences, supporting workflow automation, decision-making, and autonomous operations.

The new practice will also enable IBM consultants to design, build, and govern AI agents directly on Google Cloud. The companies said IBM’s pre-built assets, reusable agents, and transformation methodologies will be integrated with Google Cloud’s agent runtime, governance capabilities, and enterprise safety controls to help accelerate deployment.

The partnership builds on previous collaboration between the companies, including modernisation projects with aerospace company Airbus. IBM and Google Cloud said they worked together to help transition two Airbus businesses into independent operations within 18 months, updating more than 100 systems across engineering, manufacturing, customer service, and other regulated functions.

“Enterprises are facing one of the most complex modernisation cycles in decades,” said Mohamad Ali, Senior Vice President and Head of IBM Consulting. “By expanding our work with Google Cloud, we’re giving clients a clearer and more reliable path to scale AI across their business, combining deep industry expertise, hybrid-cloud modernisation, and an AI-first delivery platform.”

“This partnership significantly expands the pool of expert Google Cloud consultants in the market to meet surging demand for AI,” said Kevin Ichhpurani, President of Global Partner Ecosystem at Google Cloud. “By combining Google’s agentic infrastructure with IBM’s deep industry expertise and proven delivery frameworks, we are ensuring joint customers can move beyond pilots to deploy and govern production-grade AI agents across their entire cloud environment.”

Beyond AI deployment, IBM Consulting will help develop interface patterns and integration solutions that connect enterprise data to Gemini using technologies from IBM and its ecosystem. The companies said these interfaces can be customised to fit client architectures, enabling organisations to consolidate data and expand AI capabilities more efficiently.

The practice will focus on several areas, including production-ready AI and data platforms, industry-specific AI solutions, cybersecurity modernisation, hybrid cloud transformation, AI-powered workflows, and operational governance.

Among the technologies highlighted are Google’s BigQuery data platform, Confluent’s real-time data streaming capabilities, Red Hat OpenShift deployments through Google Cloud, and integrations involving IBM’s watsonx Orchestrate and watsonx.data platforms. The partnership will also incorporate automation, governance, and monitoring tools supported by HashiCorp and Apptio to strengthen operational resilience and compliance.

The companies said the initiative is intended to help organisations move from AI experimentation to large-scale deployment while modernising critical workloads across cloud and on-premises environments.

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