IBM and Google Cloud announced a new consulting practice on June 4, 2026, aimed at helping large organizations move artificial intelligence projects into production while modernizing older technology systems.
The new Google Cloud Practice sits inside IBM Consulting and is being positioned around enterprise AI, hybrid cloud modernization, data systems and cybersecurity. IBM and Google Cloud said the effort will bring IBM consultants and engineers together with Google Cloud tools including Gemini Enterprise Agent Platform, BigQuery and Google Cloud security services.
Because the announcement comes from the companies themselves, several of the larger business claims should be read as company positioning rather than independently verified market results. IBM and Google Cloud describe the practice as a major commercial opportunity, but they did not provide independently verified financial projections or a firm public timeline for every part of the rollout.
The move reflects a broader shift in enterprise AI spending. Many companies have tested generative AI through pilots, internal tools and proof-of-concept projects, but production deployments often require harder work: connecting private data, updating legacy systems, setting governance rules, securing workflows and deciding which processes are safe to automate. IBM and Google Cloud are framing the new practice around that gap between experimentation and day-to-day business use.
A Consulting Push Built Around Gemini and IBM Delivery Tools
IBM said the practice will combine its consulting delivery methods and IBM Consulting Advantage with Google Cloud’s AI and data stack. IBM Consulting Advantage is IBM’s internal AI-powered platform for consulting teams, used to support design, build and deployment work with agents and industry workflows.
In the companies’ description, IBM consultants will use Google Cloud’s Gemini Enterprise Agent Platform alongside IBM assets to design and govern enterprise AI agents. IBM also said it is developing industry-specific AI agents for sectors such as banking, government, retail, telecommunications, energy, security, insurance and life sciences. Those agents are described as being built with IBM Consulting Advantage and optimized for Gemini Enterprise, though the announcement does not independently verify how many are already deployed with customers.
The companies said the practice is intended to help clients reuse pre-built assets, agent patterns and transformation methods rather than starting each AI project from scratch. That approach is meant to make enterprise AI work more repeatable, especially for organizations with regulated data, complex approval processes or hybrid infrastructure.
IBM and Google Cloud also pointed to the role of Google Cloud-certified IBM consultants and forward-deployed engineers. The companies say those teams will support AI deployment, system modernization and management across hybrid environments. The exact staffing scale and customer commitments were not independently verified in the announcement.
Why the Partnership Matters for Enterprise AI
The announcement is aimed at a specific problem facing large organizations: AI systems rarely become useful in isolation. A chatbot or agent may be easy to demonstrate, but production AI usually needs access to clean data, identity systems, security controls, audit trails and business applications.
IBM Consulting will help develop interface patterns and solutions that connect enterprise data into Gemini, according to the announcement. The companies described the approach as open and flexible, with room to integrate IBM technology and other ecosystem tools depending on a client’s architecture.
That part of the partnership is important because data access remains one of the main blockers for enterprise AI. Companies often hold information across cloud services, on-premises databases, software-as-a-service tools and legacy systems. The new practice is intended to help connect those environments without forcing every client into the same architecture.
IBM and Google Cloud also tied the practice to modernization work. That includes updating older applications, moving workloads into cloud or hybrid environments and supporting regulated industries where migration projects must account for compliance, uptime and security.
The companies cited previous work with Airbus as an example of their joint modernization experience. According to the announcement, IBM consultants and Google Cloud helped transition two aerospace businesses into independent operations in under 18 months, including updates to more than 100 critical systems across engineering, manufacturing, customer service and other regulated functions.
Priority Areas Named in the Announcement
IBM and Google Cloud listed several focus areas for the new practice. These are company-stated priorities, not independently verified outcomes:
- Production AI and data: Helping clients build AI foundations that can support operational systems, using IBM industry knowledge and Google Cloud tools such as Gemini Enterprise Agent Platform and BigQuery.
- Industry-specific solutions: Developing AI and data capabilities for fields including aerospace, financial services, government, healthcare and telecommunications.
- Real-time data: Using technologies such as Confluent to help stream and govern data for AI systems in regulated or operationally complex environments.
- Cybersecurity modernization: Applying AI-driven defense and response capabilities to security operations.
- Hybrid cloud modernization: Supporting workloads that span on-premises systems and cloud environments. IBM also said Red Hat OpenShift is now available directly in the Google Cloud Console, though that claim should be treated as company-provided unless verified separately during deployment planning.
- AI-powered workflows: Integrating Gemini with IBM tools such as watsonx Orchestrate and watsonx.data, according to the companies, to support automation and data-driven applications.
- Operational resilience and governance: Using IBM automation, HashiCorp and Apptio capabilities with Google Cloud AI to support monitoring, compliance and performance management, as described by the companies.
The breadth of that list shows that IBM and Google Cloud are not presenting the practice as a single AI product. They are pitching it as a services and platform combination for organizations that need consulting, infrastructure, data work and governance together.
Executive Comments Frame AI as a Modernization Cycle
Mohamad Ali, senior vice president and head of IBM Consulting, said enterprises are facing one of the most complex modernization cycles in decades. He described the expanded Google Cloud work as a way to give clients a more reliable path to scale AI across their businesses, combining industry expertise, hybrid cloud modernization and an AI-first delivery platform.
Kevin Ichhpurani, president of the global partner ecosystem at Google Cloud, said the partnership expands the pool of expert Google Cloud consultants available to meet AI demand. He said the goal is to help joint customers move beyond pilots and deploy production-grade AI agents across cloud environments.
Those comments align with the central message of the announcement: enterprise AI is moving from experimentation toward managed deployment. IBM and Google Cloud are making the case that clients need both AI platforms and experienced implementation teams to make that transition.
The companies also included standard cautionary language that statements about future direction and intent may change. That matters for readers evaluating the announcement, because some parts of the practice describe current capabilities while others describe intended integrations, industry assets or future client outcomes.
For now, the concrete development is the launch of the Google Cloud Practice within IBM Consulting. The larger promise is that IBM and Google Cloud can turn that practice into a repeatable path for enterprises trying to put AI agents, data systems and modernized infrastructure into production.