IBM and Google Cloud have announced a strategic partnership to accelerate the deployment of artificial intelligence in large organizations and modernize critical systems. The agreement includes the creation of a new Google Cloud Practice within IBM Consulting, staffed with thousands of certified consultants and engineering teams deployed close to clients to help them transition from AI pilots to production environments.
The collaboration combines IBM Consulting Advantage, IBM Consulting’s AI delivery platform, with Gemini Enterprise Agent Platform, along with data, cybersecurity, and governance capabilities from Google Cloud. The initiative targets sectors where AI adoption depends not only on having good models but also on integrating them with legacy systems, regulated data, critical processes, and hybrid environments.
AI Agents for Regulated Industries
IBM is developing a portfolio of industry-specific AI agents based on IBM Consulting Advantage, tailored for Gemini Enterprise. These agents will focus on use cases in banking, public administration, retail, telecommunications, energy, security, insurance, and life sciences.
The goal is for companies to automate workflows, improve decision-making, and move toward more autonomous operations supported by Gemini models. However, the value of this partnership isn’t just in the agents themselves but also in the layer of consulting, governance, and integration IBM aims to provide, ensuring these agents operate within real business environments, with their processes, risks, and constraints.
Mohamad Ali, Senior Vice President and Head of IBM Consulting, stated that companies are facing “one of the most complex modernization cycles in decades.” He believes the alliance aims to offer clients a clearer path to scaling AI by combining industry expertise, hybrid modernization, and a platform focused on AI delivery.
Kevin Ichhpurani, President of Google Cloud’s global partner ecosystem, echoed this: AI demand is growing, and the market needs more experts capable of bringing agents into production with enterprise control and security.
| Area of the Partnership | What IBM Brings | What Google Cloud Contributes |
|---|---|---|
| Consulting and Implementation | Thousands of certified consultants and sector expertise | Cloud platform and AI infrastructure |
| Enterprise Agents | IBM Consulting Advantage and industry-specific agents | Gemini Enterprise Agent Platform |
| Data | Integration with hybrid environments and core systems | BigQuery and cloud data capabilities |
| AI Governance | Transformation methods and enterprise control | Agent runtime, controls, and security |
| Modernization | Experience with legacy systems and Red Hat OpenShift | Google Cloud Console and cloud services |
| Cybersecurity | Security defense and operations services | Cloud security and data capabilities |
| Automation | IBM Automation, HashiCorp, and Apptio | Google Cloud AI for monitoring and performance |
From Pilots to Real Deployment
The overarching message closely mirrors what the tech industry has been emphasizing in 2026: many companies have tested AI, but few have scaled it systematically. An agent that works in a demo isn’t necessarily ready to operate within a bank, energy company, insurer, or government agency.
To bring AI into production requires clean, governed data; connectors to corporate systems; identity controls; traceability; security; regulatory compliance; integration architecture; and a clear way to measure results. The IBM-Google Cloud alliance aims to bridge precisely that gap between model promise and business execution.
The new practice will focus on several priority areas. The first is AI and data ready for production, combining IBM’s industry assets with Gemini Enterprise Agent Platform and BigQuery. The second involves developing tailored solutions for industries such as aerospace, financial services, government, healthcare, and telecommunications. IBM also references the use of Confluent for real-time data streaming and governance—an essential component as agents need to operate on up-to-date information.
Another component is cybersecurity modernization, with AI-driven defense capabilities to improve preparedness and response times. Additionally, hybrid modernization of mission-critical workloads is highlighted, particularly in regulated industries. Red Hat OpenShift, central to IBM’s hybrid strategy, is now directly available in Google Cloud Console, simplifying deployment of hybrid environments on Google infrastructure.
The partnership also envisions enhanced AI workflows through integration of Gemini with watsonx Orchestrate, aimed at decision automation and agent intelligence, as well as with watsonx.data to provide greater flexibility in generating actionable insights for enterprise applications.
Modernizing Legacy Systems Without Disrupting Business
The deal comes at a time when companies face dual pressures. On one side, there’s a need to adopt AI to improve productivity, customer service, analytics, security, and automation. On the other, they depend on core systems that cannot be turned off or replaced overnight.
Here, IBM leverages its well-known expertise in modernizing complex environments. The company cites its work with Google Cloud on Airbus, where they helped separate two aerospace businesses into independent operations in less than 18 months, updating over 100 mission-critical systems across engineering, manufacturing, customer support, and regulated functions.
Such projects exemplify the challenge. Enterprise AI isn’t just about isolated applications; it’s built on existing processes like ERP, CRM, manufacturing systems, data platforms, support tools, industry applications, and security layers. Without modernization, AI remains limited to peripheral functions; poorly modernized systems increase operational risks.
The combined promise of IBM and Google Cloud is to offer a more structured approach: reusable agents, common interface patterns, integration of enterprise data into Gemini, governance from design, and capability to operate in hybrid settings. The alliance also leverages IBM ecosystem technologies such as HashiCorp and Apptio to enhance monitoring, compliance, performance, and financial management.
A Multibillion-Dollar Cloud Services Opportunity
IBM and Google Cloud position this new practice as a multimillion-dollar opportunity in Google Cloud services. It’s no small detail—the enterprise AI business is not just about models but also about capturing the work involved in integration, migration, governance, security, and operations that enable these models to create tangible value.
For Google Cloud, the partnership enhances its ability to reach large clients through IBM’s consulting network. For IBM, it extends its footprint in AI projects over one of the top cloud platforms, without abandoning its hybrid approach or focus on regulated sectors.
It also reflects a broader trend: leading tech giants are forming cross-company alliances because no single provider can handle all the complexities of enterprise AI alone. Customers aren’t just asking for more powerful models—they want solutions that integrate with their data, comply with regulations, work with their existing systems, and endure over years.
The IBM-Google Cloud collaboration aims at this more mature market phase. The era of experimenting with generative AI has been rapid. Moving agents into production will be slower, costlier, and more demanding. In that phase, consulting, hybrid architecture, security, and governance will be as important as the model itself.
Frequently Asked Questions
What have IBM and Google Cloud announced?
They announced a new Google Cloud Practice within IBM Consulting to assist companies in scaling AI into production, modernizing critical systems, and deploying Gemini-based agents.
What is IBM Consulting Advantage?
It is IBM Consulting’s AI delivery platform. It helps teams design, build, and deploy AI solutions through agents, reusable assets, and sector-specific workflows.
What role will Gemini Enterprise play?
Gemini Enterprise Agent Platform will serve as the foundation for IBM to develop and govern industry-specific enterprise agents, integrating it with their consulting, data, and integration capabilities.
Why is this important for regulated companies?
Because sectors like banking, government, healthcare, telecommunications, and energy need to deploy AI with control, security, traceability, and compatibility with legacy systems. This partnership aims to bridge the gap between pilots and production.