IBM is accelerating the deployment of enterprise-ready agentic AI systems by strengthening its partnerships with Oracle, AWS, and Salesforce. At
IBM's Think 2025 conference, the company announced these partnerships with the aim to accelerate the adoption of agentic AI and hybrid cloud solutions across enterprises.
. Through integrations across hybrid cloud environments and enterprise platforms, IBM aims to make it easier for businesses to adopt intelligent agents that automate workflows, act on data in real time, and scale AI use cases securely and efficiently.
Driving Agent Workflows with Oracle Cloud Infrastructure
IBM and Oracle have expanded their long-standing partnership to deliver agentic AI capabilities via Oracle Cloud Infrastructure (OCI). The partnership brings IBM’s watsonx Orchestrate and Granite models to OCI, enabling enterprises to automate functions like HR through intelligent agent workflows. These agents run on Red Hat OpenShift within OCI, providing the flexibility to operate in public, private, or sovereign cloud environments—crucial for meeting regulatory and data residency requirements.
IBM's Granite models will also be accessible on OCI Data Science via AI Quick Actions, allowing faster inferencing by hosting cached model versions close to enterprise data. Meanwhile, watsonx.ai has been certified to run natively on OCI, giving Oracle users the ability to build and manage AI applications without moving data out of their cloud environment. IBM Consulting is offering new services to support these implementations, including agent ecosystem design, legacy app migration, and infrastructure modernization via OpenShift Virtualization.
Advancing Scalable AI with AWS and Agentic Governance
At IBM Think, the company also detailed new offerings built in collaboration with AWS to streamline the adoption of agentic AI. The integrations connect IBM’s watsonx Orchestrate with AWS services—such as Amazon Q index and Bedrock—enabling enterprise agents to act on trusted content from systems like Salesforce, Slack, and Zendesk.
Pre-built IBM agents for HR, procurement, and sales are being upgraded to use real-time context via Amazon Q. To ensure responsible AI use, watsonx.governance features will soon be available through AWS Marketplace, giving organizations tools to monitor for model bias, drift, and compliance. Granite 3.2 foundation models are being deployed on AWS via Bedrock and SageMaker JumpStart, with support for serverless deployments through Bedrock’s Custom Model Import. IBM is also introducing new consulting toolkits and integration accelerators tailored for AWS-native services—enabling rapid deployment of AI agents across business domains.
Unlocking Mainframe Data with Salesforce Agentforce
IBM’s collaboration with Salesforce is focused on bringing mainframe data into modern AI workflows.
By integrating IBM Z and Db2 systems with Salesforce Data Cloud via Zero Copy, AI agents can now access enterprise-grade data without replication—meeting the needs of regulated industries like finance.IBM is also releasing watsonx-powered agents built specifically for Salesforce Agentforce and Slack. These include a Sales Prospecting Agent and an Employee Support Agent, aimed at improving productivity in sales and HR functions through natural language interaction and contextual insights. IBM’s domain-optimized Granite models are now offered as BYO-model options within Salesforce, giving enterprises more flexibility in deploying targeted generative AI solutions.
Across Oracle, AWS, and Salesforce, IBM is leveraging its watsonx platform, Granite models, and consulting expertise to scale the adoption of agentic AI. Each partnership expands the footprint of IBM's AI ecosystem, aligning with enterprise infrastructure choices and enabling agent workflows across cloud, mainframe, and business application environments.
Real-Time AI to the Edge for Scalable, Secure Enterprise Use with Lumen
IBM is also partnering with Lumen to address a pressing challenge in enterprise AI: how to scale real-time intelligence without incurring the high costs and security risks of centralized cloud models. By combining IBM’s watsonx AI tools with Lumen’s edge computing infrastructure, the two companies aim to bring inferencing capabilities directly to the edge—closer to where data is generated. This setup minimizes latency, reduces dependence on public cloud resources, and offers businesses more control over their data. Edge AI processing will support real-time insights and decision-making across industries like healthcare, financial services, manufacturing, and retail—helping organizations act on data faster while maintaining compliance and security.
The collaboration also positions IBM Consulting as the lead systems integrator, ensuring that clients can deploy AI models at scale while aligning to industry-specific goals. This partnership also represents a strategic push to move enterprise-grade AI out of test environments and into live, production-ready edge deployments—meeting the growing need for localized, secure, and efficient AI across distributed operations.
