IBM Introduces Hybrid Technologies for Enterprise-Scale AI Deployment

At its annual THINK event, IBM announced new hybrid technologies designed to enable businesses to build and deploy AI agents using enterprise data, addressing key challenges associated with AI scalability.

IBM projects the emergence of over one billion applications by 2028. This trend is expected to place increasing demands on enterprises to scale operations across fragmented environments, highlighting the need for integrated tools that enable orchestration, data readiness, and seamless connectivity.

According to IBM’s latest CEO study, business leaders anticipate that the rate of AI investments will more than double within the next two years. Many organisations are actively adopting AI agents and preparing for broader deployment. However, the accelerated pace of investment has contributed to a disjointed technology landscape. Currently, only 25% of AI initiatives are delivering the expected return on investment.

To support enterprises in operationalising AI, IBM is combining hybrid infrastructure capabilities with AI agent development tools and sector-specific consulting expertise through IBM Consulting. This approach aims to bridge the gap between experimentation and enterprise-grade AI implementation, enabling organisations to manage complexity, improve ROI, and support scalable AI adoption.

"The era of AI experimentation is over. Today's competitive advantage comes from purpose-built AI integration that drives measurable business outcomes," said Arvind Krishna, Chairman and CEO, IBM. "IBM is equipping enterprises with hybrid technologies that cut through complexity and accelerate production-ready AI implementations."

IBM Enhances watsonx Orchestrate with Enterprise-Grade AI Agent Capabilities

IBM has expanded its watsonx Orchestrate offering to support the development and deployment of AI agents that integrate with over 80 enterprise applications. This initiative aims to assist businesses in embedding AI systems that perform operational tasks across varied IT environments.

Key Capabilities of watsonx Orchestrate

• Rapid Agent Development: Tools are provided to build AI agents within five minutes. Users can choose from no-code to pro-code options for integrating, customizing, and deploying agents across platforms.

• Pre-Built Domain Agents: Solutions include AI agents focused on HR, sales, and procurement, as well as utility agents for basic tasks such as web research and calculations.

• Wide Application Integration: Compatibility extends to major platforms from Adobe, AWS, Microsoft, Oracle, Salesforce Agentforce, SAP, ServiceNow, and Workday.

• Agent Orchestration: Enables coordination among multiple agents and tools for executing complex workflows and routing tasks appropriately.

• Agent Observability: Offers tools for monitoring agent performance, enforcing guardrails, optimizing models, and maintaining governance throughout the lifecycle.

IBM has also introduced the Agent Catalog in watsonx Orchestrate, providing access to over 150 AI agents and tools developed by IBM and partners including Box, MasterCard, Oracle, Salesforce, ServiceNow, Symplistic.ai, and 11x.

Enhancing Integration with webMethods Hybrid Integration

To address the challenge of integrating applications across hybrid environments, IBM has launched webMethods Hybrid Integration. This solution replaces rigid workflows with agent-driven automation for managing integrations across APIs, applications, B2B systems, events, gateways, and file transfers.

An independent Total Economic Impact (TEI) study by Forrester Consulting reported that organizations implementing webMethods realized over three years:

• 176% ROI

• 40% reduction in downtime

• 33% time savings on complex projects

• 67% time savings on simple projects

These capabilities complement IBM's automation portfolio, including integrations with HashiCorp for infrastructure provisioning and secrets management.

Unlocking Unstructured Data for AI

IBM is evolving watsonx.data to better utilize unstructured data for generative AI. Enhancements include:

• Open Data Lakehouse and Data Fabric Capabilities: To unify and govern data across silos, formats, and clouds.

• watsonx.data Integration: A single interface to manage and orchestrate data workflows.

• watsonx.data Intelligence: AI-powered tools to extract insights from unstructured data.

Select features will also be offered as standalone products to maintain flexibility for users.

IBM has announced its intent to acquire DataStax, expanding vector search capabilities to improve generative AI. watsonx is also now integrated within Meta's Llama Stack, enhancing deployment options for enterprise AI.

A new Content-Aware Storage (CAS) feature is available via IBM Fusion and will be supported by IBM Storage Scale in Q3 2025. CAS enables real-time processing of unstructured data for faster inference in retrieval-augmented generation (RAG) applications.

Infrastructure Advancements with IBM LinuxONE 5

IBM introduced LinuxONE 5, optimized for secure, high-performance AI workloads. Key features include:

• AI Acceleration: Includes IBM Telum II and the IBM Spyre Accelerator for high-volume inference workloads.

• Security Enhancements: Confidential containers and quantum-safe encryption.

• Cost Efficiency: Running containerized workloads on LinuxONE 5 can reduce total cost of ownership by up to 44% over five years compared to x86 systems.
  
  

IBM is also deepening its collaborations with AMD, CoreWeave, Intel, and NVIDIA to provide infrastructure support for compute-intensive AI workloads.

These developments reflect IBM’s continued focus on enterprise AI scalability, integration, and performance.

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