IBM’s flagship annual conference opened today in Boston with CEO Arvind Krishna delivering what the company called its most comprehensive set of enterprise AI announcements to date. The central message was blunt: 2026 is the year enterprises stop piloting AI and start running it at scale.

More than 5,000 senior business and technology leaders from 80 countries gathered at the Thomas M. Menino Convention and Expo Center for Think 2026, which runs May 4 through 7. The product launches were not incremental.

Watsonx Orchestrate Reaches Production

The headline announcement is that watsonx Orchestrate, IBM’s agentic AI platform, moves from preview to full general availability. The production release ships with 150-plus enterprise connectors covering the systems most large organisations already run: Salesforce, SAP, Workday, ServiceNow, Microsoft 365, Oracle, Adobe, and AWS.

The platform now includes built-in observability dashboards, so IT and operations teams can see exactly what each agent is doing, catch errors early, and maintain audit trails without building custom monitoring on top. That observability layer is not an afterthought. It addresses one of the biggest friction points slowing enterprise AI deployments: legal, compliance, and risk teams needing to know what decisions the AI is making and why.

Agent Catalog: 150-Plus Ready-to-Deploy AI Workers

The bigger announcement for most enterprises is the new Agent Catalog inside watsonx Orchestrate. IBM describes it as a governed marketplace where organisations can discover, deploy, and combine agents from IBM and its partner ecosystem.

The catalog launches with 150-plus pre-built agents and tools. Partners contributing to it include Box, MasterCard, Oracle, Salesforce, ServiceNow, Symplistic.ai, and 11x. The pre-built agents cover specific business domains: sales engagement, HR talent acquisition, and supply chain optimisation are among the launch use cases.

What makes the catalog notable is what it does not require. Agents built on any framework, any LLM, or any cloud can be onboarded, validated, and listed. An organisation running a mix of AWS-hosted custom models, Google Gemini integrations, and IBM-native agents can wire all of them into the same orchestration layer without rewriting anything. That cross-platform stance is a direct response to the multi-cloud, multi-model reality most large businesses now live in.

Every agent in the catalog is validated and observable before being listed. IBM is positioning this as the difference between a generic app store and an enterprise-grade marketplace, where governance is baked in from the start rather than bolted on after a security incident.

Other Announcements at Think 2026

IBM also introduced the watsonx Workshop, a skill-building platform for enterprise teams that uses AI to run coaching sessions and realistic role-play scenarios. The goal is to help employees develop the skills needed to work alongside AI agents, rather than just learn about them in theory.

On the infrastructure side, IBM launched LinuxONE 5, its most secure Linux platform for AI and enterprise data, rated to handle up to 450 billion AI inference operations daily. That number matters for organisations running AI at transaction-level volumes, such as banks processing payments or insurers handling claims in real time.

Customer demonstrations at Think 2026 include deployments at Aramco, Cleveland Clinic, and Elevance Health, three organisations with very different compliance and security requirements, all running production AI agents.

What This Means for Business

The watsonx Orchestrate GA and Agent Catalog represent something worth paying attention to: a major enterprise platform vendor declaring that the testing phase is over.

For business leaders still evaluating AI, the Agent Catalog lowers the entry cost significantly. Instead of building custom agents from scratch, teams can pull pre-validated, domain-specific agents off a shelf, connect them to existing systems through 150-plus connectors, and have something running in production in weeks rather than months.

The cross-framework design is also practically important. Most organisations have already bought something, built something, or committed to a cloud. IBM is not asking them to throw that away. The orchestration layer sits on top and connects what is already there.

The observability and governance features matter most for industries where AI decisions carry real accountability: healthcare, finance, legal, and government. Knowing what an agent decided, when, and based on what information is the foundation of defensible AI deployment.

IBM is not the only company making these kinds of announcements this week. ServiceNow opens Knowledge 2026 today in Las Vegas with similar themes around agentic AI and platform maturity. The signal from both events is the same: enterprise AI has crossed from experimentation into infrastructure. The question for most organisations is no longer whether to run AI agents, but how fast to scale them and which ones to run first.

For businesses that have been waiting for enterprise-grade tooling before committing, that tooling is now here.