University of Kwazulu-Natal

Agentic Ai In Enterprise Workflow Automation Ibm Developer

Bonisiwe Shabane
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agentic ai in enterprise workflow automation ibm developer

This IDC Market Perspective describes how IBM is accelerating enterprise transformation in the agentic AI era with new offerings announced in October, including IBM Bob, Project infragraph, and the Granite 4.0 model family. These innovations focus on agentic workflows, infrastructure automation, and cost-efficient AI inference, addressing legacy modernization, developer productivity, and governance. IBM's multimodal strategy and partnerships position the company to meet evolving enterprise needs, while the company's agentic tools empower organizations to modernize, automate, and secure complex IT environments."By adding agentic capabilities to a wide... Gain premium exposure to our growing audience of professionals. Learn More AI agents already going beyond rigid scripts to handle complex, evolving tasks and adapt to any workflow or domain.

CUGA is a next-generation, open-source AI agent framework now available on Hugging Face Spaces that removes common barriers like workflow brittleness and tool misuse, making robust, enterprise-grade AI agents accessible to developers and organizations... Figure 1: CUGA Agentic Architecture Credit: IBM CUGA brings a new level of versatility to agent technology by providing a highly configurable solution for automating intricate tasks across both web and API platforms. The framework consistently ranks at the top of industry benchmarks: The secret to CUGA’s excellence lies in its fusion of advanced agentic patterns, combining planner-executor and code-act architectures with structured planning, intelligent variable management to reduce hallucinations, and dynamic task decomposition. Its customizable reasoning modes let users tailor performance for speed, cost, or complexity.

IBM BAW as Your Agentic AI Platform: Why Organizations Are Ditching Standalone AI for Workflow-Integrated Agents Most organizations are approaching AI backwards. The cost is failed pilots and missed opportunities. While most organizations are chasing the latest AI shiny object with standalone implementations that don’t scale, we are now giving organizations with business process management (BPM) systems, such as IBM Business Automation Workflow (BAW)... We’ve built the first native agentic AI framework for IBM Business Automation Workflow, and the results are transformative. For organizations already running BAW as part of their business process management strategy, this changes everything about how you should think about implementing AI agents.

Walk into most Global 2000 companies today and you’ll find a repeating story: AI pilots everywhere, production deployments nowhere. According to multiple analyst reports, organizations are taking an AI-first approach rather than a process-first approach, and this is putting the odds for failure very high. For years, automation in the enterprise meant scripts and rules. You mapped a process, broke it into steps, and asked software to follow those steps exactly. Robotic process automation and workflow tools excelled at this kind of work. They never improvised.

That was the point. Agentic AI arrives with a very different promise. Instead of asking systems to follow a script, you ask them to achieve a goal. The system then decides which steps to take, which tools to use, and how to adapt when conditions change. McKinsey’s latest State of AI survey notes that 23% of organisations are already scaling agentic AI systems, and another 39% are experimenting with them somewhere in the enterprise. Agentic AI is moving from labs into live workflows.

The question is no longer “Is this real” but “What happens to our operating model when it is.” IBM describes agentic AI as systems made of AI agents that can pursue a specific goal with limited supervision, breaking work into subtasks and coordinating to reach an outcome. IBM BAW as Your Agentic AI Platform: Why Organizations Are Ditching Standalone AI for Workflow-Integrated Agents Most organizations are approaching AI backwards. The cost is failed pilots and missed opportunities. While most organizations are chasing the latest AI shiny object with standalone implementations that don’t scale, we are now giving organizations with business process management (BPM) systems, such as IBM Business Automation Workflow (BAW)...

We've built the first native agentic AI framework for IBM Business Automation Workflow, and the results are transformative. For organizations already running BAW as part of their business process management strategy, this changes everything about how you should think about implementing AI agents. Walk into most Global 2000 companies today and you'll find a repeating story: AI pilots everywhere, production deployments nowhere. According to multiple analyst reports, organizations are taking an AI-first approach rather than a process-first approach, and this is putting the odds for failure very high. Reworked's leadership channel brings together the latest trends and best practices to guide the leaders of today and tomorrow. Hear from the leading voices in the space on organizational design, modern management, corporate culture and more.

At IBM Think 2025, IBM doubled down on a bold agentic AI strategy to unify digital labor across hybrid enterprises. With the rise of AI agents that can reason, collaborate and operate autonomously, businesses are racing to transform siloed automation efforts into orchestrated, enterprise-wide digital workforces, according to Scott Hebner, principal analyst at theCUBE... IBM’s vision aims to bring interoperability, flexibility and trust to this new world by enabling any agent, on any platform, to work across any workflow. Agentic AI is quickly emerging as a pivotal evolution in enterprise technology. It’s reshaping how companies manage processes, empower employees and create value. IBM’s approach stands out by focusing on open standards, semantic control planes and an architecture that invites a diverse ecosystem of agents.

“We’re seeing a critical inflection point,” Hebner said. “IBM is applying the same interoperability playbook that made it a leader in e-business and hybrid cloud.” The scale and complexity of enterprise ecosystems demand AI agents that are not just intelligent, but also interoperable. IBM’s announcements at Think 2025 centered around this very idea, championing openness as the foundation of digital labor. With watsonx Orchestrate positioned as the orchestrator of the agentic enterprise, IBM introduced a platform capable of managing, coordinating, and integrating agents built with any framework. “Over the next three years, one billion agents will be built on the basis of generative AI,” Rob Thomas, senior vice president, software and chief commercial officer at IBM, said during IBM Think.

“They will need to work with each other seamlessly.”

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