IBM has launched a new service designed to help enterprises deploy agentic AI at scale across business operations. The offering, called IBM Enterprise Advantage, brings together IBM consulting services, pre-built AI agents, and governance tools to help companies deploy AI more quickly and safely across the enterprise, the company said.
Enterprise Advantage enables organizations to integrate AI into existing workflows and systems and expand agentic applications using their current cloud environments and AI models.
It does this by combining IBM’s consulting expertise with tools developed through IBM Consulting Advantage, the company’s internal AI-enabled delivery platform. IBM said the internal platform has been used in more than 150 client engagements and has helped improve consultant productivity.
Those experiences shaped how Enterprise Advantage is now being offered to customers to support their own AI initiatives.
The service supports major hyperscalers including AWS, Google Cloud, and Microsoft Azure, as well as IBM watsonx and a mix of open‑ and proprietary models. The service will allow companies to extend existing technology investments rather than replace them.
Addressing the Enterprise AI Execution Gap
A recent IBM Institute for Business Value report highlighted a growing gap between AI ambition and execution. The report found that 79% of executives expect AI to deliver significant business value by 2030. However, only 24% say they have a clear view of where that value will come from.
The report indicated that many organizations still lack the operating models and systems required to support AI at scale.
Enterprise Advantage is designed to help address this gap by providing a structured way to build, integrate, and govern AI agents within existing enterprise platforms.
Key elements of the service include:
- Enterprise AI platform design: Companies can integrate AI capabilities into existing enterprise systems and workflows without requiring wholesale infrastructure changes using Enterprise Advantage. IBM cited Pearson, as an example where Pearson is building personalized, AI-powered learning tools for global organizations and individuals. The learning company is also developing a custom internal AI platform to transform its own business operations and drive growth.
- Multi‑cloud and model flexibility: Support for major cloud platforms and a mix of open‑ and proprietary AI models, allows organizations to build on existing technology investments.
- Pre‑built AI agents and accelerators: Enterprise Advantage will give companies access to a catalog of reusable, industry‑specific AI agents intended to shorten deployment timelines and reduce implementation risk.
- Built‑in governance and controls: Enterprise Advantage supports embedded mechanisms for security, compliance, and lifecycle management as AI agents are deployed into production environments. IBM’s research report notes that organizations are increasingly adopting hybrid human‑and‑AI working models, which introduce new governance and risk management requirements as AI becomes more operationally embedded.
Mohamad Ali, senior VP and head of IBM Consulting, said, “Many organizations are investing in AI, but achieving real value at scale remains a major challenge. We have solved many of these challenges inside IBM by using AI to transform our own operations and deliver measurable results, giving us a proven playbook to help clients succeed. Enterprise Advantage brings this framework to clients by combining human expertise with digital workers and ready-to-use AI assets so they can scale AI with confidence and achieve meaningful impact.”
What This Means for ERP Insiders
Enterprise AI is shifting from experimentation to operating mode. IBM’s launch reflects growing pressure on large organizations to move beyond pilots and define how AI fits into core operating models. The emphasis is on repeatable architectures that can scale across the enterprise and deliver value while working within existing systems.
Agentic AI raises the architectural bar for ERP environments. As AI agents take on more orchestration and decision-support roles, ERP systems must allow AI to work directly with live business data, rather than sitting outside core processes. This increases the importance of platform design and interoperability over point functionality.
Governance becomes a prerequisite for scaling AI. IBM’s research highlights that risk, compliance, and oversight concerns are emerging as primary constraints on AI adoption. For large enterprises, scalable AI now requires governance frameworks built into the architecture from the outset.
