Kathy Gibson reports from Pinnacle TechScape – For years, IBM has been very deliberate in how it has shifted its strategy, positioning itself for today’s realities.
This is according to Clarissa Lindeque, ecosystem and software segment leader at IBM, who points out that the company has built an enterprise AI portfolio that directly addresses customer use cases.
The IT giant’s software portfolio covers public cloud, hybrid cloud, hybrid data and middleware, hybrid automation and insights, and AI agents. This is complemented by its extensive server and storage solutions.
All of the various types of AI – machine learning, generative AI and agentic AI – are incorporate into the IBM solution.
Indeed, IBM offers a full automation platform that includes integration and security layers.
Gartner predicts that 60% of AI projects will fail, and only 26% of chief data officers are confident their data capabilities can support new AI-enabled revenue streams.
“But why is this?” asks Lindeque.
The first challenge that companies fact is figuring out where their data is, and whether it is structured or unstructured – or a mix.
The next step is to figure out what is blocking AI-ready data.
This could be fragmentation. A massive 63% of companies aren’t integrating their data, with silos across multiple clouds. The risk here is that data silos block innovation and realtime access across hybrid estates, Lindeque explains.
Today, less of 1% of enterprise data is represented in models, and 90% of it is unstructured, presenting another challenge.
Governance and security is also stopping a full-scale move to AI, with just 15% of it leader believing they have the right governance modes in place to manage AI agents in enterprise applications.
Despite these challenges, organisations persevere because AI-ready data increases the business value of AI.
But only if the data is being delivered quicker, and that it is trusted and reliable,” Lindeque says.
The IBM data portfolio integrates various data types and sources into a unifying data layer and applies the intelligence that adds value.
Rounding out the AI software offering is Bob, IBM’s assistant, agent and software development tool.
“Bob helps partners to move customers from planning to production,” Lindeque explains. “It has a plan mode and a code mode – and governance and policies are built in.”
Because Bob has access to IBM’s vast knowledge base, it is a powerful tool for partners to add value.
IBM’s software solutions are complemented by its hardware portfolio that include IBM Z and LinuxOne mainframes, IBM Power and PowerVS client systems, IBM Cloud and IBM storage.