Zoë Balroop
Data, Automation & AI Advisor and Specialist Development Deputy Team Leader, Softcat
Defining the Future of Enterprise AI with IBM
Think IBM, and one typically thinks reliable, robust, but not necessarily agile. For decades, their reputation was built on its enterprise hardware, mainframes, and consulting services – all hallmarks of stability rather than speed or innovation.
The rise of cloud-native competitors, however, forced a reckoning. As the world shifted from hardware to cloud and SaaS-based hosting, IBM was increasingly seen as being left behind. But something has changed.
Enter the AI market, and this perception is shifting. Today, IBM is not just keeping pace; it’s helping to define the future of enterprise AI.
The Legacy Perception
IBM’s history as a conservative enterprise vendor is well documented — a quick search easily surfaces timelines and performance analyses. Founded in 1911, the IT giant became synonymous with business computing, powering banks, governments and multinationals with its mainframes and integrated solutions. For much of the late 20th century, IBM was a safe, leading choice for large organisations. The technology was tried, tested, and trusted, but not really associated with challenger or disruptive innovation.
As the technology landscape evolved, a new generation of agile, cloud-native competitors emerged, dominating conversations about digital transformation. IBM, meanwhile, was often perceived as lagging behind, an effect catalysed by its slower innovation cycles.
The Transformation Journey
Under the leadership of Arvind Krishna, who became CEO in 2020, IBM embarked on a strategic pivot toward open hybrid cloud and artificial intelligence. This shift was marked by a series of acquisitions and investments designed to modernise IBM’s portfolio and accelerate innovation.
Key milestones included the acquisition of Red Hat in 2019, which brought open source and hybrid cloud capabilities to IBM’s core offerings; Turbonomic in 2021, for application resource management and automation; Apptio in 2023, for technology business management and FinOps; and WebMethods (from SoftwareAG), HashiCorp, and DataStax in 2024 and 2025.
Collectively, these moves underscore IBM’s ongoing effort to position itself as a leader in enterprise technology management and optimisation. They have also invested heavily in quantum computing, with up to $20 billion earmarked specifically for practical quantum system development as part of a broader $150 billion 5-year U.S. technology investment plan.
Cultural change accompanied these strategic moves.
IBM has embraced open source with renewed enthusiasm, investing in developer communities and promoting a faster innovation cycle. Their long-standing commitment to open source — dating back to early support for Linux, Apache, and Eclipse — has been clearly revitalised. You only need to look at their watsonx platform and open-source enterprise-grade Granite LLM to see IBM as a collaborator and innovator rather than a closed, proprietary vendor.
Becoming an AI Leader: The Technical Edge of watsonx
IBM’s transformation is most evident in its watsonx portfolio, a suite of tools and platforms designed to help enterprises build, deploy, and govern AI models at scale. The latest advancements, showcased at IBM Think 2025, highlight their ambition to lead in the era of agentic AI and generative AI.
watsonx Orchestrate: Enabling Agentic AI at Scale
watsonx Orchestrate is IBM’s platform for building, deploying, and managing AI agents in enterprise environments. These agents are not just chatbots; they are systems that can execute complex workflows, automate business processes, and integrate seamlessly across applications, data, and systems.
IBM’s approach to agentic AI is grounded in practical, production-ready use cases. IBM themselves are ‘Client Zero’, with their HR sales agent already massively deployed across the organisation and yielding $3.5 billion in productivity gains. More broadly, the platform supports the operationalisation of complex agentic workflows, emphasising the importance of high-quality, unstructured data as fuel for those workflows.
Now, new capabilities in watsonx Orchestrate include enhanced support for unstructured data, semantic search, and integration with existing enterprise systems, enabling organisations to automate everything from procurement to customer service and compliance.
watsonx.data: Unifying, Governing, and Activating Enterprise Data
A critical challenge for enterprise AI is the fragmentation and complexity of data. IBM’s response is watsonx.data, an open, hybrid data lakehouse designed to unify, govern, and activate both structured and unstructured data across silos, formats, and clouds.
Recent innovations in watsonx.data include:
- Open Data Lakehouse Architecture: watsonx.data provides a single, unified environment for managing the entire data-for-AI lifecycle. It supports open formats like Iceberg and Presto, and can be deployed in hybrid (on-premises and cloud) environments.
- Data Fabric Capabilities: The platform offers data lineage tracking, governance, and quality management, empowering organisations to trust and access meaningful data across their ecosystems.
- Integration and Intelligence: New products like watsonx.data integration and watsonx.data intelligence simplify accessing and managing data across formats and pipelines. These tools use AI to automate data curation, management, and governance, and can deliver AI models that are up to 40% more accurate than conventional retrieval-augmented generation (RAG) approaches.
- Vector Search and NoSQL Integration: Following the planned acquisition of DataStax, IBM will integrate vector search and NoSQL capabilities into watsonx.data, further enhancing its ability to manage unstructured data for generative AI applications.
watsonx.ai: Foundation Models and Automation
watsonx.ai provides a foundation for building, training, and deploying AI models at scale. The platform includes:
- Granite AI Models: IBM’s open-source, high-performing foundation models, optimised for efficiency and customisation. Granite 4.0 Tiny Preview, announced at Think 2025, offers smaller, more efficient models for edge and resource-constrained environments.
- AutoAI for RAG: watsonx.ai automates the development and deployment of retrieval-augmented generation (RAG) pipelines, enabling enterprises to build AI applications that deliver accurate, context-aware responses.
- BeeAI: An open-source, no-code platform for discovering, building, and running AI agents, empowering non-technical users to participate in AI innovation.
watsonx BI: AI-Powered Analytics
IBM has also introduced watsonx BI, an AI analytics agent that rewires how teams engage with data. watsonx BI can answer domain-specific questions (marketing, sales, operations, finance) in seconds, providing step-by-step explanations of its reasoning. This further empowers organisations to harness the full potential of their data for actionable insights.
Enterprise Impact and Industry Recognition
IBM’s investments in AI and data are already delivering measurable value. For example, Lockheed Martin recently leveraged watsonx.data to enable 70,000 engineers, scientists, and technicians to retrieve answers and information from millions of documents using natural language.
“We are rapidly accelerating our innovation and efficiency to get solutions out of the lab and into the field, helping create a safer, more secure world,” says John Clark, senior vice president of Technology and Strategic Innovation at Lockheed.
IBM’s approach to AI is also earning industry recognition. They have been named a Leader in the 2025 Gartner Magic Quadrant for Finance and Accounting Business Process Outsourcing, recognised for embedding generative AI into core processes to transform operations and reporting.
Perception Shift
Analyst reports and market data reflect IBM’s changing perception. While the company’s share of the server market remains modest — around 3.2% in 2025 — its expertise in AI-driven computing and quantum-inspired technologies positions it as a niche leader in high-end enterprise solutions. IBM’s market capitalisation surged to $242.51 billion in March 2025, a testament to investor confidence in its transformation.
Stock price trends further illustrate this shift. After starting 2024 at $163.55, IBM’s share price climbed to $191.85 by the end of the year, reflecting a 17% increase.
These gains reflect optimism about IBM’s ability to capitalise on AI and hybrid cloud opportunities.
Industry recognition has followed. IBM’s partnerships with SAP, AWS, and Microsoft demonstrate its integration into the broader technology ecosystem. Their open-source contributions and developer engagement have also grown, with initiatives like the watsonx AI Labs in New York City fostering collaboration with startups and enterprises.
But beyond the acquisitions and alliances, it is IBM’s technical depth, especially in the watsonx portfolio, that now sets it apart. The open, hybrid architecture of watsonx.data, the agentic workflows enabled by watsonx Orchestrate, and the foundation models and automation tools in watsonx.ai collectively represent a new standard for enterprise AI.
These capabilities are not just theoretical; they are being deployed at scale in industries like aerospace, finance, and healthcare, delivering measurable improvements in productivity, accuracy, and innovation.
Conclusion
IBM’s journey from legacy to leader offers a model for enterprise and brand transformation. It also serves to ensure they are not overlooked in the race to be a leading AI provider. Partly achieved through acquisition, but also through a comprehensive and genuinely impressive data, automation, FinOps, and AI offering, their reference-ability will be bolstered by real-world use cases — like their own internal transformation as “Client Zero” — and by a growing portfolio of industry recognition, from analyst reports to customer case studies.
As enterprises increasingly seek out proven, scalable, and responsible AI solutions, IBM’s ability to demonstrate tangible value — internally and externally — positions them as a credible, future-ready partner for organisations navigating the complexities of digital transformation.
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This article was written by Zoë Balroop, Data, Automation and AI Advisor at Softcat. To request more information from Softcat, an IBM Platinum Partner, please complete the form below.
