AI Dominates IBM Executives’ Predictions for 2025
The IBM leaders weren't specifically asked about their thoughts on AI, but it was top of mind for nearly all of them
If 2024 didn’t inject enough AI into your life, just sit tight. And maybe buckle up. AI was almost all that IBM executives could talk about when asked about the industry developments they see coming over the next 365 days. And if their predictions come to pass, 2025 will be another big year for the technology as companies seek to gain an AI-enabled edge.
The rise of agentic AI and “shadow AI” will require a greater vigilance from the tools’ human keepers; super-charged, on-premises, open-source and multimodal AI will open up new possibilities for enterprise uses; and automation will help organizations reach their sustainability goals. This is what some of the top minds at IBM see coming, according to a list of their predictions shared by the company this month.
The Rise of Agentic AI
In 2025, AI will get increasingly proactive, i.e., agentic, according to Ritika Gunnar, general manager, Data & AI, IBM. “As agentic AI emerges as a predominant theme in 2025—marking a fundamental shift from traditional AI tools to proactive agents and teams of agents—so too will questions around accountability and control of these increasingly autonomous systems,” Gunnar said.
“This will bring greater attention to the guardrails, processes and tools for how we govern agents, in order to build trust for this powerful new frontier of AI capabilities. It will also heighten the need to upskill employees across every discipline and leadership level so they can responsibly develop, use and oversee agentic solutions.”
In addition to upskilling their employees, companies will also have to change their personnel structures to fully take advantage of agentic AI, said Jill Goldstein, global managing partner, HR & Talent Transformation, IBM Consulting. “As AI agents become more common, companies will need to reevaluate their work processes and create new types of teams where humans oversee groups of autonomous AI agents,” Goldstein said.
Among these new responsibilities is understanding the difference between AI assistants and AI agents. “Unlike AI assistants, AI agents have the ability to generate plans based on a prompt and carry out tasks independently. They are most effective when focused on specialized tasks and working together with other agents on complex, multi-part requests,” Goldstein explained.
‘Shadow AI’ and Other Data Security Concerns
While learning to manage AI agents, enterprises will also have to focus on protecting their sensitive data from escaping its confines via “shadow AI,” said Nataraj Nagaratnam, CTO, IBM Cloud Security.
“The democratization of AI technology with ChatGPT and OpenAI has widened the scope of employees that have the potential to put sensitive information into a public AI tool,” Nagaratnam explained. “In 2025, it is essential that enterprises act strategically about gaining visibility and retaining control over their employees’ usage of AI. With policies around AI usage and the right hybrid infrastructure in place, enterprises can put themselves in a better position to better manage sensitive data and application usage.”
One answer to security concerns is to keep certain AI workloads on premises, a measure that will be enabled by hardware innovations, said Tina Tarquinio, chief product officer, IBM Z and LinuxONE. “In 2025, we will see businesses shift to a fit-for-purpose approach to AI using dedicated hardware—particularly in mainframes that handle high-volume transactional data,” Tarquinio said.
“…Since this approach enables AI workloads to stay on premises, it also enhances the security, resiliency and compliance management process for mainframe operators in regulated sectors, while empowering them to unlock new levels of efficiency and insights, setting the new standard for predictive outcomes.”
Meeting Post-Quantum Threats
IBM’s prognosticators didn’t just focus on AI as they looked ahead. Alongside AI, quantum computing will also warrant consideration for matters of data security, as organizations prepare for threats enabled by the technology, said Ray Harishankar, IBM Fellow, IBM Quantum Safe. With that in mind, companies can tap the U.S. National Institute of Standards and Technology’s (NIST) expanding toolbox of post-quantum cryptography standards.
“NIST’s initial post-quantum cryptography standards were a signal to the world that the time is now to start the journey to becoming quantum safe,” Harishankar said. “But equally important is the need for crypto agility—ensuring that systems can rapidly adapt to new cryptographic mechanisms and algorithms in response to technological advances, changing threats and vulnerabilities—ideally leveraging automation to streamline and accelerate the process.”
AI and Automation
And with the mention of automation, the conversation quickly turns back to AI. “Next year, you won’t be able to have an AI conversation without talking about automation, and vice versa—you cannot have an automation discussion without talking about AI,” said Bill Lobig, VP, product management, IBM Automation.
“Simply put: Automation is needed to solve AI’s complexity,” Lobig said. “Organizations can now confidently advance and scale their AI initiatives using automation, moving from spending time managing and maintaining AI applications and IT environments, to proactively detecting and resolving issues.”
The pairing of automation and AI can help companies honor their sustainability goals, too, said Kendra DeKeyrel, VP ESG and asset management product leader, IBM. “Companies have bold 2030 sustainability goals, but also have more complex infrastructure and more data sources than when these goals were first announced years ago,” DeKeyrel said.
“In 2025, organizations with sustainability ambitions and targets should implement AI-powered automation capabilities, including observability, resource management and application lifecycle management. These capabilities can help reduce the strain on data centers, including managing energy consumption and improving asset performance and lifecycle, which can ultimately help progress sustainability goals overall.”
Open Source Opens Doors
Another development that will help organizations leverage AI will be the increased availability of open-source models, said Bill Higgins, watsonx Platform Engineering and Open Innovation, IBM Research. “Despite mounting pressure, many enterprises are still struggling to show measurable returns on their AI investments—and the high licensing fees of proprietary models is a major factor. In 2025, open-source AI solutions will emerge as a dominant force in closing this gap,” Higgins said.
“Thanks to their community-driven development, open-source models are quickly equaling the major proprietary offerings in power, and the proliferation of open industry- and task-specific AI solutions will make it easier than ever for organizations to apply them to a wide range of innovative use cases without hefty fees or API call costs. With their friendlier cost structure, greater transparency and auditability, and support for multi-cloud architectures, I expect open-source AI will prove pivotal in helping organizations scale beyond experimentation and start realizing returns in the coming year.”
Multimodal AI Handles Rich Content
Companies can also expect to get more value from AI through its growing ability to handle complex documents, said Sriram Raghavan, VP, IBM Research for AI. “Multimodal AI models are capable of processing and analyzing all manner of complex documents with embedded rich content in the form of images, tables and charts,” Raghavan explained.
“These models are also evolving to support other modalities such as audio and images, unlocking countless new possibilities for insights. As a result, organizations will need to begin bringing order and method to the way they handle all of this multimodal unstructured data to get it ready for enterprise AI. This will put pressure on existing infrastructure including greater storage requirements and robust management solutions.”
Careful Consideration Required
If these IBMers’ predictions are any indication, the topic of AI will again be hard to escape in 2025. But ubiquity doesn’t mean inevitability, and unlocking the power of AI while getting a return on that investment will be anything but automatic. So while the technology may be poised to do more for enterprises in the coming year, it will also give them more to think about.