The first phase of the artificial intelligence (AI) boom was undoubtedly defined by powerful large language models capable of a large variety of tasks. AI models like those that power ChatGPT can do a lot of things reasonably well, although they still output incorrect information and fabricated responses at times.
The second phase will likely be defined by AI agents, which are narrow in focus and can be designed to autonomously handle related tasks. Imagine a customer service AI bot that can chat with customers, figure out what needs to be done to fix the customers’ problems, and then hook into internal systems to process refunds, change settings, or escalate issues, all while adhering to company policies and procedures. AI agents could greatly reduce costs while improving customer service, a one-two punch that makes the technology extremely appealing.
AI agents for the enterprise
While a lot of technology companies are talking about AI agents and agentic AI, International Business Machines (IBM 0.01%) is uniquely positioned to ride the AI agent wave. After years of unsuccessful AI strategies, IBM has landed on an enterprise AI approach that’s racking up billions of dollars in bookings.
IBM’s AI strategy has two components. First, there’s watsonx, the company’s AI software platform that can run just about anywhere, including on Amazon‘s AWS. With watsonx, IBM’s enterprise customers have a fully stocked toolbox to develop, train, test, deploy, and manage AI models and AI agents.
A big selling point of watsonx is its governance capabilities. Some industries have strict regulatory and compliance requirements, particularly when sensitive user information is involved. Imagine a financial services company looking to build an AI agent that can help customers solve problems. That company needs to be sure that its AI agent isn’t going to leak sensitive information or go off the rails. IBM’s watsonx platform provides the observability and monitoring tools to keep AI agents in check.
While watsonx is a powerful platform, the bulk of IBM’s $3 billion in AI-related bookings so far has come from its consulting business. While software is an important component of any AI strategy, large enterprises also need guidance, implementation, and other services to realize the full benefits of AI. The consulting business is a key differentiator for IBM, and it helps to bring new business to other parts of the company like software and infrastructure.
Fulfilling the promise of AI
While general-purpose AI models are impressive, their value to large enterprises is questionable since their answers can’t be trusted and they can be expensive to run. AI agents, in contrast, can be trained to do specific tasks well, and they can often use less powerful and cheaper-to-run models that don’t need to be trained on a vast amount of external information. For enterprises that have struggled to find viable use cases for AI, AI agents could be the answer.
IBM’s powerful artificial intelligence software platform paired with its consulting arm is a potent combination that puts the company in a great position to ride the AI agent wave and implant itself at the center of the next big thing in AI. IBM’s AI strategy won’t make a lot of headlines, but the company is working behind the scenes for its enterprise clients to enable them to deploy AI in a way that makes financial and business sense.
With the stock trading for about 17 times the company’s full-year free-cash-flow guidance, IBM is a top AI agent stock that can be bought at a reasonable price.
John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool’s board of directors. Timothy Green has positions in International Business Machines. The Motley Fool has positions in and recommends Amazon. The Motley Fool recommends International Business Machines. The Motley Fool has a disclosure policy.
