As 2025 unfolds, AI agents are emerging as the year’s defining business technology trend, with tech giants racing to develop tools that promise to transform how companies operate. However, amidst the excitement, a fundamental question remains: what exactly is an AI agent?
The Business World’s Next Frontier
Imagine technology that negotiates contracts, predicts supply chain collapses, and resolves customer complaints—all without human oversight. This isn’t speculative fiction. AI agents are already doing it, rewriting business playbooks at a pace that’s startling even Silicon Valley’s optimists.
OpenAI’s latest API and SDK release isn’t just an upgrade—it’s checkmate on inefficiency. This new tool stack allows companies to deploy agents that independently scour internal databases, crawl websites, and execute workflows with surgical precision, effectively retiring the era of scripted chatbots and rigid automation.
The business impact could be substantial. Companies that leveraged AI in 2024 saw 1.5 times higher revenue growth, and AI agents promise to extend these advantages. For instance, in customer service, conversational agents equipped with natural language processing are handling complex customer inquiries, with Bank of America’s virtual assistant Erica efficiently managing over 1.5 billion customer interactions.
But this breakneck progress conceals a fault line. The same boardrooms pouring billions into “AI agents” can’t agree on what the term means. Are they autonomous decision-makers? Sophisticated workflow tools? Or something entirely new? The answer could determine which companies dominate the next decade—and which get left behind.
The Definition Dilemma
Despite the enthusiasm, the industry faces a significant challenge: no one can agree on what an AI agent actually is. Tech leaders including OpenAI’s Sam Altman, Microsoft’s Satya Nadella, and Salesforce’s Marc Benioff have made bold predictions about AI agents “joining the workforce” and becoming “the number one provider of digital labor in the world.” To the same point, in an interview on occasion of the World Economic Forum 2025, Benioff claimed, “Today’s chief executives are the last generation to manage all-human workforces as companies increasingly adopt artificial intelligence.”
The push for AI adoption from top tech CEOs is loud. Their financial stake in it is obvious. The question is, however, how much of it is the organic result of underlying dynamics versus the forced message of business propaganda.
As one expert noted, “The concepts of AI ‘agents’ and ‘agentic’ workflows used to have a technical meaning, but about a year ago, marketers and a few big companies got a hold of them.” This ambiguity creates both opportunities and challenges for businesses. While it allows for flexibility in customizing agents to specific needs, it also leads to misaligned expectations and difficulties in measuring ROI.
The tech industry’s track record suggests it’s unlikely companies will coalesce around one definition anytime soon – if ever. This definitional crisis echoes previous technology buzzwords that became diluted through overuse and marketing hype.
Practical Applications Amid the Hype
Despite the definitional chaos, businesses are finding concrete ways to implement these technologies. AI agents can execute time-consuming data-related tasks in minutes, creating high-quality content and extracting more value from meetings. They operate in three stages: perceiving their environment through models like natural language processing, applying algorithms to reason and make decisions, and continuously learning to refine their performance over time.
Some companies are already seeing results. ServiceNow reports that 80% of its customer support cases are now handled without human intervention, utilizing analytical and generative AI to address common questions. When human workers remain involved, the company found that agentic AI shrank the time to handle complex cases by 52% in a two-week period.
As businesses navigate this evolving landscape, the key challenge will be separating practical implementations from marketing hype. While 2025 may not deliver the fully autonomous AI workforce that some tech leaders have promised, organizations that develop clear internal definitions and strategic implementation plans for AI agents stand to gain significant competitive advantages as the technology matures.