The global AI agent market is set to exceed $103 billion by 2032. For executives, the message is blunt: This isn’t just another tech upgrade. Instead, AI agents are the most powerful financial lever your business will have this decade.

As Aditya Gautam, one of the field’s leading researchers, explains during a recent interview, agents go beyond language. Instead, they reason, plan and act. That makes them strategic profit engines that help cut costs, accelerate data-driven decision-making and unlock revenue opportunities at a scale that traditional automation could never achieve.

To understand how AI actually generates revenue for companies, let’s start from the beginning.

From LLMs to agents: The financial breakthrough

To understand why this evolution matters, Gautam explained that AI agents are the orchestration and intelligence layer that sits atop LLMs. “They’re goal-driven systems that plan, reason and use tools — not just understand language,” he said.

Whereas LLMs advance through pre-training, fine-tuning and reinforcement learning, the real breakthrough comes when agents add reasoning, memory and tool use. According to Gautam, that’s where the economics shift, automating tasks that save time, reduce headcount needs and increase revenue efficiency.

Measurable ROI, not hype

Gartner predicts that by 2026, 80% of enterprises will deploy GenAI in production. Gautam points out this isn’t just experimentation anymore: “Companies are cutting operating costs, shrinking cycle times and supporting executive decisions at scale.”

The ROI is already visible. Sales teams are automating qualification and reporting, compliance departments are reducing audit costs, and service organizations are lowering customer support overhead. In every case, agent projects are proving themselves to be profit multipliers, not experimental spending.

Agents vs. misinformation: A $78 billion problem

Did you know misinformation costs the global economy $78 billion annually? Fortunately, a recent interview where Guatam references his ICWSM 2025 paper, which outlines a multi-agent framework with five roles, replicates a fact-checker’s workflow at scale.

Having read his report and spoken with him about this framework, the benefits are obvious. We’re talking faster, cheaper and more reliable outcomes. The same architecture can also be applied to compliance, auditing and customer service, all of which directly impact cost savings and revenue protection.

“The real test is real-world impact,” Gautam said. “If it reduces cost and effort, it’s not just buzz — it’s value.”

Strategic guidance for executives

For leaders weighing build vs. buy, Gautam is direct: “Only companies with billions to spend should consider building foundational models.”

Instead, he recommends an ROI-first approach:

• Identify ROI – Target processes where agents deliver measurable financial value.
• Start Small – Use APIs for quick wins and cost reduction.
• Layer Agents – Add context, memory and tool access to expand efficiency.
• Evaluate & Monitor – Apply guardrails to avoid costly mistakes and reputational risk.

Evaluation itself must be both financial and technical. Gautam’s six criteria — task success, factuality, safety, robustness, reasoning and efficiency — are designed to maximize ROI while minimizing wasted effort.

What’s next: Agents as profit centers

By 2030, Gautam envisions agents embedded across every enterprise function — including research, analysis, planning and customer engagement — that reduces labor costs, accelerates innovation and increases revenue per employee. He added that agent marketplaces will emerge, allowing businesses to plug in pre-built tools instead of absorbing high development costs.

Yet, he’s quick to add caution: “Automation is powerful, but without oversight, it risks poor experiences and reputational damage. Not every problem needs an LLM. Understand your use case. Measure ROI. Build with intention.”

The possibilities for strategic AI agents represent the single most significant financial opportunity of the decade. I agree with Gautam when he says that the enterprises that seize it first will set the pace for growth, profitability and competitive advantage.

Amy Osmond Cook is co-founder and chief marketing officer at Fullcast, a Silicon Slopes-based, end-to-end RevOps platform that allows companies to design, manage and track the performance of their revenue-generating teams.