The Transition from Building to Operating AI Agents
As we venture deeper into 2026, the landscape of artificial intelligence in business is undergoing a pivotal transformation. Enterprises, having spent the last few years in a whirlwind of experimentation and rollout of AI agents, are now pivoting towards a focus on effective operation and governance of these technologies. According to Maryam Ashoori, Vice President of Product and Engineering at IBM Watsonx, the time has come for companies to shift their mindset from merely creating AI agents to ensuring they operate safely and effectively within integrated business systems.
The Rise of Agentic AI
Back in 2023, the rise of generative AI marked an experimental phase within organizations. Most companies engaged in pilot projects and proof-of-concept initiatives, grappling with the array of possibilities AI presented. However, as organizations started deploying large language models that could invoke APIs and directly interact with their internal software, it triggered a flurry of activity. Each AI agent introduced presented a dual-edged sword: while they opened new avenues for productivity, they also required robust frameworks for governance to mitigate operational risks.
The Challenges of Managing AI Agents
The rapid scale of AI agent implementation led to unforeseen complications. The absence of a centralized management system results in a chaotic environment where varied agents built by different developers operate under diverse operational assumptions. Ashoori emphasizes that the goal has evolved; rather than racing to produce agents—some constructed in mere minutes—businesses must now focus on questions of trust and reliability.
Observability: The New Imperative
Key to navigating this transition is observability—an unyielding necessity for organizations utilizing AI agents. Robust observability ensures real-time monitoring of agents’ actions, enabling organizations to maintain control over potential malfunctions and data governance issues. Echoing insights from industry experts, organizations must build detailed audit trails of agent interactions to enhance accountability and facilitate adjustments as needed.
Building a Future Facing AI Workforce
This shift has profound implications for the future of work. HR professionals and operations leaders are called to rethink their strategies around workforce automation and employee development. As automation through AI agents proliferates, so too does the demand for vital upskilling initiatives. The landscape of talent management is shifting; leaders must focus on cultivating human-AI collaboration that enhances workforce capabilities while maintaining essential roles for employees in oversight and decision-making.
Conclusion: Embracing the New Era of AI Integration
The evolution from developing AI agents to managing them reflects a broader understanding of their implications within business systems. As AI technology matures, it becomes evident that an agile workforce will be poised to harness AI’s potential while guarding against its inherent unpredictabilities. Embracing this period of transformation, organizations must ensure thoughtful integration of AI agents as aligned tools within their broader workforce strategy.
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