Vin Vomero, CEO FoxyAI

This month’s Crew AI Enterprise Agent Summit in Manhattan brought together thought leaders, investors, and AI practitioners to discuss the emerging landscape of AI agents and their transformative role in modern operations. A central theme was that these agents – software capable of reason, decision-making, and system interactions – will handle routine, “junior-level” tasks and free people to focus on higher-order work. Rather than replacing people, agents complement teams by eliminating tedious processes, allowing them to focus on higher level activities – creativity, strategy, and complex problem-solving.

From supply chain optimization to global trade compliance and Know-Your-Customer (KYC) analysis, the conference showcased real-world use cases where agents were already streamlining tasks that were once bogged down by paperwork and manual intervention. Collaborative multi-agent reinforcement learning stood out as a promising area of research, offering ways to optimize networks of agents for maximum efficiency and minimal cost. Jake Bengtson of Cloudera explained that while training large models can be expensive, the resulting systems can often be deployed lighter weight and “on the edge,” models, enabling responsiveness in critical settings – including cybersecurity.

Investor panels underscored the market’s hunger for agent-based solutions. With organizations like JP Morgan and startups alike pouring resources into AI-driven process automation, “agentic” technology has become a must-have for any forward-looking venture. Yet, integration challenges—such as system interoperability, software tools, data readiness, and security—still loom large. Speakers stressed the importance of building robust “last-mile” solutions, where the real business value emerges.

Legendary machine learning engineer and industry veteran Andrew Ng noted that while the hype around AI agents can overshadow immediate realities, focusing on high-value workflows yields strong ROI. Regardless of the vertical business sector, companies are rapidly incorporating agents into daily operations. The takeaway for leaders? Embrace this shift by identifying tedious tasks that stand to benefit most from automation, and remember that despite the hype, it all comes down to real-world implementation, delivering tangible improvements to productivity, cost savings, and overall business agility.

When FoxyAI launched back in 2018, our vision often outpaced what the technology could realistically deliver—certain tasks simply weren’t feasible because large-scale language models and accessible AI frameworks hadn’t reached the level of sophistication we see today. The release of ChatGPT was an inflection point, catapulting AI into mainstream awareness and enabling startups and enterprises alike to develop solutions that previously felt out of reach. Today, keeping up with the latest in AI is a nearly full-time job in itself. This rapid evolution not only highlights the massive strides AI has made but also underscores the opportunity for innovators to harness these capabilities and fundamentally reshape how work is done.