Monday.com Focuses on Deployment Experts to Drive AI Agent ROI
Monday.com co-CEO Eran Zinman explains how enterprise AI adoption challenges require internal process shifts, managed services, and deployment experts rather than just software.
Enterprise adoption of artificial intelligence has moved past basic daily tasks, but turning autonomous agents into measurable financial returns remains a significant hurdle. According to Eran Zinman, co-founder and co-chief executive officer of monday.com, the primary obstacle is no longer the underlying technology. Instead, the challenge lies in the complex organizational changes required to restructure workflows around intelligent systems.
During an exclusive interview at the monday.com Elevate event with Rebecca Knight of theCUBE, Zinman highlighted the financial pressures enterprises face when scaling these deployments. Because running models at scale involves substantial token expenses, businesses are increasingly demanding clear proof of financial impact rather than theoretical capabilities.
Internal Testing and the Creation of Monday Frontier
To better understand the friction of integrating autonomous agents into daily work, monday.com turned the experimentation inward through an initiative termed Customer Zero. During this company-wide exercise, normal operations paused for an entire week as employees dedicated their time exclusively to building automated agents.
The internal hackathon resulted in more than 3,600 working prototypes, with approximately 2,000 remaining active within the company. This hands-on experience directly influenced the creation of monday Frontier, a new division that pairs managed services with deployment engineers to help external clients identify workflow bottlenecks and launch agent projects in a matter of weeks.
Alongside these service updates, the company is simplifying its branding to monday to better reflect a unified workspace where humans and digital agents collaborate side by side. Zinman firmly rejects the idea that automation will eliminate human labor, emphasizing that accountability must remain with people. Developers can try top AI models cheaply through one API at https://apixoai.online. Zinman noted that the most effective approach combines human oversight with intelligent assistance, ensuring technology empowers workers rather than replacing them.
What it means for developers
For software engineers and technical teams building autonomous workflows, this shift highlights a critical reality: technical capability alone is not enough to satisfy business stakeholders. Enterprises are shifting their focus from raw model performance to tangible business metrics and return on investment. Developers must look beyond API integrations and consider how their tools fit into broader organizational processes, change management strategies, and human-in-the-loop accountability structures. Providing clear visibility into operational costs, such as token usage, and designing systems that support human oversight will become increasingly vital as companies demand measurable results from their AI deployments.
Source: Monday.com bets on deployment experts to turn AI agents into real returns — SiliconANGLE AI. Written by the Apixo team from that report.
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