The transition from SaaS to Services as Software with AI agents is underway, necessitating new orchestration methods similar to Kubernetes for containers. AI agents will require resource allocation, workflow management, and scalable infrastructure as they evolve. Two key trends are driving this shift: 

Data Evolution – From spreadsheets to AI agents, data has progressed through relational databases, big data, predictive analytics, and generative AI. 

Computing Evolution – Starting from mainframes, the journey has moved through desktops, client servers, web/mobile, SaaS, and now agentic workflows. 

Janakiram MSV, an analyst, notes on this episode of The New Stack Makers that SaaS depends on data—without it, platforms like Salesforce and SAP lack value. As data becomes more actionable and compute more agentic, a new paradigm emerges: Services as Software. AI agents will automate tasks previously requiring human intervention, like emails and sales follow-ups. However, orchestrating them will be complex, akin to Kubernetes managing containers. Unlike deterministic containers, AI agents depend on dynamic, trained data, posing new enterprise challenges in memory management and infrastructure. 

Learn more from The New Stack about evolution to AI agents:

 How AI Agents Are Starting To Automate the Enterprise 

Can You Trust AI To Be Your Data Analyst? 

Agentic AI is the New Web App, and Your AI Strategy Must Evolve 

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