Reading: From Software to Agentic AI Systems

As organisations adopt advanced AI technologies, it is important to first understand that we are not simply adding new tools to existing systems—we are witnessing a shift in how work itself is structured and executed. Traditionally, work has been carried out by humans navigating software applications, using interfaces (screens, dashboards, workflows) to access data and complete tasks. However, with the rise of AI agents, this model is beginning to change.

Two influential perspectives help frame this shift:

“The IT department of every company is going to be the HR department of AI agents in the future.”
— Jensen Huang

“AI agents will replace all software.”
— Satya Nadella

“Since SaaS is essentially a thin UI layer on top of a database (as Nadella described), the ability of AI agents to interact directly with databases will fundamentally disrupt traditional SaaS. Business logic will migrate to an AI layer, making full application stacks less necessary when AI can work directly with core data.”
— Satya Nadella

These statements signal a fundamental transformation in computing. Jensen Huang’s view reframes the role of organisations—from managing systems to managing intelligent agents that behave more like a workforce. This introduces new responsibilities around supervision, coordination and governance. At the same time, Satya Nadella’s perspective highlights a structural change in software itself—applications are no longer the centre of value. Instead, the intelligence layer, powered by AI agents, becomes the primary driver of outcomes.

As AI agents gain the ability to directly access and interact with data, the traditional need for multiple application layers begins to reduce. Rather than navigating systems step by step, users can express intent and agents can plan, execute and coordinate tasks across systems. This represents a shift from interface-driven interaction to outcome-driven execution.

This transformation has significant implications. The role of IT evolves into orchestrating agents rather than maintaining software. The architecture of systems shifts from standalone applications to interconnected, agent-driven ecosystems. Most importantly, the definition of “software” itself changes—the interface is no longer the product; the outcome delivered becomes the product.

In the context of the upcoming video, this reading provides the foundation for understanding agentic AI as more than just an advancement in technology. It represents a strategic shift where AI systems move from being passive tools that respond to prompts, to semi‑autonomous actors that can understand context, take initiative and execute tasks within defined boundaries.