You shouldn’t work for your software. Your software should work for you.
This idea, once provocative, is now becoming a reality. The catalyst for this shift? Agentic AI. Agentic AI — which refers to AI systems and models that can act proactively to achieve goals without the need for constant human guidance — has quickly picked up steam with companies in the past year, powering AI agents so they can autonomously perceive, reason and act to complete tasks on the user’s behalf. In fact, AI agents are predicted to make at least 15 percent of daily business decisions by 2028 — up from 0 percent in 2024, according to Gartner, Inc.
But this shift isn’t happening in a vacuum; agentic AI systems aren’t just improving software like SaaS — they’re making it obsolete.
How SaaS is being surpassed
For decades, software evolved in service of human workflows. It started with on-premise software. Initially, it was installed and run on a company’s hardware infrastructure, while hosted locally.
Then, on-premise software gave way to SaaS, which allowed people to operate their applications from anywhere, thanks to the internet-enabled cloud. However, whether it was on-premise software or SaaS, they had one thing in common: They required a human in the loop. Someone had to sit in front of a screen and toggle between tabs to get the job done, which led to silos.
Now, agentic AI systems can do that work — and do it better. Take code generation, for example: Tools like the AI-powered code editor Cursor are demonstrating how natural language interfaces can collaborate with AI to understand users’ code, suggest improvements and produce high-quality code, faster than ever before. Go-to-market (GTM) is another example. GTM roles are siloed across SaaS platforms, where account executives live in Salesforce while sales development representatives spend most of their time in Outreach or Salesloft. But with agentic AI systems, they can take on each of these roles by executing campaigns, analyzing outcomes and optimizing future efforts. This marks the rise of VibeGTM — where users let agentic AI automate the complex, multi-step process of B2B sales outreach, enabling them to simply review the AI-suggested GTM campaign, tweak any details if needed, then quickly launch it with one click.
Agentic AI doesn’t just assist the user — it initiates, executes and optimizes tasks autonomously.
Prolonging the inevitable isn’t enough to save SaaS
From Workday to Slack, many SaaS incumbents are introducing gen AI features into their products, like copilots, assistants and chatbots, as a way of prolonging the inevitable. In fact, 35% of SaaS businesses are already using AI, and another 42% plan to use it in the near future, according to a Tech Jury study.
But this is like modifying a flip phone with a touchscreen — you’re just adding modern features to a device never designed for them.
SaaS tools retrofitted with AI features still assume a user is at the center. While they help users navigate, type or summarize, the user still orchestrates everything. That’s fundamentally different from an agentic AI system, where the software orchestrates itself.
True agentic AI systems are designed for machines to act, not for humans to operate. They act on real-time data, learn from outcomes and continuously adapt.
The new role of humans in an agentic AI world
With agentic AI designed to execute tasks on the user’s behalf, many workers may wonder where that leaves them — 28% of people are concerned about the possibility of their jobs being reduced or replaced by AI.
But agentic AI systems aren’t meant to replace humans; they’re meant to replace unhuman work, like administrative tasks and mindless screen-toggling. With humans no longer tethered to our desks, this allows us to spend more time face to face and do more creative and strategic work that machines can’t replicate, all while shaping, guiding, approving or rejecting the actions agentic AI systems produce.
Ironically, agentic AI will take us back to a more human world — one where software takes care of the software work, and people do the people work.
With agentic AI systems inevitably replacing SaaS, companies that use SaaS or are built around it have two ways to respond: Adapt or get left behind. Here’s how companies can start transitioning:
Test agentic AI systems against legacy software and human teams
Although agentic AI systems are catching on, companies still haven’t seen enough ROI to fully adopt them. That’s where testing becomes crucial.
Currently, a company’s IT team is set up to evaluate software. But, in order to adopt agentic AI, IT teams need to evaluate the agentic AI systems replacing the software and humans having to operate it. As a result, companies must rethink how they evaluate software when transitioning to an agentic AI system, moving beyond feature comparisons to full-scale bake-offs that measure real-world performance. This means testing agentic AI systems not just against legacy software and its productivity, but also against the human teams that operate the legacy software.
As agentic AI matures across horizontal and industry-specific use cases, the most strategic organizations will be the ones that aggressively test, validate and rapidly adopt the solutions that prove themselves in head-to-head performance comparisons.
Transition procurement and legal processes to prepare for agentic AI
Before adopting agentic AI systems, companies must also transition their procurement and legal frameworks to address a new class of risks, particularly data privacy and security. Agentic AI systems need data to perform self-determined tasks to meet predetermined goals. However, companies may be hesitant to share data outside of their own servers or public cloud, which may hinder updating their procurement and legal frameworks.
But this isn’t an overnight process; this is an evolution. Just as companies once feared the cloud before realizing it offered greater protection than on-premise infrastructure, their skepticism about agentic AI systems handling sensitive data will subside once realizing the advantages of contributing data to domain-specific models.
Early adopters who embrace this shift and update their legal and procurement processes accordingly will gain a competitive edge — just like Airbnb outpaced hotels by rethinking operations from the ground up.
As agentic AI moves from the margins to the mainstream, companies that embrace this transition will unlock unprecedented speed, efficiency and strategic focus. Those who cling to legacy SaaS systems, no matter how retrofitted, risk being outpaced by competitors who adopt agentic AI systems. The choice is clear: adapt now, or be disrupted later.
