The Rise of SaaS Killers: How Agentic AI Will Rewrite the Software Playbook
- George Bandarian
- 5d
- 6 min read
Updated: 2d
How Agentic AI SaaS Is Redefining Enterprise Software
Agentic AI SaaS is reshaping enterprise software in ways that feel almost like magic. These systems don’t just respond; they observe, decide, and act across workflows without waiting for human input. For founders, this isn’t just a trend; it is a chance to build the next generation of SaaS killers—platforms that are smarter, faster, and more adaptive than legacy systems.
“A lot of the traditional SaaS… We have a tremendous opportunity for a new batch of AI founders to take a first principles approach to what the customer really wants,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.
The competitive landscape is shifting fast. KPMG’s 2025 AI Survey reports that 82 % of organizations believe AI agents will change how business software competes. That means customers are ready for platforms that do more, anticipate needs, and drive results. The window for early movers is wide open, and the timing has never been better.
So why are traditional SaaS platforms at risk, and how can agentic AI give founders the edge they need? Let’s break it down.
Why Traditional SaaS Platforms Are at Risk and How AI Agents Change the Game
If you’ve ever scaled inside Salesforce or ServiceNow, you know the pain: workflows balloon, per-seat pricing surprises customers, and everything feels more complicated than it should. That frustration is exactly where agentic AI finds its opening.
With agentic AI, software begins to:
Make Decisions Autonomously: Agents can interpret data, take action, and optimize workflows without constant human guidance.
Connect Across Systems: Bottlenecks disappear as agents coordinate between finance, HR, sales, and operations.
Learn Continuously: Every action teaches the system how to get better, reducing errors and inefficiencies over time.
Tech leaders like Satya Nadella have noted that companies that don’t embrace agentic AI risk irrelevance. Legacy platforms struggle to reinvent themselves quickly, but startups can start fresh by designing software that feels alive from day zero.
Somebody needs to come up with something we call a mafia offer to get me to consider your new way… the mafia offer is simply an offer your customers can’t refuse,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.
Now that we understand the opportunity, let’s see how agentic AI makes a real impact inside business workflows.
How Agentic AI Boosts Efficiency Across Business Workflows
Agentic AI shines most when it lives inside the day-to-day work of a business. Think of it as a teammate who sees the full board and always knows the next move.
Key areas where it adds value:
Finance: AI can route invoices, signal cash flow risks, and follow up with vendors automatically.
Customer Service: Agents draft suggested replies, summarize interactions, and close tickets faster.
Supply Chain: Predict disruptions, optimize inventory, and adjust delivery routes in real time.
Amazon is a perfect example at scale. Its network blends software, robotics, and human oversight to keep orders moving faster while reducing errors. Startups can emulate these practices to make their platforms feel just as seamless, even on a smaller scale.
Next, let’s explore where founders should focus first when adding AI agents to enterprise software.
Prioritizing Use Cases: Where AI Agents Deliver the Most Value
Not every business process benefits equally from agentic AI. Founders should pick areas where impact is measurable and clear.
Core Systems: Finance, HR, sales, and supply chain. Ask yourself: can an agent move a record across systems without human intervention?
High-Volume Tasks: Invoices, email sorting, basic support. Measure: can the agent handle these reliably while freeing humans for higher-value work?
Cross-System Journeys: Quote to cash, order to delivery, hire to onboard. Test: can the agent coordinate every step across departments in real time?
When startups focus here, they don’t just increase efficiency; they transform entire workflows, delivering real ROI.
Of course, coordinating agents across multiple systems requires careful oversight. Let’s look at practical governance.
Ensuring Seamless Collaboration: Multi-Agent Orchestration and Governance
Imagine a team of AI agents collaborating like your best coworkers—autonomous, efficient, and always in sync. Deploying multiple AI agents across business functions is powerful, but without oversight, miscommunication, duplicate work, or errors can sneak in. Startups aiming to compete with traditional SaaS platforms need the right balance between autonomy and control.
Key strategies to get this right:
Human-in-the-Loop Checks: Ensure outputs, especially in sensitive areas like finance or healthcare, are reviewed by humans. This way, you reduce risk without slowing down the workflow.
Multi-Agent Coordination: Agents working across departments—finance, HR, sales—must align their actions. Centralized orchestration frameworks act like a conductor in an orchestra, keeping every agent on the same page. For example, a lead agent coordinating invoice approvals across finance and sales can cut duplicate work by 30 percent.
Observability Layers: Track agent behaviors, decision accuracy, and compliance in real-time. Dashboards and alerts make it easy to spot deviations before they become problems.
Practical approaches to governance:
Assign lead agents to oversee sub-agents in complex workflows.
Set up automated alerts for outputs that deviate from expected outcomes.
Conduct regular audits to ensure policies and ethical standards are met.
With these practices, startups can deploy agentic AI confidently, scaling integration across the business without sacrificing reliability or agility. This approach turns multi-agent orchestration from a potential headache into a competitive advantage.
Transforming IT Operations: From Application Management to Agent-Led Systems
IT teams no longer just maintain apps—they now guide AI agents that handle coding, testing, and optimization. This shift lets teams focus on innovation while agents manage routine work.
Key applications include:
Code Automation: AI agents can write, review, and optimize code, reducing development cycles.
Infrastructure Optimization: Agents monitor system performance, detect inefficiencies, and automatically optimize uptime.
Real-Time Risk Assessment: AI identifies cybersecurity threats, flags vulnerabilities, and recommends preventative actions.
For example, during an S/4HANA migration, an AI agent detected a compatibility issue that could have caused delays. IT teams intervened proactively, avoiding downtime and keeping the project on track. Agent-led models turn IT departments into strategy hubs, rather than just maintenance units.
Strategic Implications: Why Founders Have the Edge
Enterprises are demanding real ROI and trimming SaaS spend. Legacy providers are weighed down by seat-based pricing, technical debt, and rigid architectures. Startups have a unique advantage: they can design platforms from the ground up with agentic AI at the core.
Early-Mover Advantage: Nimble startups can deploy smarter systems faster than bloated incumbents.
Full-Stack Innovation: Companies building AI-native platforms are not simply adding features—they’re creating intelligent, adaptive SaaS solutions.
Outcome-Driven Design: Focusing on measurable results, founders can deliver immediate value and differentiate from legacy systems.
The opportunity is clear: build a SaaS killer that solves real pain points while traditional software struggles to keep pace.
Real-World Success Stories of Agentic AI in Action
Several globally recognized brands illustrate the transformative potential of agentic AI:
Amazon: Autonomous warehouse robots and AI-driven supply chain orchestration reduce fulfillment times and increase efficiency.
UiPath: Robotic process automation integrates AI agents across enterprises to automate repetitive workflows.
Salesforce Einstein: Predictive analytics agents embedded in CRM workflows help companies make smarter decisions faster.
These examples show founders the tangible impact of agentic AI—faster decision-making, fewer errors, and scalable efficiency. Startups can emulate these approaches to stand out in competitive SaaS markets.
“Software used to help a human deliver a service, now the software is the expert and delivers the service,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.
Looking Ahead: The Future of SaaS in the Agentic AI Era
Agentic AI will not merely improve SaaS; it will redefine enterprise software. Startups have a unique opportunity to:
Launch platforms that integrate intelligence natively, rather than layering AI afterward.
Optimize end-to-end workflows for rapid, measurable ROI.
Build adaptive, self-improving systems that scale seamlessly as businesses grow.
The real question is: who will seize this moment? Will you be the founder who builds the SaaS killer every enterprise is waiting for, or will incumbents keep dragging things forward on their terms?
If you’re already sketching, prototyping, or even building in stealth, we want to hear from you. This is exactly where Untapped Ventures is deploying first checks with deep conviction.
Ready to Build?
At Untapped Ventures, we back early-stage AI founders reimagining software at the agentic frontier. If this resonates with your vision, pitch us. Together, we can build the next generation of enterprise platforms.
FAQs
What is agentic AI SaaS?
Agentic AI SaaS refers to AI-powered software platforms that can operate autonomously, integrate across multiple business functions, and improve performance over time.
How does agentic AI differ from traditional SaaS?
Unlike traditional SaaS, which relies heavily on human input for decision-making and workflow execution, agentic AI SaaS automates complex processes, reduces errors, and continuously adapts to changing data and business needs.
Can legacy SaaS platforms survive the AI revolution?
Yes, but only if they embed agentic AI, eliminate technical debt, and redesign their platforms for adaptability. Otherwise, nimble startups could disrupt them.
How can startups leverage agentic AI SaaS?
Startups can design intelligent platforms from the ground up, focusing on end-to-end workflow optimization, measurable ROI, and adaptive automation that scales with the business.