How B2B Software Is About to Change Forever
Why the Future Isn’t SaaS — It’s Systems That Think for You
We’re standing at the edge of a massive shift in how businesses use software.
Today’s Model: Most internal business software fall into one of two buckets:
Custom-built internal tools – expensive to build and even more expensive to maintain, update, and scale.
Out-of-the-box SaaS platforms – easier to implement, but dependent on users to input data, configure workflows, and extract insights manually.
This model has powered digital transformation for years, but it’s about to be disrupted by something much more powerful.
Tomorrow’s Model: The future belongs to agentic AI — autonomous systems that complete tasks without ongoing user inputs. These agents can work 24/7, pulling from APIs, internal and external data sources, and existing tools to produce outputs that previously required full-time teams.
No more dashboards to check. No more recurring SaaS subscriptions for generic tools that sort-of fit your workflow. Just a network of intelligent agents working behind the scenes, tuned specifically to your business’s needs.
What’s Needed to Make the Shift
To get there, two critical enablers must be in place:
While the vision of autonomous, always-on agents might sound futuristic, we’re far closer than most realize. The building blocks like powerful language and reasoning models, contextually accessible APIs, flexible no-code platforms, and a growing ecosystem of AI tools, are already here. What’s missing isn’t capability. It’s coordination and specialization.
We’re just two steps away from this future becoming the norm:
A New Generation of Agentic Developers and Consultants
The current AI wave has given rise to prompt engineers and automation specialists. But agentic AI requires a different mindset — one that blends software architecture, task design, and a deep understanding of business workflows.
These professionals won’t just build tools. They’ll define systems of autonomous agents that interact with data (single agent) and each other (multi-agent), connect to APIs, and complete full processes without human intervention. As businesses recognize the cost and performance advantages of agent-based systems, the demand for this new breed of builder will explode. With it, the skill sets required will become more standardized and accessible.Simplified Access to Contextual Data and Tools
Today’s software and data ecosystems are still too fragmented for agents to operate independently at scale. Many APIs require custom integration work. Data is often siloed or locked behind interfaces meant for human eyes. And outputs are rarely structured in a way that other tools, let alone AI agents, can interpret.
To support agentic workflows, more companies need to make their tools machine-consumable by default. This means exposing clean, well-documented APIs, enabling contextual queries across datasets, and adopting formats that allow agents to ingest, reason, and act, all without needing human translation or constant reconfiguration.
Together, these two shifts don’t just move us closer to the agentic future. They unlock it.
The technology is ready. The use cases are clear. Now, it’s just a matter of connecting the dots and preparing for the biggest transformation B2B software has seen since the dawn of SaaS itself.
What This Means for SaaS Companies
SaaS platforms, especially horizontal tools that serve broad audiences, are at risk. Why? Because the very tasks they help users accomplish — scheduling campaigns, monitoring news, compiling reports, generating content — are increasingly replicable through AI agents.
Yes, the upfront cost to develop an agentic system might exceed a typical SaaS subscription. And yes, running agents comes with ongoing expenses — including token usage for large language models (LLMs) and API query fees across connected services. But in most cases, these costs remain negligible when compared to traditional SaaS subscription fees and their annual, frankly inevitable, price hikes, especially at scale.
The ROI is exponential: build an agent once, and let it run continuously, tuned exactly to your company’s structure, goals, and data sources. Instead of paying for broad, generic tooling, you're investing in a system that works precisely the way you need — no excess, no manual overhead. And optimizing the frequency and types of calls to connected LLMs and APIs allows you to further control and predict costs.
As agentic systems become easier to develop and more integrated into business operations, companies will favor bespoke autonomy over generic usability. SaaS platforms, which rely on mass adoption and one-size-fits-all solutions, will struggle to compete in this new landscape.
A Real-World Example: Media Monitoring in PR
Let’s say you’re a PR agency tracking media coverage. Today, you might license a media monitoring SaaS tool that offers analytics, dashboards, and search capabilities. But you still need:
Analysts to create and refine searches
Researchers to interpret results and build reports
Strategists to use those reports for planning
You’re also at the mercy of that tool’s licensing agreements. If it doesn’t cover a key publication your client cares about, you’re stuck buying another tool, exporting the data manually, and trying to stitch everything together.
Now imagine an agentic system:
Connects directly to the RSS feeds, websites, or APIs of key publications
Monitors for relevant mentions 24/7
Automatically builds and delivers client-ready reports, insights, and charts
Adjusts its own searches and reports based on evolving strategy
The result? Fewer people, more insights, faster delivery, and outputs that are fully aligned with your agency’s needs. You own the data. You own the format. You own the process. The SaaS platform? No longer needed.
The Clock Is Ticking
Media monitoring is just one example. This pattern applies across industries and use cases. Whether it’s sales prospecting, financial modeling, HR recruiting, or operational analysis, if it’s a repetitive knowledge task, agentic AI will take it over.
So what should SaaS companies do?
They have two choices:
Integrate agentic capabilities directly into their products – allowing users to define autonomous workflows instead of relying solely on UI-driven use.
Expose their data and capabilities through powerful, agent-friendly APIs – enabling businesses to plug their tools into custom agentic ecosystems.
Failing to do one of these will lead to irrelevance as businesses build the exact tools they need without renewing yet another SaaS subscription.
We’re quickly heading toward a world where building an agent is as common as spinning up a spreadsheet or writing a Zapier automation. It’s not a question of if. It’s a question of how soon.
And for SaaS companies, that future is coming fast — and it won’t wait.