As we stand on the brink of a technological revolution, I’m thrilled to sit down with Marco Gaietti, a veteran in business management with decades of experience in strategic management, operations, and customer relations. Marco has witnessed firsthand the evolution of technology in business and offers unparalleled insights into the seismic shift from traditional applications to AI-driven agentic systems. Today, we’ll explore how AI agents are transforming the way we interact with software, reshaping industries like healthcare, altering power dynamics between users and software companies, and redefining business operations across the board. Let’s dive into this fascinating conversation about the future of technology and work.
Can you explain what you mean by the transition from the ‘application era’ to ‘agentic speed’ and why it’s such a game-changer?
Absolutely. The ‘application era’ was all about humans interacting directly with software—think clicking through apps, navigating menus, and managing multiple tools to get things done. It was user-driven and often time-consuming. Now, with ‘agentic speed,’ AI agents take over that interaction. These agents can navigate software on our behalf, execute tasks across platforms, and deliver results without us ever touching a button. It’s a game-changer because it slashes the time and effort we spend on mundane tasks, letting us focus on higher-level thinking and decision-making. This shift fundamentally changes productivity, both for individuals and businesses, by automating the grunt work at an unprecedented scale.
How does this shift change the way people engage with technology in their everyday lives?
It’s transformative. Instead of wrestling with multiple apps or interfaces, people can simply tell an AI agent what they need—whether it’s scheduling a meeting, pulling data from a report, or even handling personal tasks like booking travel. The agent figures out the ‘how,’ navigating the necessary tools behind the scenes. This makes technology feel less like a tool we have to master and more like a seamless assistant that anticipates and acts. It’s less about learning software and more about expressing intent, which lowers the barrier for everyone, from tech-savvy users to those who struggle with digital interfaces.
Can you share an example of a task that once needed a specific app but can now be managed by an AI agent?
Sure, take something as common as managing expenses. Previously, you’d download an app, manually input receipts, categorize expenses, and submit reports by clicking through endless forms. Now, an AI agent can handle all of that. You just upload a photo of a receipt or give a voice command, and the agent logs into the expense software, categorizes the data, and submits the report without you ever opening the app. It’s a small example, but it illustrates how agents eliminate the friction of manual interaction across countless daily tasks.
You’ve talked about AI agents navigating software for us. Can you break down how this actually works in practical terms?
In practical terms, AI agents act like virtual employees who understand and operate software interfaces just as a human would, but faster and with greater precision. They use advanced algorithms, often powered by machine learning and computer vision, to ‘see’ and interact with web-based platforms or applications. They can click buttons, fill out forms, and extract data by interpreting the structure of a user interface, even if there’s no direct integration like an API. This means they can work with almost any existing software, adapting to changes in real time, and execute complex workflows without human oversight.
Why is healthcare such a pivotal area for testing and implementing AI agents?
Healthcare is a perfect proving ground because it’s one of the most challenging environments for software. The industry is riddled with fragmented systems—think hundreds of different electronic health record platforms that don’t talk to each other, plus endless paperwork and regulatory constraints. Clinicians spend hours on administrative tasks like charting or billing instead of focusing on patients. If AI agents can navigate this mess successfully, as we’re seeing with some innovative tools, it proves they can handle complexity and high stakes in any sector. Healthcare’s pain points make it the ultimate stress test for agentic technology.
How do AI agents address some of the specific inefficiencies in healthcare compared to traditional software solutions?
Traditional software in healthcare often creates more problems than it solves—rigid interfaces, poor interoperability, and constant manual input. AI agents tackle this by acting as an intelligent layer on top of existing systems. For instance, they can take a finalized clinical note and insert it directly into the right fields of an electronic health record, mimicking human navigation but with flawless accuracy. They don’t need IT approvals or vendor partnerships to integrate; they just work with what’s there. This cuts down hours of administrative burden, letting healthcare providers prioritize patient care over paperwork.
You’ve mentioned a changing power dynamic between users and software companies. Can you elaborate on what that looks like?
Certainly. In the past, software companies held most of the power—users had to adapt to their interfaces, pay per seat, and deal with high switching costs if they wanted to move to a competitor. With AI agents, that dynamic flips. Agents act as intermediaries, prioritizing outcomes over brand loyalty. If a better system comes along, an agent can switch platforms instantly without the user even noticing. This forces software companies to focus on delivering measurable results rather than locking users into their ecosystem through complex interfaces or training needs. It’s a shift toward user empowerment.
What impact do you foresee this agentic revolution having on industries beyond healthcare?
The impact will be massive across the board. Take finance, for example—CFOs could stop manually navigating expense or budgeting software as agents handle data entry, analysis, and reporting. In HR, managers might never touch payroll or benefits systems again; agents can process forms and answer employee queries. Sales teams could skip updating CRMs, with agents logging interactions and generating insights automatically. Any industry with repetitive software tasks—and that’s most of them—stands to gain from agents reducing human friction, letting professionals focus on strategy and relationships rather than administrative minutiae.
You’ve described this as a ‘market earthquake’ for software-as-a-service companies. What are the biggest hurdles they face in adapting to this new reality?
SaaS companies are in for a rough ride. Their traditional model—charging per user seat and relying on sticky interfaces—is crumbling. When agents become the primary users, pricing must shift to outcomes or usage, not headcount, which squeezes margins for companies built on human interaction. Plus, agents reduce switching costs to near zero, so customer loyalty isn’t guaranteed anymore. The biggest hurdle is rethinking their value proposition: they’ll need to prioritize reliability, auditability, and seamless agent interaction over flashy user interfaces, or risk becoming obsolete in a world where humans aren’t the ones clicking.
Looking ahead, what’s your forecast for the role of AI agents in shaping the future of work and technology?
I believe AI agents will redefine work and technology entirely within the next decade. We’re moving toward a world where software navigation becomes invisible—agents will handle the operational side of nearly every business function, from admin to analytics. This will free up humans to focus on creativity, strategy, and interpersonal connections, fundamentally changing job roles. Technology will evolve from tools we operate to systems that anticipate and act on our behalf. The challenge will be ensuring trust, security, and ethical boundaries as agents take on more responsibility, but the potential for efficiency and innovation is limitless.
