In my first blog post last week, I talked about why I joined Citrix and what I’m excited about—especially around how AI is reshaping the workplace.
This week, I’m setting the stage for the months ahead. AI is here, it’s evolving quickly, and it’s way bigger than just IT. Over the coming months, I’ll be exploring a framework for how leaders can think about what’s happening and where it’s going.
I’ll kick things off today with a post based on an expanded conversation Shawn Bass and I shared on stage at Citrix UNITE last month. Let’s start with the obvious:
For most of our lives, AI was a future science fiction concept or limited to narrow use cases like machine learning or big data analysis. Then ChatGPT came out, and almost overnight we found ourselves in actual serious conversations about whether AI would take our jobs or when AGI would hit.
Today, most leaders agree that AI is going to be a big deal. The only debate is how big and how soon. For every exec who thinks AGI is only three years away, there’s another who believes AI is the most overhyped tech in history.
Regardless of your own long-term view, there’s one thing most of us can agree on: AI has already entered the workplace. Millions of workers are using AI today—in their browsers, workflows, and meetings. And in most cases, they didn’t get these tools from IT. They found them on their own.
This shadow IT scenario is the real story of AI in the workplace today.
Your workers don’t care about AI ROI, the Gartner Hype Cycle, or whatever the AI accelerationist nerds are arguing about on their latest 4-hour podcast. They care about getting work done faster, better, and with less hassle. And with each passing day, they’re getting better at figuring out how to use AI to do it.
While many leaders are still debating “AI strategy” in the abstract, the ground is shifting under them as their workers have already started running towards an AI-enhanced future.
So how do we frame this impact in a useful way?
I start by thinking about what workers do. Not their job titles or the latest tools, but the individual tasks that make up their day. Every job is just a bundle of tasks. Some are simple. Some are complex. Some happen all the time. Others rarely. Bundles of tasks then roll up into workflows, decisions, and deliverables, but at the core, jobs are just people doing tasks.
This is where AI is showing up—in the task itself.
Workers aren’t thinking about strategic AI transformation. They’re looking at the task in front of them and asking: “Can AI help with this?” Sometimes the answer is no. But more and more, there’s a way they can use some kind of AI to speed things up, improve the quality, or do the annoying part. Each of these micro-interactions is small, but taken together, they’re reshaping how knowledge work gets done.
This isn’t about top-down AI projects or shiny copilots. It’s workers figuring out—one task at a time—how AI can help them think smarter and move faster.
The companies who win will be the ones who embrace this shift and help their workers get good at it.
Right now, most AI in the workplace is passive. It’s a tool a worker accesses by typing into some window that helps them write or summarize a doc. The human worker is an active participant in the process by copying and pasting the AI’s output into the real workflow.
But this method of interaction is changing quickly.
New AI tools are emerging that can view screens, click buttons, navigate apps, and simulate keyboard and mouse input. In the future, we’ll look back at today’s text-based chat interfaces the way we look back at DOS prompts—cutting edge in their day, but comically clunky compared to what came next.
Once AI can reliably use a computer or browser the way a human does, it will shift from passive assistant to active helper. This will unlock an entirely new kind of workplace automation. For example, I dream of the day when I can say, “Hey AI, do my expenses,” and never think about it again.
But for that to happen, the AI tool needs to reliably:
That’s not some crazy sci-fi ask. It’s just navigating a few systems that all converge on my desktop in my user context. Once AI can automatically wake up and do this on its own, I’ve just created something new—a task-level automation that runs on my behalf. I’ve created an AI-powered micro-application.
I can think of dozens of these I’d want to create, as will every other worker. These workers won’t need to be software developers or power users—they’ll just need to know what they want done and how to explain it in plain language. Suddenly every company will be made up entirely of accidental citizen developers!
Now imagine every employee creating five or ten of these. The IT department of an F500 company would need to deal with hundreds of thousands of new apps doing who-knows-what.
This is not some distant future. Early versions of these computer-using AI tools are being previewed by all the major AI players. While they’re extremely limited today and filling social media feeds with their “dumb” mistakes, the pace of progress is fast. At some point they’ll be “good enough” for workers to try, first slowly and then suddenly, and companies need to be ready.
This is the real future challenge of AI in the workplace. It’s not today’s chat—it’s the flood of worker-created AI-powered automations running quietly and constantly. That’s the world we need to prepare for.
By now it’s clear: AI isn’t something you can contain with policies or block with memos. It’s here. It’s moving fast. And it’s reshaping how work gets done. We’ve moved on from “Should we allow our workers to use AI?” to “How do we give them the benefits of AI without losing control?”
This is where it gets tricky: Security. Compliance. Governance. Auditability. These remain critical and yet can be completely broken by AI used by workers in this way. You can’t manage this with your SaaS playbook, and you can’t spend six months building a strategy when the tech is evolving by the week. We’re headed towards a reality where real work is done by AI-powered automations created by workers, operating across enterprise systems in a way that looks more like humans than traditional software.
This is where our thinking at Citrix comes in. For decades, we’ve helped companies balance freedom and control—enabling secure access to apps, desktops, and data from anywhere, while keeping security, governance, and policy intact.
That mission hasn’t changed. But what’s changing is who—or what—is doing the work.
As more AI agents and AI-powered automations do more work alongside and instead of human workers, these tools need the same guardrails we’ve always provided for human workers: consistent access, visibility, and control at the workspace level.
This isn’t just an IT challenge. It’s a challenge for the workforce, for operations, and for leadership. We believe it’s solvable, but we have to start preparing now.
Everything I’ve covered today—bottom-up adoption, worker-led automations, and evolving task patterns—is starting to happen in real workplaces. But we’re still early in this shift.
As leaders, it’s time to start thinking about new questions:
These questions are just the tip of the iceberg and the types of conversations we’re having with customers when we talk about how we’re securing the future of work. These are also the topics I’ll be exploring in this blog in the coming months. Some posts will be technical. Some will be strategic. But all will help leaders understand and navigate the workplace shift that’s already underway.
The bottom line is we can’t wait for the “AI future” to arrive before we start seriously thinking about it. We’re already living with the early phases today, and the rest will be here in the blink of an eye. The companies who embrace this shift while supporting their people will be the ones who win.
We’re here to lead and be part of that conversation, and I can’t wait to dig in.
Join the conversation and discuss this post on LinkedIn or Bluesky. You can find all my posts on my author page on the Citrix blog (or via RSS).
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