Work Sprawl is the silent killer of productivity, innovation, and morale in today’s workplace, often rooted in disconnected tools and processes. I’ve lived it, led through it, and—most importantly—learned how to fight it. In this piece, I want to share my journey with Work Sprawl, the hidden costs I’ve uncovered, and why I believe the future of work depends on unified workspaces and AI that actually works for people.
Summarize this article for me pleaseWhat Is Work Sprawl? My Personal View
When I started leading B2B marketing and sales development teams, I thought the biggest challenge was simply managing costs—ensuring we weren’t overspending on tools. But over the years, I realized that the real problem was much deeper and more insidious.
What I was really up against was Work Sprawl—something I now define as the fragmentation of work across too many disconnected tools, systems, and processes. It’s when your teams switch between platforms, lose context, and spend more time updating each other than actually getting work done.
The impact on productivity was undeniable. Teams slowed down, duplicated efforts, and spent more time aligning than executing. Information was scattered, collaboration became fragmented, and projects lost momentum before they even got going.
The four faces of Work Sprawl
1. Application Sprawl
This is where it all started for me. I remember walking into a new role and discovering that our team was using dozens of different tools—many of which did the same thing, or worse, didn’t do anything at all. We were paying for shelfware, and the CFO was (rightly) frustrated. But the cost wasn’t just financial. The lack of integration led to fragmented work and loss of alignment—classic signs of work sprawl.
2. Context Sprawl
This one hit me hardest as a leader. I’d try to get a clear picture of what my teams were working on, but I found that information was scattered across Google Docs, Slack, email threads, and project management tools. There was no single source of truth. I was constantly “stitching together” a narrative—a result of fragmented tools that lacked Convergence by design. I lost visibility, and my teams lost the context needed to do their best work.
3. Process Sprawl
I’ve seen this break even the best teams. When every group uses its own tools and workflows, there’s no unified process. I’ve watched teams try to “jigsaw” their processes together, only to end up with inefficiencies, confusion, and missed opportunities for collaboration. It’s a perfect example of what causes Work Sprawl: siloed tools, misaligned teams, and rushed decisions.
4. AI Sprawl
This is the newest—and fastest-growing—challenge. In the rush to adopt AI, I’ve seen organizations (including my own) collect a patchwork of AI tools that solve tiny problems but don’t connect to the bigger picture. These tools quickly become shelfware, just like the SaaS tools before them. Worse, when AI isn’t integrated with real context, it produces bad outputs and erodes trust—a hidden cost that most teams don’t recognize until adoption drops.
Summarize this article for me pleaseThe Hidden Costs: What Most Leaders Miss
I used to think the main cost of sprawl was a line item in the budget. But the real costs are hidden—like the iceberg beneath the water.
Morale and innovation
When people don’t have context, they feel siloed and disengaged. I’ve watched top performers “brute force” their way to get the necessary information—setting up extra meetings, chasing down colleagues, and piecing together insights. But not everyone can do that, and it’s exhausting even for those who can.
Productivity drains
A stat that sticks with me: the average knowledge worker toggles between apps and websites nearly 1,200 times a day, spending over four hours each week just reorienting themselves. I’ve seen this firsthand—people copying and pasting, duplicating work, and losing hours every week to “double work”—a kind of digital spatial mismatch between information and execution. It’s not just inefficient; it’s demoralizing.
AI without context is useless
I’ve seen so many AI projects fail because they lack context—especially in fast-moving technology companies where teams rely on precision and clarity. If your AI doesn’t know your brand guidelines, sales methodology, or the nuances of your business, it’s just generating noise. And once people lose trust in AI, adoption plummets.
Summarize this article for me pleaseHow I’m Solving Sprawl at ClickUp
Convergence: The power of a Converged AI-powered Workspace
The big unlock for me was realizing that Convergence—bringing apps, processes, people, knowledge, and AI together in one place—changes everything. At ClickUp, we’re building a workspace where context isn’t lost, processes are mapped, and AI is truly integrated.
Work Sprawl often starts with scattered notes and half-remembered ideas that never make it back into the system of record.
That’s why we use features like Talk to Text in ClickUp Brain Max—it bridges that gap by capturing thoughts the moment they surface and turning them directly into tasks, docs, or reminders—no typing, no chasing context—just seamless knowledge capture that keeps work moving forward.
With Brain embedded natively, I don’t just see my work converge—I see intelligence woven into it. Need to draft a brief, summarize a doc, or automate a workflow? It happens inside the same system where the work lives.
Personal anecdote: The AI Notetaker
One of the most transformative tools for me has been the ClickUp AI Notetaker. I can’t attend every meeting, but with the AI Notetaker, I don’t have to. It captures the discussion, summarizes key points, and shares context with everyone who needs it. I remember missing a critical product meeting, and like many, adapting to remote work, I simply reviewed the AI-generated summary instead of chasing down notes or a recap. I was instantly up to speed and able to make decisions without delay.
Documenting and sharing knowledge
I’ve learned the hard way that the most valuable context is often trapped in people’s heads. I push my teams—and myself—to take 20 minutes to write things down. It’s not easy, but it’s essential. When we document our learnings, processes, and insights, we create a shared repository that benefits everyone.
Summarize this article for me pleaseLeadership Lessons: What I Tell Every Executive
1. Map your processes
You can’t automate what you haven’t mapped. Take the time to document how work gets done—then look for ways to streamline and automate.
2. Prioritize context
Make it easy for people (and AI) to access the information they need. Centralize knowledge, standardize documentation, and break down silos.
3. Integrate AI thoughtfully
Don’t chase shiny objects. Invest in AI that’s deeply integrated with your workflows and context—not just another point solution.
Additionally, to get the most out of AI, it’s important to choose tools that adapt to your team’s needs and workflows. With ClickUp Brain, you can switch between large language models (LLMs) to personalize your AI experience. This flexibility ensures that the AI you use is not just a generic solution, but one that’s tailored to your unique context and goals.
4. Lead cultural change
Transformation isn’t just technical—it’s cultural. Model the behaviors you want to see: transparency, documentation, and a willingness to change.
Summarize this article for me pleaseThe Future of Work: My Vision
I believe the future belongs to organizations that solve Work Sprawl—not just by cutting costs, but by building cultures of clarity, collaboration, and continuous improvement. Integrated AI agents, unified workspaces, and a relentless focus on context will free people to do their best, most creative work. This is the power of a Converged AI Workspace—not just bundling tools, but rebuilding work itself around a single, intelligent platform.
Work Sprawl doesn’t solve itself. It slows your teams, clouds your strategy, and costs more than you can track. It’s time to lead with clarity—start by trying what we’ve built to fight it.
Everything you need to stay organized and get work done.
