Digital fragmentation is the hidden issue no one talks about when it comes to AI adoption, and it’s the reason so many projects fail before they ever get off the ground.
At its core, digital fragmentation means your systems, applications, and data don’t talk to each other. It’s what happens when decades of point solutions, disconnected platforms and departmental software purchases leave you with a complex, patchworked tech stack: one that’s impossible to scale, automate or optimize without serious rework.
3 Tips to Resolve Digital Fragmentation for AI
- Understand your architecture and digital processes to get your data to talk to each other.
- Create an integration and automation strategy.
- Adopt a robust integration platform that can connect applications, databases, APIs and AI.
If you don’t solve digital fragmentation, AI won’t work no matter how advanced your model or how generous your budget is.
Let me explain why.
Why Digital Fragmentation Is a Problem
Software companies don’t talk to each other. It’s worth asking how we got to a point where our most critical systems don’t interact well. The answer is, mainly through good intentions and unintended consequences.
To unpack these unintended consequences, just for fun, I asked a child of the digital transformation era — ChatGPT — to define the term as well. It responded:
“Digital transformation is the process of utilizing digital technologies to fundamentally change business operations, customer experiences, and value delivery. It’s about integrating digital technology into all areas of a business, leading to significant improvements in efficiency, value, and innovation. This transformation reshapes how organizations engage with their customers, stream- line processes, and compete in the digital age.”
Digital transformation might be an abstract concept, but it’s another way to describe innovation that helps humans progress.
The pandemic got the attention of businesses that hadn’t already been thinking digitally. It exposed the widespread lack of digital preparation, and organizations frantically rushed to catch up. In April 2020, Microsoft CEO Satya Nadella famously said the company had “seen two years’ worth of digital transformation in two months” as cloud adoption exploded. With the best intentions, businesses loaded up innovative cloud applications and services like kids in a candy store. The goal was to become more agile and provide the “easy button” experiences customers demanded.
Then came the unintended consequences.
Those systems created digital silos, walled gardens obscuring essential data, application sprawl and technology complexity. Disconnected architecture became the norm. The newer, cloud-based systems had difficulty communicating with one another, and with the critical legacy systems still humming along in data centers, applications and data sources were everywhere. Connecting and synchronizing them became a monumental challenge. Here are numbers that show the scope of this digital fragmentation:
- One study determined that larger organizations (2,000 or more employees) deployed an average of 231 applications in 2024 – an increase of 10 percent from the previous year.
- Dwarfing that data point was another recent survey that found organizations, on average, use 342 SaaS applications. It also determined that the typical business department relies on about 73 apps.
- Yet another study revealed that 79 percent of organizations have more than 100 different data sources, and 30 percent use more than 1,000 sources.
These findings likely underestimate the scope of the problem. As applications have become easier to purchase, it’s increasingly common for business units to avoid the delays associated with over-worked and understaffed technical teams. They just implement what we often refer to as shadow IT. They deploy apps independently, often without the technical teams knowing what’s embedded within the company architecture. It’s not exactly going rogue, but that lack of oversight can introduce a multitude of risks in the form of security gaps, duplication of systems, inaccessibility and other negative repercussions for the business.
But these problems are solvable. In fact, a new sense of urgency is forcing every organization to finally address these issues. If businesses can overcome the fundamental challenge of connectivity that has long thwarted their digital transformation ambitions, they will also set the stage for success in the AI era, or they will be left behind. It’s that simple.
How to Solve Digital Fragmentation for AI
If you’re waiting for the AI economy to arrive, you missed the launch. It’s already here. There’s a reason why the world’s most valuable technology companies are heavily involved with AI. It all comes back to connectivity. Integration and automation are the keys to eliminating digital fragmentation and preparing your business for AI.
AI-readiness requires understanding your architecture and processes, getting your applications finally talking to one another and ensuring your data is accessible. If you don’t accomplish that first, pretrained generative transformers, large language models and everything else AI will become just more “stuff” in your overly complex tech stack. You won’t see the business value. Instead, you will fall behind your competitors — some of whom might not yet exist.
In an environment of innovative unpredictability, the best way to prepare for changes you can’t predict is to become as nimble, agile, and flexible as possible to be ready when they burst onto the scene. Connectivity does that. An integration and automation strategy that’s thoughtful and balanced allows you to adapt to technological advances perpetually. The best opportunity to participate in the radical reshaping of the future is when you can:
- Connect everyone to everything.
- Tame technology fragmentation and complexity.
- Finally, digitally transform your operations.
- Increase business speed, agility, and flexibility.
- Enable the practical use of AI solutions.
Solving problems caused by disconnection, fragmentation and complexity requires a universal translator for technology systems that can integrate applications, databases, APIs and AI.
Over the past decade or so, tools have emerged that help integrate and automate the systems that are critical to your business operations. Known as integration platforms as a service (iPaaS), these tools simplify the complex task of connecting different systems, enabling smoother workflows and more efficient processes.
At its core, iPaaS connects essential systems and data within your organization so they work together seamlessly. iPaaS not only automates workflows but also plays a critical role in successful digital transformation. As AI becomes more integral to business operations, having a robust integration platform will help future-proof your organization.
This is the direction I want to guide you toward. My point here is this: Connectivity is the key to overcoming digital fragmentation and achieving true transformation.
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Excerpted with permission from the publisher, Wiley, from Digital Impact: The Human Element of AI-Driven Transformation by Steve Lucas. Copyright © 2025 by Boomi, LP. All rights reserved. This book is available wherever books and eBooks are sold.
