Every company has the same story. Someone signs up for Slack because the old email chains were too slow. A different department keeps Microsoft Teams because that came with the office software. The support team adds a ticketing tool with its own chat. Nobody ever goes back to clean it up.
That habit has quietly become expensive. Research shows the average organization now runs anywhere from about 150 apps at smaller companies up to more than 600 at large enterprises, a huge jump from fewer than 20 apps back in 2017. Executives at systems integrator Blue Mantis and analysis firm ISG both point to this same pattern: companies buy collaboration tools one at a time to solve a small problem, without ever stepping back to ask whether they already own something that does the job.
The cost of that habit is not abstract. One widely cited estimate puts the price of scattered, hard-to-find company knowledge at 31.5 billion dollars a year across Fortune 500 companies alone. A separate study found that a large majority of companies now run two or more separate chat platforms at once, which forces employees to constantly hunt across systems for the same piece of information.
The toggling itself eats real time. Research tracking desktop activity found workers switching between apps and windows more than a thousand times a day, adding up to several hours a week lost to nothing but jumping between tools and re-finding context. None of that time shows up on a budget line, which is exactly why it never gets fixed.
The problem gets sharper during a crisis. When a system goes down or a customer has an urgent issue, teams that have to piece together what happened from alerts in one tool, tickets in another, and chat messages in a third take longer to fix the problem. Every extra minute of downtime during an outage costs real money, and tool-hopping is a direct cause of that delay.
Now add AI into the mix, and the sprawl problem changes shape. Company AI assistants are only as good as the information they can see. When that information sits scattered across a dozen disconnected chat tools, ticketing systems, and shared drives, the AI either misses important context or has to be manually fed it, which drives up the cost of running it while making it less reliable.
This is turning platform cleanup from a nice-to-have into a requirement. Companies planning to roll out AI assistants across their workforce will get a poor return on that investment if their underlying information stays fragmented. The fix is not another app: it is picking one hub for communication, retiring the duplicates, and making sure whatever AI tool comes next can actually see everything happening across the business.
For any company sitting on a pile of messaging tools accumulated over the years, the message is straightforward. The cleanup pays for itself twice: once in the time employees stop wasting jumping between apps, and again in the AI tools that finally work properly once they can see the whole picture.