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The SaaS
Benchmark
Annual Report
2026
A data-backed look at what companies actually use: sanctioned apps, shadow apps, and the AI tools taking over our workspace.
Table of Contents
Choose a ChapterExecutive Summary
The year’s biggest stack shifts—and what they mean for governance.
Portfolio Sprawl
How stacks scale, where the growth hides, and why “app count” is no longer a procurement metric.
Shadow IT Audit
What’s actually running in the business—including the AI tools employees adopt first.
Top Apps
The apps that dominate each layer of the stack (and how that changes by company size).
AI Breakout
The AI categories growing fastest, plus the adoption curve that governance can’t ignore.
Browser Wars
Why the browser is becoming the front line for SaaS + AI governance.
Entitlements
Where access drifts, licenses go unused, and identity lifecycle breaks down.
Budget Burn
Where spend escapes the contract—and which categories create the most overage risk.
Uri Haramati
Co-founder & CEO, Torii
The Decentralized
Stack is Now the Default.
Enterprise software has crossed a structural threshold. The modern organization now operates 831 applications on average, but only a fraction of them are truly governed. Over 61% of apps are Shadow IT discovered through usage, browser activity, or direct signup, not procurement.
This isn’t a compliance failure. It’s a market signal.
In 2025, adoption speed became the defining force of the stack. Employees didn’t wait for permission. They adopted what worked. And increasingly, what worked was AI-native.
More than half of the top Shadow IT apps are pure-play AI tools, and nearly 700 new AI applications entered enterprise environments in a single year. These tools didn’t replace legacy software, they layered on top of it, accelerating sprawl while quietly redefining productivity.
What breaks isn’t control, it’s governance models built for a slower era. The data is unambiguous: the browser is now the operating system, AI is the fastest adoption vector we’ve ever measured, and the long tail of the stack is where risk, cost, and innovation collide.
The takeaway isn’t “lock it down.”
It’s redesign governance for a world where software adoption never stops. This report is a map of that world.
Portfolio Sprawl
This chapter breaks down what’s in a modern SaaS portfolio and how it grows as headcount grows. The key point: stacks don’t scale neatly. They compound—especially in the long tail of apps that never touch procurement.
Average Apps per Org
Median Apps per Org
Most benchmarks undercount apps because they only look at what procurement touched. The majority of apps show up elsewhere—browser activity, direct signups, and usage that never becomes a purchase order.
Volume Explosion
App count doesn’t grow linearly with headcount—it accelerates. At enterprise scale, the average portfolio reaches 2,191 apps.
The Individual Employee
Company-wide numbers are useful. But the lived reality is per employee: more tools, more logins, more access pathways, and more places for data to go without oversight.
Apps Per Employee
Across all company sizes, the average employee interacts with 40 apps to do their job. That’s productivity when it’s managed. It’s risk and waste when it isn’t.
The Shadow Iceberg
The “known” stack is the tip. But, the majority lives below the waterline. According to SaaS stack data, only 15.5% of applications are formally sanctioned tools. However, 61.3% of apps are Shadow IT. Used without review, ownership, or lifecycle controls.
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The Endless Sprawl of
Shadow IT AI
Shadow IT isn’t just a procurement gap. It’s the fastest adoption channel in the enterprise—especially for AI. When employees can sign up in seconds, governance needs to move at the same speed.
The Shadow Leaderboard
How to read this table: We treat an app as Shadow IT once it shows up in at least 3% of organizations and is considered shadow by 80% of them. From there, we rank those apps by how widely they’re adopted each month.
The AI-First Shift
In 2025, 26 out of 50 of the top shadow IT apps were pure-play AI tools. The new wave of Shadow apps is AI-native by default.
Top Discovery Sources of Applications
Discovery sources tell the adoption story of how apps enter the business (sanctioned and shadow). The frictionless process of Google social signups accelerate adoption followed closely by manually entering corporate email.
Shadow Categories
Shadow IT adoption tends to cluster around specific capabilites. Productivity, Developer Tools, Design, and Sales and Marketing tools combine for approximately 70% of all shadow apps.
Category Distribution Map
See what's hiding in the shadows.
61% of apps are unmanaged. Find out exactly which ones are running in your environment.
The Category Leaders
In a world of fragmented solutions, the head is still dominated by major players. These are the top 9 applications for each major category based on company adoption.
Category Leaderboard
Pick a category to see the most adopted apps
The Maturity Adjusted Ideal Stack
The “default stack” changes with scale. Choose a company size to see the most common winners by category.
Stack patterns
Cross-cutting add-ons
The AI Breakout
AI apps exploded in 2025. They boosted productivity—and they widened the governance gap. This chapter shows which tools led, how fast adoption moved, and where Shadow IT is most concentrated.
The AI Leaders of 2025
Ranked by AdoptionGovern your AI for the first time.
AI is sprawling through your org and now you can finally do something about it.
LLM Adoption vs. Shadow IT
How to read this chart: Every company uses AI, but the model of choice is in flux.
The higher the blue dot, the higher the adoption rate.
The higher the purple dot, the higher the shadow IT rate.
The Speed of Adoption
Measuring the cumulative adoption of leading LLM models by month (January 2024– December 2025)
App Categories with Higest Rates of AI Use
How to read this chart: This chart measures what percentage of apps fall into different categories overall vs when limited to just AI apps. (🔥 indicates significant AI adoption within the category)
Baseline: % of total app count per category
AI Stack: % of "Pure Play" AI apps per category
As with the Shadow IT categories, we see Productivity, Developer Tools, Design, and Sales & Marketing categories as the top four categories for AI powered apps further indicating the persistent link between AI and Shadow IT.
New AI Apps
Discovered
In 2025, we discovered nearly 700 new AI-native applications—more than double the 2023 baseline.
Browser Wars
The browser has effectively become the operating system. We tracked the three distinct battlegrounds where governance is being decided.
1. Adoption Leaders
Google Chrome dominates, but the "Default Browser" war is settling into a rigid hierarchy.
2. Viral Density
Which browsers have the deepest footprint per company? (Safari & Edge lead corporate installs).
3. The Dark Web
High Shadow IT rates signal a lack of governance. AI browsers like Arc and Zen are entering completely unmanaged.
The Access Gap
Unused licenses and stale access are where spend and risk quietly pile up.
License Utilization Audit
These are the most overbought apps. They have the highest non-utilization rates within the organization. Often high-non-utilization rates are a reflection of a difficult balance within the modern organization between having the right tools available to the right people without purchasing more than is needed.
The Living Dead
Identity decay occurs when users leave or change roles but retain active access. These "Zombie" accounts represent a significant security surface area and wasted budget.
Average percent of license seats
assigned to offboarded users
2.5%
Account Decay by Application
The graveyard of access. We tracked the percentage of active licenses that haven't been utilized in over 90 days across the top SaaS categories.
The Budget Burn
This section presents a focused inventory of the top 12 enterprise apps which most frequently exceed their negotiated contract ceilings. These platforms represent some of the primary drivers of unbudgeted spend.
Top Cost Drivers are AI
The majority of applications that consistently exceed their contracted ceilings are AI-powered. Much of this variance is directly attributable to consumption-based pricing, highlighting the specific dynamic driving the "budget burn."
The Overage Frequency
For applications that result in expenses exceeding contracts, frequency matters. This chart shows how often a given app's expenses exceed the contracted amount.
Overage Intensity
Each stack represents the median overage percentage. The higher the stack, the greater the median financial cost exceeding the contract. For most applications, overages are moderate, but some select, AI-powered apps can leave a significant scorch mark on the budget.
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