The SaaS Benchmark Annual Report 2026 | Torii

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Table of Contents

Choose a Chapter

CH 00\ Executive Summary \ The year’s biggest stack shifts—and what they mean for governance. CH 01\ Portfolio Sprawl \ How stacks scale, where the growth hides, and why “app count” is no longer a procurement metric. CH 02\ Shadow IT Audit \ What’s actually running in the business—including the AI tools employees adopt first. CH 03\ Top Apps \ The apps that dominate each layer of the stack (and how that changes by company size). CH 04\ AI Breakout \ The AI categories growing fastest, plus the adoption curve that governance can’t ignore. CH 05\ Browser Wars \ Why the browser is becoming the front line for SaaS + AI governance. CH 06\ Entitlements \ Where access drifts, licenses go unused, and identity lifecycle breaks down. CH 07\ 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.

831

Avg Apps Per Org

61.3%

Shadow IT Volume

Chapter 01Portfolio Sprawl

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

0

Median Apps per Org

0

Data Insight

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.

01

Volume Explosion

App count doesn’t grow linearly with headcount—it accelerates. At enterprise scale, the average portfolio reaches 2,191 apps.

Average vs Median Portfolio Size

Avg

Med

448

392

Startup

679

615

Small

1189

1157

Mid-size

1250

1335

Large

2191

2323

Enterprise

02

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.

Global Benchmark

40

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.

03

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.

Need to Close

In Review

Approved

Blocked

Shadow IT61.3%

Need to Close1.5%

In Review4.6%

Approved15.5%

Blocked17.1%

Discovered (Shadow)61.3%

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Chapter 02Shadow IT Audit

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.

Avg Shadow IT Rete per Org61.3%

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.

52%

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.

01

Google Workspace

Social Signup + SSO

02

Torii Extension

Email Signup Detection

03

Expenses

Shadow Spend Detection

04

Microsoft Intune

MDM Enrollment

05

Slack

OAuth Integrations

06

Iru

Apple & Fleet MDM

07

Entra ID

Active Directory Identity Logs

08

Jamf

macOS Device Management

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.

Productivity23%

Developer Tools16.3%

Design15.7%

Sales & Marketing14.3%

Operations11.8%

IT & Security6.9%

Human Resource5.6%

Analytics & BI2.6%

Project Management1.9%

Customer Success1.2%

Finance0.7%

Critical (21+)

High (13–20)

Mid (6–12)

Low (1–5)

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Chapter 03Top Apps in the Stack

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

Analytics & BICustomer SuccessDesignDeveloper ToolsFinanceHuman ResourceIT & SecurityOperationsProductivityProject ManagementSales & Marketing

1Tableau

70.5% Adoption

2Grafana

65.2% Adoption

3Power BI

61.4% Adoption

4Hotjar

59.9% Adoption

5Snowflake

51.5% Adoption

6Fivetran

48.5% Adoption

7Supermetrics

47.1% Adoption

8Google Analytics

45.6% Adoption

9Mixpanel

43.0% Adoption

The Maturity Adjusted Ideal Stack

The “default stack” changes with scale. Choose a company size to see the most common winners by category.

Startup

<100 Empl. Small

100-499 Empl. Mid-Market

500-1.5k Empl. Large

1.5k-4k Empl. Enterprise

4k+ Empl.

Showing: ✕

🔑Identity & Access

Microsoft Entra IDCisco Duo

SSO + MFA anchors access

🏢Workplace Suite

Microsoft 365Google Workspace (G Suite)Microsoft OutlookMicrosoft OneNote

Email, docs, calendar backbone

💬Chat & Meetings

Microsoft TeamsZoomWebEx

Meetings and internal coordination

📚Content & Knowledge

SharepointOneDriveConfluenceGoogle Drive

Files, intranet, and team knowledge

✅Work Management

JiraMiroAsanamonday.comSmartsheet

Projects, tickets, and execution

👥HR

Workday HCMCoursera

Employee system of record

💰Finance & Spend

Concur

Expenses and travel controls

📈Revenue (CRM)

SalesforceLinkedInZoomInfo

Pipeline and account management

🎧Customer Support

Zendesk

Tickets and service workflows

💻Endpoint Mgmt

Microsoft IntuneCitrixVMware

Devices and virtual workspace

⚙️Engineering & DevOps

GitHubVisual StudioPostmanDocker HubSonarQube

Build, ship, and maintain software

☁️Cloud Platforms

Amazon Web Services (AWS)Microsoft AzureGoogle Cloud

Core infrastructure and cloud services

Stack patterns

Microsoft gravity

Entra + M365 + Intune form a strong “operating spine,” even when Google Workspace is also present.

Meetings are multi-tool

Teams + Zoom are both central, and WebEx remains broadly embedded in enterprise workflows.

Work execution is layered

Jira is the execution hub, with Miro and multiple PM tools (Asana/monday/Smartsheet) coexisting.

Multi-cloud, uneven depth

AWS and Azure are broadly deployed; GCP is common but typically smaller footprint.

AI is still a pilot phase

Claude/Copilot show up widely, but usually with comparatively thin seat depth versus the org size.

Cross-cutting add-ons

Security/Privacy

OneTrustProofpoint

Privacy controls and protection

Automation

ZapierPower Automate

Workflow glue between tools

Agreements

DocuSign

Approvals and signatures

AI Assistants

Claude AIMicrosoft Copilot

Pilot-scale productivity support

Data & Analytics

TableauDatabricks

Dashboards + data platform

Design & Creative

Adobe AcrobatFigmaAdobe Creative Cloud

Docs + design production

Chapter 04The AI Breakout

Artificial Intelligence

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 Adoption

1

ChatGPT

Productivity

Adoption Rate95.3%

2

Zapier

IT & Security

Adoption Rate93.9%

3

Grammarly

Productivity

Adoption Rate93.3%

4

OpenAI

Productivity

Adoption Rate90.9%

5

Claude AI

Productivity

Adoption Rate88%

6

Read AI

Operations

Adoption Rate81%

7

Cursor AI

Developer Tools

Adoption Rate79.5%

8

Gong

Sales & Marketing

Adoption Rate78.7%

9

Fireflies.ai

Sales & Marketing

Adoption Rate78.4%

Fast Movers (Ranks 10-100)Scroll to view

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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.

Adoption

Shadow IT

ChatGPT

Adoption95%

Shadow IT28%

Claude AI

Adoption88%

Shadow IT49%

DeepSeek

Adoption67%

Shadow IT66%

Grok

Adoption65%

Shadow IT76%

Gemini Code Assist

Adoption61%

Shadow IT73%

Mistral AI

Adoption40%

Shadow IT70%

Google Gemini

Adoption23%

Shadow IT55%

The Speed of Adoption

Measuring the cumulative adoption of leading LLM models by month (January 2024– December 2025)

ChatGPT98%

Claude AI90%

DeepSeek67%

Grok64%

Gemini Code Assist61%

Mistral AI40%

Google Gemini23%

0%25%50%75%100%

DeepSeek

Disruption

Historical Milestone: January 2025 The release of DeepSeek-V3 shattered the Western "Compute Moat," proving state-of-the-art LLMs could be trained at a fraction of the cost. This triggered a global spike in shadow adoption.

Jan 24 Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec Jan 25 Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

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

Market Shift Analysis

BASELINEAI STACK PRODUCTIVITY 7.9%🔥 PRODUCTIVITY 16.8% DEVELOPER TOOLS 12.2% DEVELOPER TOOLS 15.3% SALES & MARKETING 16.2% SALES & MARKETING 14.1% DESIGN 4.9%🔥 DESIGN 11.3% OPERATIONS 15.3% OPERATIONS 9.9% ANALYTICS & BI 6.1% ANALYTICS & BI 9.6% IT & SECURITY 16% IT & SECURITY 7.9% CUSTOMER SUCCESS 3.9% CUSTOMER SUCCESS 7.6% HUMAN RESOURCE 8.5% HUMAN RESOURCE 3.6% FINANCE 6.1% FINANCE 2.7% PROJECT MANAGEMENT 3.1% PROJECT MANAGEMENT 1.2%

Data Insight

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.

694In 2025

11

2020

24

2021

59

2022

317

2023

436

2024

694

2025

Chapter 05Browser Wars

Browser Wars

The browser has effectively become the operating system. We tracked the three distinct battlegrounds where governance is being decided.

view: adoption_leaders

1. Adoption Leaders

Google Chrome dominates, but the "Default Browser" war is settling into a rigid hierarchy.

Google Chrome

82% Adoption

#1

Firefox

55% Adoption

#2

Microsoft Edge

54% Adoption

#3

Opera

47% Adoption

#4

Brave

45% Adoption

#5

ChatGPT Atlas

43% Adoption

#6

DuckDuckGo

38% Adoption

#7

Vivaldi

34% Adoption

#8

Apple Safari

19% Adoption

#9

Arc

17% Adoption

#10

Zen Browser

16% Adoption

#11

Comet Browser

12% Adoption

#12

view: user_density

2. Viral Density

Which browsers have the deepest footprint per company? (Safari & Edge lead corporate installs).

Google Chrome

618 Avg Users

#1

Apple Safari

471 Avg Users

#2

Microsoft Edge

370 Avg Users

#3

Firefox

120 Avg Users

#4

Arc

17 Avg Users

#5

Brave

11 Avg Users

#6

ChatGPT Atlas

11 Avg Users

#7

Comet Browser

9 Avg Users

#8

Opera

4 Avg Users

#9

DuckDuckGo

3 Avg Users

#10

Vivaldi

2 Avg Users

#11

Zen Browser

2 Avg Users

#12

⚠️ alert: shadow_risk_detected

3. The Dark Web

High Shadow IT rates signal a lack of governance. AI browsers like Arc and Zen are entering completely unmanaged.

Zen Browser

96% Risk Score

#1

Vivaldi

87% Risk Score

#2

Comet Browser

86% Risk Score

#3

ChatGPT Atlas

81% Risk Score

#4

DuckDuckGo

80% Risk Score

#5

Opera

70% Risk Score

#6

Brave

65% Risk Score

#7

Arc

58% Risk Score

#8

Firefox

55% Risk Score

#9

Microsoft Edge

52% Risk Score

#10

Apple Safari

46% Risk Score

#11

Google Chrome

33% Risk Score

#12

Chapter 06Entitlements & Identity Decay

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.

55%

Salesforce

45%

PagerDuty

40%

monday.com

39%

Iru

35%

Zendesk

33%

1Password

32%

Zoom

30%

Adobe

28%

Atlassian

27%

DocuSign

25%

Calendly

24%

Slack

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.

62%

Crunchbase

56%

Seamless.ai

55%

MapBox

51%

UserVoice

51%

Owler

51%

Mailchimp

48%

6sense

47%

Vendr

46%

AON Radford

46%

Helm

44%

Frontend Masters

43%

Nightfall

39%

Wix

39%

Sisense

37%

Fivetran

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."

#01Zoom

#02ChatGPT

#03Snowflake

#04Fivetran

#05OpenAI

#06Cursor AI

#07Iru

#08Claude AI

#09Keeper Security

#10n8n

#11Anthropic

#12ClickUp

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.

30.1%

#01Zoom

35.4%

#02ChatGPT

21.7%

#03Snowflake

29.4%

#04Fivetran

22.5%

#05OpenAI

23.7%

#06Cursor AI

18.9%

#07Iru

25%

#08Claude AI

33.3%

#09Keeper Security

33.3%

#10n8n

20%

#11Anthropic

33.3%

#12ClickUp

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.

7.4%

#01Zoom

13%

#02ChatGPT

1.7%

#03Snowflake

6.1%

#04Fivetran

6.8%

#05OpenAI

20.5%

#06Cursor AI

3.5%

#07Iru

2.8%

#08Claude AI

4.6%

#09Keeper Security

0.3%

#10n8n

9.1%

#11Anthropic

7.1%

#12ClickUp

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