AI value is easy to see. Sustaining it is harder.

Early AI adoption tends to go smoothly.

A focused use case, a motivated team, a quick win. The harder question is what happens next, when AI spreads across teams and systems, and the early momentum runs into real organizational complexity.

MOST COMPANIES ARE PAST THE STARTING LINE

The gap now is between initial results and sustainable scale.

Where organizations get stuck begins to look very different depending on who they are.

This analysis explores three core questions:

What separates organizations that successfully scale AI from those that struggle to move beyond early adoption?
What factors shape how quickly organizations progress?
And what can businesses of different sizes learn from one another as AI scales?

Understanding those nuances creates opportunities for organizations of all sizes to learn from how others are scaling successfully.

About the study

This report draws on RingCentral’s Agentic AI Trends 2026 research, based on a survey of 2,000 IT, HR, and CX decision-makers across retail, technology, healthcare, legal, and financial services. Respondents represent SMBs, Midmarket organizations, Majors, and Enterprises across both customer-facing and employee-facing AI use cases.

Company size definitions

SMB

3-99 employees

Midmarket

100-399 employees

Majors

400-4,999 employees

Enterprises

5,000+ employees

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Table of contents

What scalers do differently

Chapter 1

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