How Insight Global Scaled AI Across Our 5,500 Employees with Microsoft Copilot

What happens when AI adoption becomes a business transformation initiative instead of a technology rollout?

When organizations invest in generative AI, the conversation often starts with licenses, training, and adoption. But those metrics rarely answer the question leaders care about most:

Is the technology creating meaningful business value?

At Insight Global, we believed the answer would depend less on the technology itself and more on how people use it.

Over the past year, we rolled out Microsoft 365 Copilot across our organization, ultimately reaching more than 5,500 licensed employees. Along the way, we learned that successful AI adoption isn’t primarily a technology challenge. It’s a people challenge. It’s a change challenge. And it’s a leadership challenge.

Today, 95% of employees use Copilot monthly, more than 70% engage with AI every week, and thousands of employees actively use AI agents in their daily work. More importantly, we’re beginning to see clear connections between AI adoption and measurable business outcomes.

This is the story of what worked, what surprised us, and what we’re continuing to learn.

Technology Wasn’t the Goal

Like many organizations, we started with a simple question: How can we help our people do their best work with AI?

From the beginning, we knew success couldn’t be measured by adoption alone. A high login rate doesn’t automatically create value. A large number of prompts doesn’t prove impact.

Even widespread usage doesn’t necessarily justify investment.

Instead, we aligned our AI strategy around outcomes our business already cared about. Recruiting performance. Productivity. Operational efficiency. Business results. The same metrics that already drive decisions every day.

That mindset shift changed how we approached adoption from the start.

Rather than asking: “How do we get more people to use Copilot?”

We asked: “How do we help people solve meaningful problems with Copilot?”

That distinction ended up making all the difference.

Building an AI Culture, Not Just an AI Program

Anyone can launch a new tool. Creating lasting behavior change is harder.

We knew we didn’t want AI adoption to become another corporate initiative that generated excitement for a few weeks before fading into the background.

Instead, we wanted to create an environment where people could learn from one another, share ideas, and discover practical ways to improve the work they do every day.

One of the most successful ways we’ve done that is through Agent of the Week.

Every week, we spotlight an AI agent built by someone inside the business and share it across the organization. These aren’t theoretical use cases or technology demonstrations. They’re solutions developed by people who understand their work deeply and wanted to make it easier, faster, or more effective.

The idea was simple: The people closest to the work are often best positioned to improve it.

Over time, this created momentum that extended far beyond any training session or enablement program. Employees weren’t just using AI. They were sharing it. Improving it. Learning from one another. And helping their teams discover new opportunities along the way.

What started as adoption became a culture of experimentation and continuous improvement.

Scaling Adoption Across More Than 5,500 Employees

As of May 2026, that approach was producing adoption levels that reached nearly every corner of the organization.

95% of employees used at least one Copilot feature in the previous month
71.5% of employees engaged with AI every week
37% of employees used a Copilot agent during the month
More than 1,100 users were repeat agent users, indicating that agents were becoming part of regular workflows rather than one-time experiments.
Employees received more than 54,000 agent responses from 872 active agents in a single month.

Just as importantly, adoption wasn’t concentrated among a handful of early adopters.

Several organizations across Insight Global achieved 100% monthly usage, while large teams across sales and operations reached adoption levels above 95%.

The most encouraging part wasn’t the scale. It was the breadth.

People across recruiting, sales, operations, finance, and corporate functions were finding ways to integrate AI into the work they were already doing.

AI wasn’t treated as a separate activity. Instead, it was becoming part of how work happens.

The Moment Adoption Became Business Impact

Adoption is an important milestone. Business impact is the destination.

One of the clearest examples came from an internally developed agent called Job Description Assessor, which helps our recruiters at all levels break down the positions they are working on in simpler terms, allowing them to get to the right candidates faster.

Job Description Assessor quickly became one of the most widely used agents in our organization.

But popularity wasn’t the metric we cared about most.

We wanted to know whether usage translated into real results.

Our analysis showed that recruiters who used the agent averaged more candidate submissions and a higher acceptance rate from those candidates than the recruiters who didn’t use the agent

What makes these findings especially interesting is that many of these users were already high performers before using the agent. The story wasn’t that AI transformed struggling employees into top performers.

The story was that experienced professionals found a way to extend their expertise. That’s a pattern we’ve seen repeatedly. The most valuable AI use cases don’t replace critical thinking and problem solving.

They help people apply that thinking more effectively.

Our Research: Where Companies Stand in their AI Journey

Why the Human Side Matters Most

There’s a lot of discussion about AI technology, but not enough discussion about the people using it.

The biggest lesson we’ve learned is that successful AI adoption has less to do with technology and more to do with empowerment.

Every meaningful breakthrough we’ve seen started with someone who understood a process, identified an opportunity, and decided to improve it.

A recruiter who understood candidate evaluation built a better recruiting workflow.

A finance professional used emerging AI capabilities to dramatically accelerate competitive analysis work.

Teams began sharing use cases, refining ideas, and helping one another solve problems faster.

The technology enabled the work.

People drove the change.

That’s why our approach to AI has consistently focused on opportunity. Not replacement. Not disruption for disruption’s sake. Opportunity for people to work differently, learn new skills, and create more value in the roles they already have.

At Insight Global, we’ve always believed people are at the center of transformation.

Our experience with AI has only reinforced that belief.

After scaling AI across thousands of employees, three lessons stand out.

1. Measure Business Outcomes, Not Just Adoption

Adoption metrics matter, but they are only part of the story. The organizations creating lasting value from AI are the ones connecting usage to outcomes that matter to the business.

The closer AI is tied to measurable goals, the more sustainable adoption becomes.

2. Let the People Closest to the Work Lead

Many of our most impactful AI solutions didn’t come from a centralized technology team. They came from employees with deep expertise in their day-to-day work. The best AI ideas often come from the people who understand the problem best.

3. Invest in the Human Side of Change

Technology alone doesn’t create transformation. Training matters. Leadership matters. Celebrating success matters. Organizations that invest in change management, enablement, and employee engagement are far more likely to realize meaningful results from AI.

What’s Next

We’re proud of the progress we’ve made, but we’re even more excited about what’s ahead.

The story isn’t that we reached 95% monthly adoption or built hundreds of agents. Those milestones matter, but they aren’t the finish line. They are evidence that our people are willing to learn, experiment, and find new ways to create value with AI.

Our focus now is helping more employees move beyond basic AI usage and into deeper, more specialized applications. We’re continuing to expand AI education and support across the business while exploring new capabilities within the Microsoft ecosystem, including Copilot Studio agents and emerging Copilot experiences. We are also continuing to sharpen how we measure success, with a growing emphasis on business outcomes instead of activity metrics.

Perhaps most importantly, we’re continuing to learn from our own people.

Many of the most impactful use cases we’ve seen didn’t come from a technology roadmap or a steering committee. They came from recruiters, account managers, finance professionals, operations leaders, and team members who understood their work deeply and saw an opportunity to make it better. The technology provided a new tool. Their expertise created the impact.

That’s why we believe the future of AI at Insight Global will look a lot like the past year: empowering people closest to the work, sharing what works, measuring what matters, and creating space for innovation to come from anywhere in the organization.