What AI Adoption Has Looked Like for Us

Artificial Intelligence (AI) has quickly become one of the most common topics in business conversations. Over the past two years, we've spoken with organizations at different stages of adoption. Some were just beginning to explore AI tools, like Microsoft Copilot (Copilot), while others were looking for ways to apply it responsibly within existing operations.

What has surprised to us is that efficient Copilot adoption rarely begins with technology alone. It requires education, guidance, experimentation, and a clear understanding of how it fits within day-to-day work. At Divergent IT, we've found that the most meaningful progress happens when the tool enablement is approached as an ongoing relationship rather than a single training session.

How We started

Over the past two years, we've worked with organizations of various sizes that were interested in understanding how Copilot can be adopted within their day-to-day operations. Rather than starting with a product demonstration, we started by understanding the work itself. We wanted to know which recurring activities were consuming time, where employees felt bottlenecks existed, and which processes created frustration for teams.

That approach helped us move beyond generic AI conversations and focus on practical business outcomes. Once we identified a workflow, we could demonstrate how Copilot can assist with the M365 applications employees were already using every day. Those conversations often go deeper into drafting emails, summarizing meetings, creating task lists, organizing projects, and developing effective prompting techniques. In some cases, clients have also requested additional guidance related to AI governance, cybersecurity policies, and responsible use practices.

While we are still working on ways to quantify long-term productivity outcomes, the engagement itself has been meaningful. Employees are asking questions, testing use cases, requesting additional training, and looking for more efficient ways to incorporate Copilot into their daily responsibilities. To us, those are early indicators that Copilot adoption is taking place.

What WE ARE DOING TODAY

Our focus today is helping organizations build practical habits around how Copilot can be incorporated into their day-to-day work. We have found that people learn more effectively when training is connected to the work they already perform instead of hypothetical scenarios.

A typical conversation starts with a simple question: What activities are taking more time than they should? From there, we demonstrate how to use Copilot around a specific objective, how to provide enough context to improve results, and how to use it within the applications where the work already happens. Just as important, we spend time discussing the limitations. We consistently emphasize that Copilot, as any other AI tool, is designed to assist people, not replace human judgment. We also discuss the importance of following organizational AI policies, governance requirements, and compliance expectations.

Organizations must understand where their data resides, who has access to it, and what information should or should not be entered into AI systems. We also encourage employees to review AI-generated content with the same level of scrutiny they would apply to any other business document. AI can help create a first draft, but the user needs to hold accountability.

This balanced approach has helped our partners build confidence while maintaining realistic expectations about what AI can and cannot do.

WHAT WE SEE IN THE YEARS AHEAD

The conversation around AI is quickly evolving. A few years ago, many organizations were still asking whether they should explore AI. Today, the discussion continues expanding to agentic AI, workflow automation and AI governance.

Over the next years, we expect AI capabilities to become more integrated into the business applications people use every day. As that happens, the challenge will no longer be access to AI tools. The challenge will be helping employees understand how to apply them in meaningful ways while maintaining security, compliance, and business oversight.

We also believe organizations will become more focused on measuring adoption. Questions will shift from "How many licenses do we have?" to "Which workflows are improving?" and "How are employees actually using these tools?" Companies that can answer those questions will be in a better position to realize long-term value from their AI investments.

At Divergent IT, we see our role extending beyond implementation. Technology alone does not create business outcomes. Adoption, education, and continuous improvement do. As AI continues to evolve, we look forward to helping our clients navigate that journey with the same mindset that has guided our work so far: start with the business challenge, prioritize security and compliance, and build practical habits that help people work more effectively.

Key TAKEAWAY

We've seen that successful AI adoption starts with understanding the work, not the technology. When organizations focus on solving real business challenges, while maintaining security, compliance, and accountability, AI becomes much safe to adopt and more valuable in everyday operations.