Artificial intelligence has captivated global attention, especially with the rise of generative AI tools like ChatGPT and Microsoft Copilot (Copilot). AI's capabilities—from understanding human language to generating rich media and assisting in medical diagnostics—are driving significant changes in business processes. As organizations rush to integrate AI tools like Copilot to enhance productivity, it’s crucial to recognize that the success of AI relies heavily on people’s readiness to adapt and change.

This article offers six key change management tips to help organizations successfully implement AI.

Creating the human conditions for success

Before diving into these tips, it is important to remember that in many ways, we are all volunteers at work. We choose how much of ourselves and our knowledge we apply to our jobs, what we focus on, what’s relevant and actionable, and how to go about getting work done.

Related article: Effective change management: 8 tips to encourage employee volunteerism

We also volunteer to change how we work. Change can’t be conscripted, but only supported, encouraged, rewarded and recognized. So here are a few things to consider when helping people through AI-related change, with a focus on Copilot.

1. Temper enthusiasm with readiness

As with any new technology that captures the imagination, the tendency is to rush ahead and make it available without readying the organization to use it effectively and gain the expected benefits. With Copilot, once it is licensed, access is enabled across many applications and contexts, such as Microsoft Teams, Microsoft Office Applications, Microsoft Whiteboard, OneNote, and Copilot Studio for organizations to create their own copilots.

Many organizations will enthusiastically turn on Copilot, but the real return on investment comes when people are ready and able to use it in truly productive ways. Since SharePoint’s release in 2013, many organizations have had to spend significant money to clean-up and reorganize the digital landfill that was created when the product was simply made available across their organizations with little or no guidance or governance. Without some thought, history could repeat itself with Copilot and other AI tools.

2. Nurture a culture of learning, innovation and purposeful experimentation

Although AI has been part of the global technology discussion for over 60 years (according to Ray Kurzweil, inventor, author and AI expert), only recently have advances in availability, capability and user interface created opportunities for its use in organizations beyond the pioneers and very early adopters. So, AI is new to most organizations, and AI itself is changing at break-neck speeds.  

Implementing AI and incorporating its use into the organization is a learning journey where people at all levels are looking regularly for answers to fundamental questions such as: “What is this?” and “How does it work? How can it benefit me or my organization? How do I implement and use it? How do I know if it has really helped? What do I do next?”

These are challenging questions to answer given that the technology itself is complex and impossible to know everything about before taking action. As well, organizations are complex such that it is impossible to truly predict future outcomes of today’s actions with any great certainty.

Given the above, an essential approach is one of learning and purposeful experimentation. Do that by:

• Making learning resources available, including training and a technical environment

• Identifying pioneers and early adopters in your organization that can explore, showcase and coach others on the productive use of AI to solve business problems

• Recognizing and rewarding innovative problem solving and learning through failure

• Ensuring people can break away from their daily work, however briefly, to learn and experiment, reflect on the experience, and improve their use of AI – not just early adopters but everyone in the organization

• Supporting the creation or emergence of groups or communities to learn and share their experiences together

3. Consider the people impacted

People make organizations go. All kinds of people. Some who are at the forefront of change and willingly lead it in some way.  And others who have little opportunity to lead change but must adjust and adapt to changes outside their control. Regardless of role, AI can have a significant impact on people in their work environment in important ways, as identified in the diagram to the right.

Effectively implementing AI, therefore, should also include a thoughtful, agile change management effort built on employee empathy, and an understanding of the impacts of changes on key stakeholders. One that takes the most appropriate actions to create awareness about AI and its use in the organization, creates an interest in a desire for the use of AI, builds skill and ability to use AI in the context of business and individual roles, and supports everyone through the learning and implementation experiences. Most importantly, equip people leaders to coach their staff through changes related to AI.

4. Lead with clarity, collaboration and regular communication

A consistent challenge all organizations face at one time or another is highly skilled, well intentioned people pulling in different directions, which creates unnecessary conflict and impedes progress towards business objectives. This can happen in the context of AI as well given its “promise and potential” and complexity.  Never has effective leadership been so important.  In the context of AI, effective leadership includes:

• Building effective business, IT and information professional partnerships to collaboratively learn about and deliver AI business value

• Creating effective supportive networks of key executive stakeholders across the organization

• Delivering clear, consistent, updated and regular messages and information about:

  • the organization’s vision for AI,

  • how the organization is progressing in the use of AI and what its learning through the process,

  • expectations about its use across the organization, and

  • guidelines for when and how to use AI to get work done, including risks, ethical use, and rewards.

5.      Ensure your data is in order

In most organizations, it is often easier and less costly over the short term to “keep everything” than use a thoughtful program to apply lifecycle management to structured and unstructured data.  And most individuals are information hoarders to some extent, often keeping convenience copies of files in their own personalized filing structures, and rarely performing any housekeeping. The net result is “digital landfill.”  The effectiveness of AI and positivity of the user experience is directly related to the quality of data it draws upon. Every implementation of AI should also include validating, and if necessary, improving data and metadata quality.

6.      Get good at governance

In one way or another, AI is here to stay and will weave its way into most organizational processes. Information governance has long been promoted as the vehicle for ensuring quality information and data is available as and when required to make decisions and take action. Layering AI capability like Copilot adds another level of complexity to governance and underscores the need for it so that AI sustainably adds value to the organization. Ensure good governance by:

• implementing policies and technologies to manage data classification, retention and disposition, and protection,

• rigorously managing and controlling access to information and data,

• auditing regularly and adjusting tactics to ensure regulatory and legal compliance,

• engaging employees (experts, business owners and end-users) in governance activities such as policy development, technology evaluation and recognize them for their contributions, and

• managing licensing and costs on an ongoing basis

• and more! Check out our article about AI Governance Recommendations to Mitigate Risk for full scope and a governance checklist.

Conclusion

Successfully implementing AI requires a thoughtful approach to change management, focusing on readiness, learning, and governance. If your organization needs support with AI implementation, contact Gravity Union (we’ve got AI experts at the ready!) or download our Copilot offerings PDF for more information:

For further insights on AI, explore our articles: Ultimate Guide to Copilot for Microsoft 365 or Mitigating AI Risks: Governance Best Practices for Microsoft 365 Copilot. Additionally, check out my other change management articles such as how to encourage employee volunteerism.

References:

The Last 6 Decades of AI — and What Comes Next | Ray Kurzweil | TED (2024)

Davenport, Thomas H., Matthias Holweg, and Dan Jeavons. 2023. “How AI Is Helping Companies Redesign Processes.” Harvard Business Review, March 2, 2023. https://hbr.org/2023/03/how-ai-is-helping-companies-redesign-processes.