Generative AI is Stirring up Change Management
Why organizations need to shift their change management approach today, and how they can use it to tackle generative AI
While generative AI has become a hot topic in the past year, it’s simply a nod to the increase in technological changes across organizations. Executive chairman and CEO of Microsoft, Satya Nadella, said at Microsoft Ignite in 2022: “We’re moving from a mobile and cloud era to an era of ubiquitous computing and ambient intelligence, an era which will experience more digitization over the next 10 years than the last 40.”
These technology changes are felt by organizations and their employees on top of a multitude of other business changes. In a recent Harvard Business Review article, it was shared that “in 2022, the average employee experienced 10 planned enterprise changes… up from two in 2016, according to Gartner research.” This article also mentioned that transformation will remain at the forefront in 2023.
Employees are on the receiving end of these changes, with their focus being pulled in an unhealthy number of directions. A new approach to change management is needed to address this change acceleration.
Below are two concepts organizations should address before tackling the unique changes brought by generative AI and other emerging technologies.
1. Reframe the change
Traditional change management prioritizes eye-catching communications and engaging events designed to promote the big “go-live.” These communications worship the future-state vision and long-term goals. Now, multiply these communications by 10. Does that language still have the same impact on the employee who is receiving it? Likely not.
To manage this change fatigue, we need to reframe the change. This means prioritizing the packaging communications together that speak to common elements of technology or business changes. Communications should only reference the changes employees will see in their lifetime. These succinct communications can become the backbone for quick communications that are needed to respond to unique fast-paced technology changes.
2. Build resilience with skill development
We can’t reframe the change on its own; we also need to build resilience within our employees to manage these changes. This means prioritizing learning programs that build the skills and capabilities that are critical for the future, as technology continues to accelerate. Research from World Economic Forum shares that 87% of organizations have or expect to have a skill gap in the future with skills that are critical for today (critical thinking, analytical and problem-solving abilities, plus adaptability, resilience, and self-management).
I’ve seen this play out in the change management programs I’ve managed. The technology-aligned changes are prioritized over process, behavioral, or skill-based changes. In an ideal world, behavioral and skill-based needs are fed into organizational learning plans — preparing employees and organizations alike for change beyond individual programs.
Let’s say you’re given a task to present at a company meeting next week; you’re going to find this task more manageable if you’ve already been learning public speaking skills. Now you can prioritize preparing your content, without sweaty palms.
By prioritizing future state behaviors, skills, and capabilities, we can create resilience within employees so they can fare and even thrive in future technology changes that come without warning (enter generative AI).
How does this apply to generative AI?
When we build resilience, we enable our employees with skills to thrive in this digital era. When we reframe the change, we provide an opportunity for employees to leverage those skills and see this change as an opportunity instead of a threat. Once we have applied these two concepts, we can optimize a change management plan for the technology in front of us — in this case, generative AI.
Below are some tactics to consider when creating a change management plan for generative AI. This strategy targets employees positioned in business teams — not IT admins.
Communicate and engage:
- Start the dialogue now. Create spaces for early adopters to share and collaborate, and expect these spaces to grow over time.
- Communicate the use policy. These are the ground rules — we can’t begin without them.
Listen and learn:
Prioritize learning that starts with building a general understanding and then focuses on applied learning for unique teams. Here’s what this might include:
- What is generative AI (the basics) and what is the company policy?
- What problems can generative AI help you solve and how? Consider the opportunities of generative AI to support research, provide recommendations, and even brainstorm. The “how” might include a mental model so employees feel empowered to bring this into their role (i.e., generative AI as a thought partner, or a first pass).
- What are the use cases for your team? This learning should be targeted where possible for unique teams. On your team, you are a subject matter expert, so you can be critical of the information being generated and optimize it.
Collect and correct:
- Create a feedback loop to support an ongoing conversation. This could be a survey or part of a working group where impacted employees can share what’s working, what’s not, and where improvements can be made (while change managers may help facilitate this conversation, feedback doesn’t have to be change management related). Remember, if you want to keep receiving honest feedback it must be acknowledged or actioned.
- Consider when your approach can be revisited. We can expect generative AI to look very different in a year. Choose a point in time when you will revisit your approach. What you have now doesn’t need to withstand the test of time.
Build your foundation and manage future changes
As I mentioned earlier, we can’t expect these technology changes to slow down, so it’s important for organizational leaders to make time today to enable their employees to embrace future changes. Maybe as a team, you invest a few hours? Or a day? Or a meeting? Whatever you decide to invest, as you approach the next inflection point reflect on the investment you made, and how it may have supported the adoption of the change or reduced change fatigue.
When organizations create and communicate an inclusive view of the future and support skill development for today, they enable employees to embrace current and future technology changes.
Slalom is a global consulting firm that helps people and organizations dream bigger, move faster, and build better tomorrows for all. Learn more and reach out today.
