In episode 115 of the Harmonious Workplaces podcast, organizational development consultant Rich Cruz and certified change management professional Ben Kleinman tackle one of the most pressing topics in the modern business world: artificial intelligence. Fresh off the Association for Change Management Professionals (ACMP) annual conference in Orlando, Ben brings back a wealth of insights on how AI is reshaping the change management landscape.
The central question driving this episode is a vital one for today’s professionals: What is one thing you can do to benefit from AI while retaining your own voice and humanity?
The Impact of AI on Jobs: Why Adaptability is Key
It’s no secret that artificial intelligence is causing anxiety in the workforce, with many fearing they might soon be replaced by robots. Rich points to recent data suggesting that professions in design, human resources, and web development are among the most impacted by AI. However, these professionals also tend to be the most adaptable.
The key to job security lies in embracing these tools rather than resisting them. As Ben notes, we are currently in a transitional phase: some organizations are fully integrating AI, while others want nothing to do with it. Regardless of where an organization currently stands, AI is here to stay, and professionals must avoid becoming “laggards” on the adoption curve.
The “Human in the Loop”: Why AI Still Needs Your Expertise
One of the core themes of the episode is the necessity of keeping the “human in the loop”—or, even better, the “human in the lead”. While large language models (LLMs) like ChatGPT, Gemini, and Claude are powerful, they frequently make mistakes, hallucinate facts, or produce “AI slop”.
Because AI can sometimes adopt a falsely positive tone or generate content that lacks a company’s specific cultural nuance, human judgment remains irreplaceable. Ben shares a helpful framework for thinking about AI, describing it as a highly capable new intern. This “intern” has access to vast amounts of information but knows nothing about your company’s specific goals, quality standards, or preferred formats. You must provide clear instructions, carefully evaluate its output, and coach it to improve.
Furthermore, the hosts highlight a practical framework from Tim Creasey, the Chief Innovation Officer at Prosci, which categorizes AI use into three buckets:
- Work AI can do for you: Automating simple, repetitive tasks, like basic email responses.
- Work AI can do with you: Brainstorming, ideation, client research, and drafting change implementation plans.
- Work AI cannot do: Building genuine relationships, having sensitive one-on-one conversations, and demonstrating true empathy.
Navigating the Accelerated Pace of Work
AI is undeniably speeding up the pace of work. It allows for nearly instantaneous prototyping, enabling teams to visualize concepts and accelerate design sessions. However, Ben warns that this capability comes with significant risks. AI “intensifies the work,” raising stakeholder expectations to unrealistic levels. Clients now expect immediate results, asking, “Why can’t you deliver this now?”.
If the speed of output increases but human bandwidth and resiliency do not scale accordingly, the result will be rapid employee burnout. Organizations must balance the efficiencies gained through AI with realistic expectations for human performance.
Leveraging AI for Sentiment Analysis and Cultural Sensing
A major talking point at the ACMP conference was the potential for AI to act as a “sensing machine” for organizational culture. Historically, change managers have relied on pulse surveys, water cooler chats, and one-on-one meetings to gauge stakeholder sentiment.
While some companies are simply using AI to digitize or automate traditional post-training surveys, Rich Cruz shares a more innovative approach. By taking transcripts from recorded meetings—such as daily standups on Microsoft Teams—and feeding them into an LLM, change managers can use AI’s language pattern recognition to extract valuable insights. When framed with the right prompts, the AI can detect shifts in vocabulary, identify potential resistance, and assess overall sentiment over time.
This method also allows change managers to quickly pull anonymized quotes to present to project sponsors. Highlighting real peer feedback—whether identifying a project that is off-track or celebrating a new process that saves time—adds powerful, objective validation to a change manager’s reports.
AI and Bias: A Double-Edged Sword
Finally, the hosts touch upon the complex relationship between AI and bias, particularly in hiring and HR. While some argue that AI can level the playing field by ignoring personal networks and focusing purely on job descriptions, it also eliminates the “good bias” needed to assess cultural fit. AI cannot yet replicate the human intuition required to recognize shared experiences or determine if a candidate shares a company’s underlying values.
Conclusion: Retaining Your Voice
Ultimately, succeeding with AI in change management comes down to intentionality. As Ben emphasizes at the episode’s close, professionals must sense-check AI outputs against their own lived experiences and human intuition. By embracing AI as a collaborative tool while firmly maintaining the “human in the lead,” change managers can unlock unprecedented efficiencies without sacrificing the human connection that is at the heart of their profession.
For more insights, be sure to check out our website here at Harmonious Workplaces. And remember, until next time, make change your friend!
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