09-10-2026
While the promise of artificial intelligence is that it will accelerate human capacity, humans right now are in the friction stage of the adoption cycle.
In the recent webinar, The Human Side of Artificial Intelligence, Heather Polivka (MBA ’96), founder and CEO of Awesome People Leaders, offered leaders a framework for how to facilitate a human-centered change. She urged leaders to view AI not as a universal solution tool, but as an amplifier.
Founder and CEO of Awesome People Leaders Heather Polivka helps leaders identify and reduce the human friction that can slow AI adoption.
To succeed, teams need to have clear processes, sound judgment and productive collaboration for AI to expand their capacity effectively. On average, change presents a human challenge for organizations, and friction increases where communication is unclear, decisions stall or handoffs break down. AI can make those weaknesses move faster, exacerbating the friction. As Polivka put it, more capacity is not the same as more capability.
For leaders, the challenge is not only addressing these behaviors, but being able to see where human friction is occurring across the organization before it shows missed priorities, slower execution or business results.
AI adoption is therefore a change-management challenge as much as a technology initiative. The McKinsey 7-S Model offers a useful lens: strategy, structure and systems must align with the softer, human-centered elements of shared values, skills, style and staff. Shared values sit at the center because culture shapes how people interpret priorities, make decisions and respond to uncertainty.
That human response should not be mistaken for resistance alone. People commonly move through a change journey that begins with shock and denial, may dip into frustration or discouragement, and progress through experimentation, decision and engagement. Even employees who support AI may feel a loss of competence or control as familiar expertise and workflows shift.
Polivka focused on how leaders can respond with emotional intelligence rather than impatience. AI-driven change can trigger fears about status, certainty, autonomy, connection and fairness. Under pressure, people may fight change, avoid it or freeze in analysis paralysis. The leadership task is to create enough clarity, trust and psychological safety for people to move from self-protection to curiosity, collaboration and problem-solving.
Psychological safety comes from normalizing uncertainty, inviting honest conversation and making experimentation manageable.
Communicate the change journey explicitly. Explain that reactions such as shock, denial, frustration and discouragement are normal — even among people enthusiastic about AI. She called the low point between discouragement and experimentation “the pit”; being there does not mean that change, the team or the individual has failed.
Give people permission to say they are struggling. When leaders create an environment where an employee can say, “I’m in the pit today,” without being judged, sidelined or told to simply get on board, they respond better. They've had their concerns acknowledged. Polivka contrasted this with “the bus is leaving the station” approach, which makes people less likely to raise concerns when implementation is not working at its best.
Make a team commitment to move through resistance together. She suggested a practical “pinky swear”: team members agree not to remain stuck, to share difficulties and to help one another take the next step.
Start with small, low-risk experiments. Rather than expect hesitant employees to adopt AI across their work immediately, help them choose one repetitive, frustrating or time-intensive task AI might assist with. Review the output using human judgment, then build confidence one experiment at a time.
Set guardrails collaboratively — and explain why they exist. Polivka cautioned against governance that feels like control or mandates. Instead, discuss with the team where AI is appropriate, what uses are off-limits, how outputs will be checked and why those boundaries matter. This preserves a sense of autonomy while providing needed clarity.
Keep difficult conversations human. Do not delegate emotionally sensitive or ambiguous communication to AI. Managers should hold human-to-human conversations, actively listen, clarify expectations and address friction directly. AI can help people prepare, but it should not replace accountability or relationship management.
Use AI to prompt reflection, not to make the call. She recommended designing AI use around questions such as: “Is my intent clear?” “Who owns this decision?” “What assumptions are we making?” and “How might this message land?” That pause can reduce defensiveness and invite candor before misunderstandings escalate.
Build trust through frequent recognition and feedback. Polivka emphasized that people need to feel seen, heard and valued. Regular positive reinforcement — she cited a four-to-one ratio of reinforcing to redirecting feedback — makes constructive feedback feel less threatening and supports a culture where people can learn openly.
When humans use AI to strengthen — not replace — human capability, agency over circumstances will lead to better discernment calls when using AI. Presently, AI can summarize information, surface options and prompt better questions. Humans own accountability, final judgments and emotionally charged conversations.
The future of work is not AI versus people. It is people working with AI by design. AI is a tool. It must be paired with empathy and sound judgment. Leaders who model this well reduce resistance, protect trust and help their teams turn technological capacity into meaningful organizational outcomes.
Download and benefit from key takeaways from the webinar.
Connect with Heather Polivka, founder and CEO of Awesome People Leaders, on LinkedIn.
