When IT Meets HR: Avoiding Culture Debt in the Age of AI

Oct 25

4 min read

Illustration of a bridge labeled “Culture” connecting IT and HR, symbolizing collaboration between technology and people in AI adoption.

Your inbox makes that familiar ring. A new email arrives from a colleague on a project you’ve been waiting to move on. Finally, some feedback. You’re ready to check items off the list and keep things moving.

Then you open the message and realize something is wrong.

The email looks polished, but the content is empty. Your colleague used AI to draft it, and the result is devoid of anything you can use. They didn’t apply their own experience or judgment to refine the output. It’s unusable.

Had they taken time to review and shape it, you could already be advancing your part of the project. Instead, they’ve handed off unprocessed AI work, creating more inefficiency and slowing progress.

Now you’re frustrated. Annoyed. And doing the work yourself.

Sound familiar?

This scene is becoming increasingly common as organizations accelerate AI adoption, and more people experiment with new tools. But alongside the progress, another pattern is emerging.

Workslop describes the unproductive output that comes from using AI tools without the skill or context to refine the results.

And what we’re seeing isn’t a technology problem. It’s a human one.

The Human Barriers

A recent paper entitled AI 2027 by Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, and Romeo Dean predicts that the impact of artificial intelligence over the next decade will be enormous, perhaps even “exceeding that of the Industrial Revolution.”

The paper emphasizes that while AI’s technical capabilities are accelerating, human adoption and understanding are lagging behind. It notes that “AI’s success will depend less on the algorithms themselves and more on how humans choose to use them.”

The real challenge, therefore, isn’t the tool. It is the behavior surrounding the tool. That is why HR must lead the cultural side of AI integration.

My work on The Cultural Microsphere™ demonstrates that employees must invest both time and effort into their roles to progress the organization’s culture. Those same investments now extend to AI adoption. Employees must learn to use the tools, apply their human skills and experience to refine the output, and make their work more efficient.

With AI becoming such an integral part of workplace culture so quickly, the time to act is now. Yet in many workplaces, two human barriers are limiting adoption.

The first is resistance to using AI tools, often driven by ego, fear of job displacement, or generational hesitation. The second is experience masking, the inability to refine AI results due to a lack of expertise or context.

Unchecked, these barriers cause employees' microspheres to stagnate and fill with friction, mistrust, and disengagement. These human barriers also create an opportunity for IT and HR to work together in new ways.

IT and HR Working in Parallel

In most organizations, the IT function owns governance, security, and tools. HR owns people development, training, and performance. Both extend well beyond those general descriptions, yet AI adoption does not live fully in either domain.

AI lives between them.

The AI 2027 paper predicts that by 2027, “AI will force the creation of hybrid functions that bridge technology and people operations” and warns of “human downgrading,” the erosion of cognitive skills when people over-rely on AI.

AI is already bringing these two essential functions together in a new way. Workplace culture is the bridge that connects them.

The Cultural Microsphere™ is where this partnership must take hold because the human level is where work truly happens. When unrefined output appears technically correct but lacks context or judgment, it signals more than a technical gap. It reflects a cultural and learning breakdown within the microsphere itself, where the personal investments of Effort and Change have weakened.

The Shared Solution Model

For organizations to navigate the fast-approaching wave of AI, IT and HR must co-lead, balancing technical governance with ethical and behavioral oversight. This becomes a shared responsibility for AI stewardship, where both functions play a critical role in ensuring AI tools are adopted and used appropriately.

A three-pillar strategy can guide this partnership:

Education

Teach employees how to use AI effectively and demonstrate what “good” looks like within the organization’s values and workflows.

Transparency

Foster open dialogue around tool usage and outcomes to build digital trust and encourage shared learning.

Goal Setting

Establish measurable AI adoption and behavior goals. IT should focus on adoption, compliance, and optimization. HR should focus on learning, productivity, and engagement. Together, they can assess the organization’s maturity with an AI Culture Score or similar metric, using data to understand how AI is truly being used within the culture.

The Rise of “Culture Debt”

Within every employee’s microsphere, AI adoption reflects the time invested in learning the tools, the effort to experiment or avoid them, the ability to adapt workflows, and the willingness to confront the ethical and evolutionary dilemmas that AI brings.

When those investments align with the organization’s mission and behaviors, AI adoption has the potential to truly thrive. When they don’t, resistance will grow and “culture debt” will accumulate.

This will manifest itself in many ways: rushed adoption; unrefined work; workplace conflict; and disengagement or misuse. Every time an organization deploys AI tools without addressing the human learning curve, it builds culture debt. The output looks efficient, but the people behind it are disengaged, uncertain, or resistant.

When organizations accelerate AI adoption without aligning culture, they take on culture debt. The systems advance faster than the people using them, and the gap widens until trust, clarity, and productivity begin to erode. The only way to repay that debt is through intentional investment in education, transparency, and shared ownership.

The Future Belongs to Culturally Fluent Organizations

To move forward with confidence, organizations must achieve what the authors of AI 2027 describe as digital trust.

From a workplace perspective, that trust is built through culture, not code.

AI will transform how we work, but only culture can transform how we think about it. IT will continue to govern, and HR will continue to help organizations learn.

The bridge between IT and HR is not technology. It is culture.

Illustration provided by ChatGPT.

Posted: 25 October 2025