Editorial
Organizations face a pivotal challenge: integrating AI in a way that enhances — rather than undermines — their people and culture.
Unfortunately, too many companies are attempting to force AI into operating systems that have been widely adopted and rarely questioned for nearly a century. By placing a transformative technology like AI into outdated frameworks, we risk dehumanizing the workforce and positioning AI as a competitive counterpart, or even a foe, that prioritizes technology over trust and productivity over purpose.
To harness the transformative power of AI effectively, we need a fundamental shift in how we think about our organizations and work as we know it today.
AI: A Mirror of Organizational Values
AI is a tool, much like money. And, like money, it will only amplify what a company already prioritizes. If an organization is primarily focused on efficiency gains, cost cutting and shareholder value at all costs, it will likely view AI as a tool to cut headcount, maximize short-term gains and downplay the cultural costs: eroding trust, stifling innovation and diminishing its employer brand. In this scenario, AI becomes a wedge that distances leadership from their workforce, treating employees as expendable resources rather than integral contributors.
On the other hand, companies that hold strong values around people and culture will take a different approach to AI. They will use it as a tool to support their workforce, enhance human capabilities and foster innovation. Rather than seeing AI as a replacement for human roles, they will position it as a powerful tool that frees employees to focus on creative, strategic and uniquely human contributions. This approach strengthens trust, reinforces cultural values and builds a strong employer brand.
The choice lies with leadership. AI’s impact isn't inherent in the technology itself but in how it is deployed. Will it be a means to cut corners, or a catalyst for growth and innovation?
The Scalable Efficiency Model: A Legacy of the Past
Many organizations still operate under what economist Robert Coase described in 1937 as the scalable efficiency model. The approach hinges on processes, technologies and workforce structures designed to maximize productivity as workloads increase. While effective in stable and predictable environments, stability and predictability are becoming the exception rather than the rule.
Worse, scalable efficiency often comes at a steep cultural cost:
- Job Eliminations: Automation-driven layoffs fuel fear and erode employee trust.
- Management via Spreadsheets: A hyper-focus on KPIs and shareholder value sacrifices culture and employer branding in pursuit of short-term results.
- Rigid Leadership: Leaders in this model are expected to “know it all,” which fosters a mindset that stifles curiosity, collaboration and innovation. Admitting uncertainty is perceived as a weakness.
The scalable efficiency model is ill-equipped to address the complexity and uncertainty organizations face today.
The Case for Scalable Learning
Enter John Hagel’s scalable learning model, a framework designed to meet the demands of a rapidly changing world. Instead of doubling down on efficiency, scalable learning prioritizes adaptability, curiosity and collective growth. Here’s how it works:
- Creating New Knowledge: The focus shifts from repeating existing processes to generating fresh insights and solutions. This expectation applies to everyone, not just a select few who happen to sit within R&D or within innovation labs.
- Psychological Safety: Leaders address employee fears head on and operate and communicate in ways that promote trust. When trust is high, employees feel comfortable speaking up, contributing, taking risks and operating in new and innovative ways.
- Building a Learning Ecosystem: Open communication, collaboration and connection is encouraged across all levels. The emphasis is on learning — not training — to share new, not pre-existing, knowledge.
- Curiosity as a Superpower: Employees are encouraged to ask questions, explore ideas and actively shape the future. Curiosity is cultivated and celebrated.
- Humble Leadership: Leaders embrace the phrase, “I don’t know, but I’m curious to find out.” They ask powerful questions, involve diverse perspectives and navigate uncharted territory with curiosity and humility.
By adopting this model, organizations position themselves not just to survive disruption but to thrive within it.
Overcoming the Fear Factor in AI Adoption
A key barrier to successful AI adoption is fear. Employees worry, often justifiably, that AI will automate their jobs away. Leaders who want to maintain trust within their organizations must address this fear directly. A failure to do so risks alienating the workforce and dehumanizing their culture.
Consider this: A recent HFS study found that while productivity is the top driver of generative AI adoption, 52% of leaders acknowledge that a singular focus on productivity could erode employee morale and trust. This is a warning we cannot afford to ignore.
Avoiding the Dehumanization Trap
Some AI vendors exacerbate fears with marketing campaigns that pit employees against machines. For example, Artisan’s recent “stop hiring humans” campaign — featuring slogans like “Artisans won’t complain about work-life balance” reduces uniquely human qualities such as empathy, creativity and collaboration to liabilities. The framing is demoralizing and shortsighted.
Organizations must take a stand. Leaders need to articulate a clear perspective on AI that aligns with their organizational vision and values. By drawing a distinction between tools and team members, organizations can reinforce that AI is here to augment human potential, not replace it.
A Path Forward for AI in the Workplace
The future of AI in organizations hinges on culture, not just technology. Leaders must:
- Shift from Scalable Efficiency to Scalable Learning: Embrace adaptability, curiosity and collective growth as core organizational principles.
- Address Employee Fears Head-On: Build trust through transparency and open communication about AI’s role and impact.
- Define a Values-Driven Approach to AI: Ensure AI adoption aligns with the organization’s vision, values and commitment to its people.
AI’s best use case to date is clearly its ability to drive efficiency, but efficiency is a double-edged sword. When used recklessly, it can undermine trust, culture and innovation. When approached with care and intention, it can liberate employees to focus on higher-value, uniquely human work.
AI has the potential to improve workplaces, but only if it is built upon a strong foundation that emphasizes humanity and organizational values. By advancing our organizational operating systems alongside technological innovations like AI, we can prioritize learning, curiosity and trust, and create environments where both humans and technology thrive.
It’s time to stop forcing round pegs into square holes. Let’s build workplaces designed for today’s complexities and tomorrow’s possibilities.
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Read More on Getting the AI-Human Balance Right:
- What AI Can't Take: 5 Traits to Preserve Humanity in the Workplace — The future of work can’t just be about what AI can take from us. It should also be about what we refuse to yield to it.
- Where AI Can Enhance Employee Experience: A Digital Workplace Perspective — AI can help build digital workplaces where employees thrive. Success lies in balancing tech innovation with an understanding of employee needs and aspirations.
- Microsoft's Annual Work Trend Index: AI Is Here, But It's a Band-Aid, Not a Transformation — Microsoft and LinkedIn collaborated on this fourth annual work trend index and found employees leading the way in AI adoption.
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