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Energy tech expert on how AI is changing in the workplace — and what employers need to recognize

The question isn't whether AI will change work – it's whether we'll use this moment to finally build workplaces that enhance rather than diminish our humanity. Photo via Getty Images

When OpenAI's GPT-4 made headlines by passing the bar exam and scoring in the top 10 percent on medical licensing tests, I noticed something fascinating: everyone focused on AI replacing professionals, but they missed the deeper story. AI isn't just disrupting work – it's exposing fundamental flaws in how we've built our entire workplace ecosystem. It's holding up a mirror to our organizations, revealing just how far we've strayed from what makes us uniquely human.

The World Economic Forum tells us 44 percent of workers' skills will need updating by 2027, but that statistic only scratches the surface. In my conversations with business leaders, I'm watching a transformation unfold in real-time. Take the accounting industry, where I've observed forward-thinking firms like Deloitte and PwC turning their accountants into strategic business advisors while other firms continue training junior staff for tasks that AI will soon handle. This isn't just a skills mismatch – it's a fundamental misunderstanding of human potential.

The challenge runs deeper than individual industries. McKinsey predicts 30 percent of hours worked globally could be automated by 2030, but I believe they're missing a crucial point. We've spent decades designing jobs around industrial-era ideals of efficiency and standardization – the very qualities that make them perfect targets for AI automation. In our obsession with measuring, standardizing, and streamlining everything, we've created workplaces that treat humans like machines rather than the complex, creative beings we are.

What's emerging is a striking paradox: as work becomes more automated, our workplace cultures are growing more disconnected. Microsoft researchers identified a "collaboration deficit" in remote work environments, with 56 percent of employees reporting a decline in workplace friendships. This cultural shift is occurring precisely when we need human connection most. During the Great Resignation of 2021, 47 million Americans quit their jobs, they weren't leaving because of salary considerations or technological inadequacies. The most common reasons cited were lack of human connection, purpose, and authentic leadership.

Yet instead of heeding this wake-up call, the rise of AI is pushing us further apart. A decade ago, the concept of "workplace family" was commonplace – now it's often dismissed as manipulative corporate rhetoric. This shift reveals a troubling blindspot in our thinking about work. Consider this: we spend more than 90,000 hours at work over our lifetime – more time than we spend with our own families – yet we're increasingly treating these relationships as purely transactional. In our rush to establish boundaries and protect ourselves from corporate exploitation, we've overcorrected, creating sterile workplaces stripped of human connection.

This timing couldn't be worse. As someone who studies the intersection of technology and workplace culture, I've observed a clear pattern: the more we automate routine tasks, the more our success depends on distinctly human qualities like trust, emotional sensitivity, and the ability to navigate complex interpersonal dynamics. Yet we're systematically dismantling the very cultural foundations that enable these qualities to flourish. It's as if we're entering a boxing match by tying one hand behind our back – at precisely the moment we need every advantage we can get.

The real crisis isn't that AI might replace jobs – it's that we're creating workplace environments that suppress the very qualities that make us irreplaceable. When we treat our colleagues as mere interfaces rather than complex human beings, we don't just damage relationships – we damage our capacity for innovation, creativity, and the kind of deep collaboration that complex problem-solving requires.

Some companies are starting to get it right. When I look at examples like IKEA, who chose to retrain their call center workers as interior design advisors rather than simply replacing them with chatbots, I see a glimpse of what's possible. They recognized something profound: you can't automate the human ability to understand what a frustrated customer really needs, or the intuition to read between the lines of what they're saying.

This is what I call the "human edge" – and it's far more nuanced than most leadership teams realize. It's the marketing manager who can sense team tension during a video call and address it before it derails a project. It's the sales representative who builds such strong relationships that clients stay loyal through market upheavals. It's the team leader who knows exactly when to push for more and when to show compassion. These aren't just nice-to-have soft skills – they're becoming our most valuable business assets.

But here's the challenge: we're still trying to measure workplace success like it's 1990. We track productivity metrics, sales numbers, and project timelines, but how do we quantify someone's ability to defuse a tense client situation? How do we measure the value of a team leader who creates an environment where people feel safe to innovate? These human capabilities – empathy, emotional intelligence, relationship building, creative problem-solving – are increasingly what separate successful companies from failing ones, yet they're nearly impossible to capture in a performance review.

When I talk to business leaders, I tell them bluntly: if a job can be reduced to a process, AI will eventually do it better. Our value lies in all the messy, human things that happen between the bullet points of a job description. Instead of asking "How many tasks did you complete?" we should be asking "How did you help your team navigate that difficult change?" Instead of training people to follow processes, we should be developing their ability to build relationships and navigate complexity.

It's time we started treating these human capabilities not as soft skills, but as core business competencies. The question isn't whether AI will change work – it's whether we'll use this moment to finally build workplaces that enhance rather than diminish our humanity.

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Nada Ahmed is the founding partner at Houston-based Energy Tech Nexus and author of Amazon Bestseller “Determined to Lead- The Disruptive Woman's Guide to Stop Playing Small and Transform your Career through Agile Leadership.”

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A View From HETI

Sage Geosystems has selected a site for its next major geothermal facility. Photo via sagegeosystems.com

Sage Geosystems, a Houston-based developer of geothermal power systems, has chosen a site in Nevada for its commercial-scale Project Vector facility.

The company’s two-well enhanced geothermal system (EGS) will deliver around-the-clock geothermal heat to Ormat Technologies’ Blue Mountain geothermal power plant in Winnemucca, Nevada.

The startup expects to begin drilling the first well later this year, with the first electricity to be generated in 2027 and full-scale production to start in 2028.

In the Nevada system, fluid will circulate through an engineered subsurface reservoir, absorb heat from the surrounding rock and return heat to the surface. The heat will be delivered to the Blue Mountain plant for conversion into electricity.

Project Vector builds on the performance of Sage’s SMECI facility in South Texas. That facility’s results, combined with Sage’s digital twin platform, will be used to shape to the design and development of Project Vector.

Project Vector supports Sage’s growing commercial pipeline, including a 150-megawatt geothermal power agreement with Meta Platforms, the parent company of Facebook and Instagram.

“Blue Mountain is an ideal location for Sage to take the next step in continuing to commercialize our proprietary EGS approach,” Jason Peart, chief operating officer at Sage, said in a release. “By delivering geothermal heat into an existing power plant, Project Vector can demonstrate the model for bringing firm, 24/7 geothermal power to market at scale.”

Project Vector extends Sage’s relationship with Ormat.

In August 2025, Sage and Ormat agreed to accelerate commercialization of Sage’s geothermal technology at an Ormat power plant. This January, Ormat co-led Sage’s $97 million Series B funding round.

Sage, founded in 2020, has raised about $159 million across three funding rounds.

As the startup ramps up its ESG platform, Sage is targeting data centers as customers, among other large-scale users of electricity.

“The energy needs are huge, and they need it now,” CEO Cindy Taff said on Data Center Frontiers’ podcast. “They can’t depend on the grid anymore.”

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