Icebreakers
“The ultimate promise of technology is to make us more human, not less." — John Naisbitt
My family and I are fortunate to be away on a bucket-list vacation on a cruise through Southeast Alaska. Yesterday we idled our small boat at the foot of a calving glacier. With every rifle‑sharp crack, a slab of ancient ice sheared away and thundered into the fjord—an audible reminder that the glacier is melting faster than it can crawl forward, leaving it to retreat up the valley it helped create.
That soundtrack finds an unexpected rhyme in the book occupying my evenings—Daniel Yergin’s The Prize, the Pulitzer Prize winning epic history of oil, published in the 90’s. The parallels between calving ice and cut‑throat competition are impossible to miss.
Melting Ice, Moving Goalposts
Sure, Earth has been warming since the last ice age, but pretending human industry hasn't accelerated things would be intellectually dishonest. That said, demonizing fossil fuels misses the point - we desperately rely on them as a society. After all, access to energy and GDP per capita are positively correlated. In today’s political climate, the paradigm has forced us to pick between prosperity and sustainability, when really, we should be insisting on both.
As we enter the AI era, our hunger for electrons will only intensify. The U.S. and China are in an AI arms race, and ENERGY—not algorithms—is the limiting factor. Whoever wins the battle will have the computational power to solve some of our most pressing problems, maybe even climate change.
And while The Prize may not seem like a resource for sustainability solutions, it does highlight the rapid return on investment of game-changing technologies—and how they can modify human behavior, even make interactions more human.
When Machines Free Humans
The 1980s and 1990s were transformative decades for Big Oil. Companies were racing to deploy breakthrough technologies that seemed almost science fiction at the time—3D seismic imaging that could peer miles beneath the ocean floor, computer-guided drilling systems that could navigate underground with surgical precision, satellite monitoring networks that tracked thousands of wells in real-time.
The conventional wisdom was that all this automation would eliminate jobs. The reality was more nuanced.
Take John Browne at BP for example. Before these systems, oil executives like Browne spent enormous amounts of time hunched over geological surveys, manually interpreting subsurface data, essentially making educated guesses about where to drill next. It was painstaking, time-consuming work that could take weeks or months to yield actionable insights.
Once 3D seismic systems could generate those same insights automatically—and with far greater accuracy—Browne found himself with something precious: bandwidth. Instead of being trapped in the weeds of geological analysis, he could focus on focus on what he termed "relationship-intensive leadership." He spent time weaving together cultures during major acquisitions of Amoco and ARCO, nurturing stakeholder relationships across continents, and creating the decentralized management structure that analysts credit for BP's golden era of growth (its market value tripled).
This concept of course is not unique to oil. The same pattern played out across industries during the technology revolution of the 1980s and 1990s. When banks introduced ATMs, critics predicted the end of human tellers. Instead, the opposite happened—banks actually increased teller hiring. Similarly, airlines adapted reservation systems to free staff for customer service. Retailers like Walmart leaned into inventory automation to put more associates on the floor.
The pattern was unmistakable: automation didn't make these executives less human; it made them more available for the work only humans can do—building trust, navigating complexity, shaping organizational culture.
The AI Multiplier
Fast-forward to today. Artificial intelligence is doing to spreadsheets what drilling software once did to surveys. The organizations that thrive will be those with an abundance of electrons and empathy.
Think about your own schedule. How many hours this week were swallowed by hunting down data that should be readily available on your lab top? How many afternoons vanished into slide decks a bot could draft in minutes? Which customer call never happened because you were "running the numbers" yet again?
In an AI-powered world, those lost hours are equity begging to be redeployed—from busywork to bridge-building, from dashboards to dialogue.
Mapping the New Territory
There is no doubt that with technological advancement comes rocky transitions. As Anthropic’s CEO recently suggested, white-collar jobs are particularly susceptible. That said, the companies poised to dominate aren't replacing people with AI; they're using AI to strip away friction so their people can do work only humans can do.
Instead of busywork, afternoons can be spent in deep in conversation with strategic customers, or forging alliances that redraw your industry's map, or accurate forecasting that stretch beyond next quarter to next decade.
None of this is idealistic. The oil majors already wrote the playbook: automate the repetitive, humanize the strategic, and the returns follow.
Nature teaches the same lesson—adaptation isn't about fighting change, but finding new ways to thrive within it.
