Vaibhav Dani, CEO at Map Communications, specializing in enterprise AI architecture and digital transformation.gettyAs artificial intelligence continues to evolve, enterprises are racing to integrate large language models and agentic workflows into their systems and processes. A persistent shadow, however, looms over these innovations: the fear that these efficiency gains will inevitably reduce the workforce. Efficiency has traditionally meant achieving the same results with fewer resources.Yet, a 19th-century economic principle suggests we may be looking at the equation backward. The Jevons Paradox posits that as a resource becomes more efficient to use, total consumption of that resource increases—because the effective cost drops, sparking massive new demand. In the context of AI, we are witnessing the democratization of intelligence: Lower costs are not leading to less work, but to a dramatic expansion of what is possible.The Rebound Effect: How Efficiency Can Fuel AcceptanceIn 1865, economist William Stanley Jevons observed that as steam engines became more coal-efficient, England’s total coal consumption skyrocketed. The resource had become cheap enough to apply to more and more use cases. We are seeing a direct digital parallel to this today.As AI models become more efficient—through techniques like quantization and the rise of small language models—the marginal cost of what I like to refer to as a "unit of intelligence" is plummeting. Epoch AI similarly reports that quality-adjusted LLM token prices have fallen at a median rate of 40 times per year, with the fastest declines—up to 900 times per year. This shift is driving higher acceptance across industries for three primary reasons:1. Democratic Innovation: When the cost of high-level analysis drops, it is no longer the exclusive tool of the Fortune 500. Small and medium enterprises are now able to use AI for complex tasks like predictive supply chain management and personalized marketing, processes that were previously cost-prohibitive.2. Solving The Dormant Data Problem: Most organizations sit on mountains of unstructured data. Efficiency gains now allow companies to finally process this “dark data,” creating entirely new value streams, rather than simply optimizing existing ones.3. Reduced Barrier To Entry: Lower costs often lower the risk of experimentation. As AI becomes too cheap to meter, internal cultural resistance to adoption may fade, replaced by a mandate for pervasive integration.The Job Market Impact: Expansion, Not DisplacementThe most common concern regarding the Jevons Paradox in AI is its impact on employment. If AI makes a worker twice as productive, logic suggests we need half as many workers. However, history—and the rebound effect—suggest a different outcome: what we might call the "Great Expansion." Just as the spreadsheet didn’t eliminate accountants—it turned them into financial analysts—AI is helping professionals manage dozens of parallel workstreams that were previously impossible to oversee.For this reason, I believe expansion, rather than pure displacement, is the more likely outcome. As routine execution becomes a commodity, I believe the value of human labor will shift toward directing and managing AI systems. We are moving from a world of doers to a world of directors. McKinsey research confirms that even though some roles may shrink, new ones will emerge, and others will grow. When the cost of a service drops, demand tends to scale nonlinearly. Economist James Bessen’s landmark IMF analysis documented how ATMs, rather than eliminating bank tellers, reduced per-branch teller requirements from about 21 to 13, making it cheaper to open branches—so banks opened 43% more urban branches, and total teller employment grew. In the AI era, I'm seeing a parallel surge in demand for roles in AI ethics, prompt engineering and human-in-the-loop auditing. The World Economic Forum projects 170 million new roles will be created by 2030, offsetting 92 million displaced—a net gain of 78 million jobs globally.As commodity intelligence becomes abundant, I believe the human premium will increase for high-context, high-stakes and emotionally intelligent work. The Jevons Paradox will allow humans to move away from robotic tasks and toward work requiring empathy, ethical judgment and complex social intuition—capabilities no model reliably replicates. The McKinsey research linked above notes that social and emotional skills, like coaching, are the least likely to be automated.Navigating The Transition: A Scalable StrategyAs technology leaders, our goal should not be to use AI to shrink our organizations. Instead, we should leverage efficiency to scale our impact. If you're looking for a place to start, I'd urge you to consider the following steps:​• Continuous Reskilling: Treat AI as a tool for human augmentation. If core tasks are changing, training employees to manage AI-created workloads will become a strategic imperative, not a cost center.• Focus On Edge Cases: Use AI to handle standardized work, then redeploy human judgment to the exceptions: ambiguous inputs, high-risk decisions and customer moments that define trust and differentiation.• Ethical Oversight: As AI becomes more accessible and widely deployed, the risk surface expands, including potential risks like bias, privacy and misuse. Put governance, evaluation and accountability in place early so scale does not outpace your safeguards.The Future: A Flourishing EcosystemThe Jevons Paradox tells us that efficiency is not a destination—it is fuel. As AI becomes cheaper and more capable, I believe it will weave itself into the fabric of every job description. The result will not be a jobless future, but a future where the cost of starting something new—a business, a research project or a creative endeavor—is lower than it has ever been.If you want to succeed in this industry, I believe you need to use AI’s efficiency to expand your horizons, creating more value, more demand and ultimately more meaningful work. In this new landscape, the companies that thrive won’t use AI just to get lean. They’ll use it to get bold, reinvesting AI’s efficiency gains into ambition, innovation and the people who make both possible.​Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?