The Scarcity Era Is Over. Here’s the Data Most Business Leaders Still Haven’t Seen.

Renewables hit 49.4% of global installed electricity capacity last year. Lithium-ion batteries cost 99% less today than they did in 1991. A high-quality lab-grown diamond that would have cost $4,800 in 2015 now retails for under $300. AI created hundreds of thousands of new roles in 2025, even as it automated others.

These are not predictions. They are published data points from IRENA, BloombergNEF, GIA market reports, and the Stanford AI Index released this week. And yet most business owners I talk to are operating as though scarcity is the default, crisis is the norm, and the future is something to brace for rather than build into.

This post is about the other story. The one hiding in plain sight. And more importantly, what it means for how you run your business today.

Are We Actually Living Through an Abundance Transition, or Is That Just Optimism?

Direct Answer: Yes, and the evidence is measurable. According to IRENA’s 2026 Renewable Capacity Statistics report, renewables accounted for 85.6% of all new global electricity capacity added in 2025, reaching 49.4% of total installed capacity. BloombergNEF confirms lithium-ion battery prices have fallen 99% since 1991, from $9,200 per kilowatt-hour to $78.

Here’s the thing about exponential progress: it looks slow until it doesn’t. For most of the 2000s and 2010s, renewables were something you read about in think pieces. A promising technology. Definitely the future. Just not yet. Then, somewhere between 2020 and now, it stopped being “not yet.”

By the end of 2025, according to IRENA, 692 gigawatts of new renewable capacity were added in a single year. A record. Solar alone accounted for nearly three-quarters of that. And the EIA is projecting 99.2% of all new US power generation in 2026 will come from renewables and battery storage.

I used to roll my eyes at the term “exponential curve.” It sounds like consultant filler. But once you see it show up in five separate industries simultaneously, using real figures and real dates, it stops sounding like metaphor and starts sounding like operational context.

The practical point for business owners: energy is becoming cheaper, more abundant, and more locally accessible. If your cost model depends on expensive or volatile energy, that changes. If you are in a business that ships physical products, expect the supply chain economics to keep shifting as electrification becomes the default infrastructure.

Tactical next step: Pull your last 12 months of energy costs. Model what happens to your margins if those costs drop 30% over the next 5 years. That is not a fantasy scenario. It is the stated trajectory from both IRENA and BloombergNEF.

Why Did Battery Prices Fall 99%, and What Does That Actually Mean for Your Business?

Direct Answer: According to Our World in Data, citing BloombergNEF data updated March 2026, lithium-ion battery prices declined from approximately $9,200 per kilowatt-hour in 1991 to $78 by end of 2025, a 99% drop in 34 years. In 2025 alone, prices fell another 8% despite rising commodity costs.

The honest answer is this: most of what you learned about technology costs being a barrier to adoption is becoming outdated in real time.

When batteries were $9,200 per kilowatt-hour, electric vehicles were an experimental curiosity. When they crossed $100 per kilowatt-hour around 2024, cost parity with combustion engines arrived in China. Over 20 million EVs were sold globally in 2025. Some are now available for $10,000.

Think about what this pattern means outside of vehicles. Batteries are not just a car technology. They are the missing link between intermittent renewable energy (the sun goes down, the wind stops) and a reliable grid. At $78 per kilowatt-hour, four-hour battery storage projects cost $78 per megawatt-hour, the lowest in recorded history according to BloombergNEF’s 2026 LCOE report. That number unlocks grid configurations that were economically impossible five years ago.

Here is the contrarian take that I think most business media underplays: this is not a green energy story. It is an economics story. Solar plus storage is now beating new natural gas construction on cost in most markets, regardless of any policy incentive. The energy transition is happening because it is the cheapest option, not because anyone is being virtuous.

I am still figuring out how to translate this into specific advice for businesses that are not energy companies. But here is my best current thinking: any business with significant physical infrastructure, logistics costs, or manufacturing exposure has a legitimate reason to build an energy cost scenario into their 3-year financial model. The change is no longer theoretical.

Tactical next step: Check whether your city or state has battery storage incentives active for commercial properties in 2026. Several states are running programs specifically targeting commercial and industrial operators.

How Did Lab-Grown Diamonds Go from Niche to 55% of Engagement Rings?

Direct Answer: Lab-grown diamonds now represent over 55% of engagement ring sales in the US as of 2026, according to market data compiled by Tashvi AI and confirmed by jewelry trade reporting. A 1-carat D/VS1 lab diamond retails for around $280–320 in 2026, compared to approximately $4,800+ for a comparable natural stone.

Look, I know diamonds might seem like a weird example to use in a business strategy post. Bear with me for a second.

The diamond market is one of the cleanest case studies of what happens when a technology collapses the cost of producing something that was previously scarce by accident rather than by physics.

Natural diamonds are scarce because they form deep in the earth over millions of years and must be located, mined, and transported. Lab-grown diamonds are identical in chemical composition, crystal structure, and optical properties. They just take weeks to grow in a controlled environment. When the process became industrially efficient, supply exploded and prices followed the standard learning curve down.

Between 2015 and 2025, lab-grown diamond prices fell approximately 80–83% according to Ethica Diamonds market data. A stone that cost $4,800 a decade ago now costs under $300.

Here is what this tells us about a broader pattern. When the cost of producing something collapses, it does not simply make the existing market bigger. It rewrites who has access to it, how it is used, and what role it plays in adjacent markets. Jewelry designers now routinely specify 2.5 to 3 carat center stones for clients who previously could not afford anything larger than 1 carat. The design language of the industry has shifted because the constraint was removed.

Ask yourself: what is the diamond equivalent in your industry? What is expensive today because of artificial scarcity, manufacturing complexity, or supply chain overhead, that a technology learning curve is quietly eroding? Because the answer almost certainly exists. The question is whether you spot it while it is still a competitive advantage or after it has become table stakes.

Tactical next step: Pick one input cost in your business (materials, software licenses, logistics, energy, labor for a specific task). Spend 20 minutes researching whether there is an emerging technology or process that is on a downward cost trajectory for that input. The answer will inform your 2027 planning more than any macroeconomic forecast.

Is AI Actually Creating Jobs, or Is That Just What Tech Companies Say?

Direct Answer: The Stanford HAI 2026 AI Index, published April 13, 2026, confirms AI’s workforce disruption has moved from prediction to reality, with measurable impact on young workers in AI-exposed roles. However, the same data shows AI created hundreds of thousands of new specialized roles across AI operations, data infrastructure, and model deployment in 2025, and the median value of AI tools to US consumers tripled year-over-year.

The jury is still genuinely out on this one. I want to be direct about that.

What we know from the Stanford data: AI is hitting young workers in white-collar, analytical roles first. That is consistent with the pattern we would expect from a technology that automates cognitive and writing tasks before physical or relational ones. It is also consistent with what founders hiring for junior analyst roles are reporting.

What the same data also shows: the creation of new roles around AI deployment, maintenance, prompt engineering, agent orchestration, and data infrastructure has been significant and measurable. The net labor market effect in 2025 was not a simple subtraction problem. It was a reshuffling.

Here is what I think is the more useful frame for business owners, though. The question “will AI create or destroy jobs overall” is the wrong question to be asking if you are running a company right now. The right question is: which specific tasks in my business can AI now do at a fraction of the cost, and what do I do with the humans who were doing those tasks?

I have seen founders who treat this as a headcount reduction opportunity miss the bigger play. The founders winning right now are the ones redeploying that freed-up human capacity toward higher-leverage work: customer relationships, strategy, creative problem-solving, and sales. The PwC AI Performance Study published this week found that 74% of AI’s economic gains are going to just 20% of companies. The differentiator is not cost-cutting. It is using AI to pursue growth.

One honest mistake I made early in this cycle: I assumed AI automation would free up my team’s time automatically, that the efficiency gains would just appear. They did not. You have to actively redirect the time. If you do not design the new workflow, the old one just continues and you end up paying for both.

Tactical next step: Identify one role in your organization where 30–50% of the weekly tasks are now automatable with current AI tools. Build a new job description for that person that assumes the AI is handling the automatable work and redirects their energy toward a higher-leverage function. This is different from eliminating the role. It is upgrading it.

Can Robots and AI Actually Speed Up the Renewable Energy Transition?

Direct Answer: Yes, and it is already happening. According to BloombergNEF’s 2026 LCOE report, battery storage projects now cost $78 per megawatt-hour, their lowest recorded level, enabling faster, cheaper deployment of renewable energy at scale. Agentic AI is being used to optimize siting, grid integration, and permitting workflows that previously slowed project timelines by years.

The combination of robotics and AI is compressing timelines that were previously bound by human labor constraints in construction, installation, and grid management.

Solar farm installation, for example, is increasingly robotic. Panel placement, mounting, and cabling workflows that required large crews and weeks of work are being automated. That does not eliminate labor from energy projects, but it changes the ratio dramatically and, more importantly, it changes the speed.

On the AI side, the permitting and interconnection process is one of the most significant bottlenecks in renewable deployment in the US. Projects routinely wait 2–5 years in interconnection queues. AI-driven workflow tools are starting to automate parts of the application, documentation, and compliance review processes that previously required manual legal and engineering work at each step.

This is early. I would not overstate where it is today. But the trajectory is clear: the deployment rate of renewables is being accelerated by the same AI and automation wave that is transforming other sectors.

For business owners, the practical implication is this: the timeline for cheap, abundant, clean energy becoming the default grid infrastructure is shortening. Every model that assumed energy costs stay flat or rise should be revisited.

Tactical next step: If you are in construction, infrastructure, or any business with significant energy exposure, request a briefing from your energy supplier on their 3-year capacity plans. Understanding the supply trajectory in your region will tell you more about your future costs than any commodity forecast.

Key Takeaways

The abundance transition is already documented, not predicted. Renewables hit 49.4% of global electricity capacity in 2025, per IRENA. Battery costs fell 99% since 1991. Lab diamonds dropped 80%+ in a decade. These are not projections, they are published data points. The transformation is measurable now.

Exponential cost collapses create new markets, not just cheaper versions of old ones. When lab diamond prices fell 80%, average engagement ring center stone size jumped from 1.3 carats to 2.5 carats. When batteries crossed the $100 threshold, EVs achieved cost parity. Cost collapses change what is possible, not just what is affordable. Your industry has an analog.

The AI opportunity is in growth, not just efficiency. According to PwC’s 2026 AI Performance Study, 74% of AI’s economic value is going to 20% of companies. The difference is not who is automating tasks. It is who is using AI to pursue new revenue and growth opportunities. Cost reduction alone does not compound.

The psychological barrier is now the real constraint. Technology is delivering on its promises faster than most people are updating their mental models. The founders who are winning are not waiting for more evidence. They are operating as though the transformation is already underway, because it is.

Ignoring this pattern does not make it slower. The leaders in your sector are already building strategies around collapsing costs, expanding access, and AI-enabled growth. The question is not whether the transformation is real. It is whether you are in the 20% capturing its gains or the 80% still in pilot mode.

The abundance era is not coming. It is here. Renewables are within months of crossing 50% of global electricity capacity. A 1-carat diamond that cost $4,800 a decade ago costs $300 today. Battery storage costs hit their lowest level in recorded history in 2025. AI tripled its median consumer value in a single year.

None of this means everything is fine, or that the transition is painless, or that everyone benefits equally. It means the baseline assumption that scarcity is permanent, that access is zero-sum, and that technological progress moves at incremental pace is wrong. And operating on wrong assumptions has real costs.

The risk is not that the abundance transition is a fantasy. The risk is that you wait until it is obvious to act, and the window for competitive advantage has closed.

If you are in the 80% of companies still running AI pilots without measurable financial returns, this week’s PwC data is the benchmark. The 20% who are winning are not smarter or better resourced. They made different assumptions earlier.

What assumption about scarcity are you still carrying that no longer matches the data?

Comment below with your answer, or send this to someone who is still waiting for permission to act.

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