#demand forecasting using ai

[public-cloud-computing]

Gen AI streamlines resource allocation, saving costs and boosting efficiency. Explore how it optimizes your business operations.

[rubylogan15]

Gen AI streamlines resource allocation, saving costs and boosting efficiency. Explore how it optimizes your business operations.

[enterprise-cloud-services]

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses.

[generative-ai-in-bi]

How Does Gen AI Make Resource Allocation Cost-Efficient?

Find out how Gen AI enhances cost-efficiency in resource allocation with cutting-edge algorithms and data insights for smarter business decisions.

In the contemporary business world, strategy implementation requires proper management of resources to sustain organizational competitiveness. Resource allocation is a critical capability for today’s businesses as it enables efficient and effective resource usage as a way of optimizing profits and reducing costs. However, most traditional techniques for resource allocation are defective since the data used are either inaccurate or insufficient to exact resource optimizations. This is where Generative AI (Gen AI) comes into play. Gen AI is revolutionizing the way businesses approach the management of their resources through increased efficiency, operational costs, and responsiveness to changing market conditions, all due to its use of sophisticated algorithms and access to large quantities of data.

Generative AI offers a new dimension in the concept of cost because they make data as the center of resource management plans. Through its real-time analysis of large datasets, Gen AI can help businesses make better decisions on the deployment of their resources. In terms of inventory, workforce, or supplies, Generative AI guarantees the spending of available resources to the least possible extent. As mentioned above the advantages of implementing Gen AI in resource management is not a pipe dream; there are already companies across industries that are realizing lower operational costs and higher efficiency.

Predictive Analytics for Demand Forecasting

The most significant application of Generative AI in the allocation of resources is its predictive analytics use in demand forecasting. Gen AI uses historical data to make persistent analyzes and draw the corresponding conclusion of future demand for products and/or services. It is most applicable in the management of inventory since both overstocking and stock-outs can be very costly. Overstocking means keeping excess inventory leads to the consumption of company capital, and stock-outs lead to lost business and customers’ disappointment. This is where Generative AI can help with demand forecasting, allowing businesses to have just the right amount of stock which is optimal for fulfilling customer needs without overstocking.

For example, a retailer leveraging Gen AI for demand forecasting can plan for increased demand of certain products during festive occasions and replenish their stock in advance. This approach reduces the probability of overstocking, but also helps to avoid stock-outs and hence the use of resources and costs are optimized. Within industries like manufacturing where raw materials and production schedules need to be carefully managed, Generative AI can forecast fluctuations in demand and optimize the supply chain as well, further reducing costs and improving efficiency.

Optimizing Workforce Allocation

There are other important area like workforce management where Generative AI can drive significant cost efficiencies. Typically, workforce management often involves manual scheduling, and this causes some problems such as high levels of inefficiency in utilization of labor resources, which include time wastage and over-time costs. As for generative AI, it is capable of identifying workforce needs of a company based on project requirements, skills and workload balances. This way, it avoids issues such as over staffing, which may lead to wastage of resources, or understaffing that may slow down productivity.

For example, in a manufacturing plant, Gen AI is capable of estimating peak and off production seasons and then schedule the employees. For instance, the AI could recommend hiring additional workers during peak production periods as well as downsizing during slower periods. Such a level of precision in workforce allocation not only reduces idle time and overtime expenses but also enhances overall productivity. Several companies that have integrated AI in workforce management solutions have realized better control of workforce costs and increased employees’ satisfaction since the workforce is well-matched with the business needs.

Enhancing Supply Chain Efficiency

Supply chain management usually involves a cocktail of issues including supplier selection, logistics, and inventory management which all have the tendency of contributing to the over cost of the overall chain. The innovation of generative AI presents a powerful solution to these challenges since it improves the transparency and flow of supply chain. Gen AI is also very effective in analyzing data from all supply chain links from the procurement of raw materials to final product delivery; Gen AI can identify cost-effective suppliers, optimize logistics routes, and streamline inventory management.

For instance, Generative AI can analyze historical data to identify the best suppliers regarding delivery time, quality, and price in the supply chain. It also simplifies the process of finding new sources and can help to negotiate for better prices and improved supply chain reliability. As for the concept of logistic, Gen AI can easily find the best routes to transport goods, reducing fuel consumption and delivery times, which directly translates into cost savings. Further, by providing real-time insights into inventory levels, Generative AI is also important in eliminating excess stock and stock out situations hence increasing the efficiency of the supply chain and decrease operational costs.

Dynamic Pricing Models with Gen AI

Dynamic pricing is a method through which prices for products and services are varied according to the current market conditions. Generative AI helps to integrate flexible pricing strategies into enterprises with high levels of accuracy based on market changes. Having information about the customer behavior, competitor actions, and broader economic trends, Gen AI can suggest the optimal price adjustments that balance competitiveness with profitability.

For instance, an e-commerce platform with Gen AI to apply dynamic pricing will reduce product prices during low demand in the market in order to increase its sales revenue, and increase prices during high demand to increase its profits. This flexibility in pricing helps businesses want to remain relevant and at the same time make profits without having to compromise on its profit margins. Companies that have adopted the use of AI in pricing strategies have disclosed that they have realized an increase in revenue and profit margins, as they are able to respond more quickly and effectively to market changes.

Energy Consumption and Sustainability

The cost of energy consumption for a business is one of its significant expenses depending on the industry where it operates, specifically those relying heavily on energy, such as manufacturing industries and other sectors utilizing large amounts of energy. As for the challenges and the solutions, there are still some challenges to be addressed that lead to Generative AI’s major advantage of improving efficiency in energy consumption and leading to cost reduction for renewable energy, which in turn makes a positive impact toward achieving sustainability. Because the patterns of energy use, equipment performance, and production schedule can be monitored and analyzed, Gen AI can suggest changes to optimize energy use and increase efficiency.

For example, in the manufacturing environment, Gen AI can use data from sensors installed in manufacturing equipment to identify low energy consumption time and recommend changes to the schedules or equipment settings. This not only lowers energy costs but also supports the company’s sustainability initiatives by reducing its carbon footprint. Industries like automotive manufacturing where energy cost forms a good fraction of the total cost have already started realizing benefits of AI-driven energy management with companies recording improvements in energy consumption of more than 20%.

Risk Management and Cost Control

It is crucial to function as a risk management practice since uncontrolled risks may significantly impact the company’s profitability. Generative AI plays a crucial role in risk management, as it helps to determine risks before they occur and provides recommendations on how to avoided them. Using historical data, trends, and various indicators, Gen AI can predict potential disruptions and recommend ways of preventing or mitigating them.

For instance, in the financial sector of a business, Gen AI can look at the market tendencies, identify emerging economic risks that might affect either a company’s investment or operations. Through early identification of these risks, the AI enables the management to make necessary changes, including adjusting investment portfolios or resource allocations, to minimize loss. This proactive approach not only lowers the probability of losses, but also helps in better dealing with the budget management, as the resources can be distributed with more precision if the risks are taken into consideration.

Continuous Learning and Improvement

One of the major benefits of Generative AI is that it expands and develops a model while working on it. Unlike traditional systems, Gen AI receives new data more often and updates its algorithms for efficient resource allocation. This continuous learning process makes certain that the AI in cost management is always up to date achieving further improved levels of effectiveness and efficiency.

For example, in a retail context, Gen AI might initially analyze sales data to optimize inventory levels. As the customer data and seasonal trends are accumulated or the conditions of competition changes, the AI system would move to more effective recommendations of solution making the whole process cost saving and more efficient. Such continuous improvement process plays an important role in contemporary business environment in order to cope up with emerging business environments.

Conclusion

This is what generative AI is doing for businesses as it brings efficiency, flexibility, and profitability to resource management. Besides, more operational expertise, workforce and supply chain management, flexible pricing, and risk management allow Gen AI to greatly contribute to cost cutting and increased effectiveness. With the progressing advancement of Generative AI systems, it will be to businesses’ advantage to allocate the power of this technology to resource management. It is for this reason that cost management of the future is already here, and it is driven by Generative AI.

Original Source : https://bit.ly/4grgQU7

[dieterziegler159]

How Does Gen AI Make Resource Allocation Cost-Efficient?

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses.

See how Gen AI drives cost-efficient resource allocation with its data-driven approach, optimizing operations and cutting unnecessary expenses. In the contemporary business world, strategy implementation requires proper management of resources to sustain organizational competitiveness. Resource allocation is a critical capability for today’s businesses as it enables efficient and effective…

[reasonsforhope]

It’s an open secret in fashion. Unsold inventory goes to the incinerator; excess handbags are slashed so they can’t be resold; perfectly usable products are sent to the landfill to avoid discounts and flash sales. The European Union wants to put an end to these unsustainable practices. On Monday, [December 4, 2023], it banned the destruction of unsold textiles and footwear.

“It is time to end the model of ‘take, make, dispose’ that is so harmful to our planet, our health and our economy,” MEP Alessandra Moretti said in a statement. “Banning the destruction of unsold textiles and footwear will contribute to a shift in the way fast fashion manufacturers produce their goods.”

This comes as part of a broader push to tighten sustainable fashion legislation, with new policies around ecodesign, greenwashing and textile waste phasing in over the next few years. The ban on destroying unsold goods will be among the longer lead times: large businesses have two years to comply, and SMEs have been granted up to six years. It’s not yet clear on whether the ban applies to companies headquartered in the EU, or any that operate there, as well as how this ban might impact regions outside of Europe.

For many, this is a welcome decision that indirectly tackles the controversial topics of overproduction and degrowth. Policymakers may not be directly telling brands to produce less, or placing limits on how many units they can make each year, but they are penalising those overproducing, which is a step in the right direction, says Eco-Age sustainability consultant Philippa Grogan. “This has been a dirty secret of the fashion industry for so long. The ban won’t end overproduction on its own, but hopefully it will compel brands to be better organised, more responsible and less greedy.”

Clarifications to come

There are some kinks to iron out, says Scott Lipinski, CEO of Fashion Council Germany and the European Fashion Alliance (EFA). The EFA is calling on the EU to clarify what it means by both “unsold goods” and “destruction”. Unsold goods, to the EFA, mean they are fit for consumption or sale (excluding counterfeits, samples or prototypes)...

The question of what happens to these unsold goods if they are not destroyed is yet to be answered. “Will they be shipped around the world? Will they be reused as deadstock or shredded and downcycled? Will outlet stores have an abundance of stock to sell?” asks Grogan.

Large companies will also have to disclose how many unsold consumer products they discard each year and why, a rule the EU is hoping will curb overproduction and destruction...

Could this shift supply chains?

For Dio Kurazawa, founder of sustainable fashion consultancy The Bear Scouts, this is an opportunity for brands to increase supply chain agility and wean themselves off the wholesale model so many rely on. “This is the time to get behind innovations like pre-order and on-demand manufacturing,” he says. “It’s a chance for brands to play with AI to understand the future of forecasting. Technology can help brands be more intentional with what they make, so they have less unsold goods in the first place.”

Grogan is equally optimistic about what this could mean for sustainable fashion in general. “It’s great to see that this is more ambitious than the EU’s original proposal and that it specifically calls out textiles. It demonstrates a willingness from policymakers to create a more robust system,” she says. “Banning the destruction of unsold goods might make brands rethink their production models and possibly better forecast their collections.”

One of the outstanding questions is over enforcement. Time and again, brands have used the lack of supply chain transparency in fashion as an excuse for bad behaviour. Part of the challenge with the EU’s new ban will be proving that brands are destroying unsold goods, not to mention how they’re doing it and to what extent, says Kurazawa. “Someone obviously knows what is happening and where, but will the EU?”"

-via British Vogue, December 7, 2023

[probablyasocialecologist]

The latest, AI-dedicated server racks contain 72 specialised chips from manufacturer Nvidia. The largest “hyperscale” data centres, used for AI tasks, would have about 5,000 of these racks.  And as anyone using a laptop for any period of time knows, even a single chip warms up in operation. To cool the servers requires water – gallons of it. Put all this together, and a single hyperscale data centre will typically need as much water as a town of 30,000 people – and the equivalent amount of electricity.  The Financial Times reports that Microsoft is currently opening one of these behemoths somewhere in the world every three days. Even so, for years, the explosive growth of the digital economy had surprisingly little impact on global energy demand and carbon emissions. Efficiency gains in data centres—the backbone of the internet—kept electricity consumption in check.  But the rise of generative AI, turbocharged by the launch of ChatGPT in late 2022, has shattered that equilibrium. AI elevates the demand for data and processing power into the stratosphere. The latest version of OpenAI’s flagship GPT model, GPT-4, is built on 1.3 trillion parameters, with each parameter describing the strength of a connection between different pathways in the model’s software brain.  The more novel data that can be pushed into the model for training, the better – so much data that one research paper estimated machine learning models will have used up all the data on the internet by 2028. Today, the insatiable demand for computing power is reshaping national energy systems. Figures from the International Monetary Fund show that data centres worldwide already consume as much electricity as entire countries like France or Germany. It forecasts that by 2030, the worldwide energy demand from data centres will be the same as India’s total electricity consumption. 

30 May 2025

[dostoyevsky-official]

Palantir Surges Over 23% on Outlook Fueled by ‘Untamed’ AI Demand

Palantir Technologies Inc. shares jumped after giving a full-year revenue forecast that exceeded analysts’ estimates, thanks to what Chief Executive Officer Alex Karp described as “untamed organic growth” in demand for its artificial intelligence software. Best known for its national security work, and more recently its AI platform, Palantir’s stock surged 340% in 2024. The company rode a wave of investor excitement for AI, and more commercial and government customers started using Palantir’s data analysis software. [...] On a conference call after the results, Palantir Chief Technology Officer Shyam Sankar was asked about the potential effects of US President Donald Trump’s efforts to cut the federal government’s budget led by the Elon Musk-run Department of Government Efficiency. “Palantir’s real competition is a lack of accountability in government,” Sankar said. “DOGE is going to bring meritocracy and transparency to government” and prompt it to function more like the commercial market. [...] “We love disruption,” [CEO] Karp said on the call. “Disruption at the end-of-the day exposes things that aren’t working, there’ll be ups and down. There’s a revolution. Some people get their heads cut off.” [...] Citing the late political scientist Samuel Huntington, Karp wrote that “the rise of the West was not made possible ‘by the superiority of its ideas or values or religion, but rather by its superiority in applying organized violence.’”

[saturniandevil]

February 2025 Important Dates

AKA my notes on The Astrology Podcast's February forecast, hosted by Chris Brennan and Austin Coppock. Ironically I'm late for the shortest month of the year, but anyways let's get started.

January Recap: The year began on a Mars-Pluto opposition, coinciding with the attacks in New Orleans & Las Vegas. Mars retrograding into Cancer, the sign of the home, brought him closest to the Earth he gets during his orbit and signaled the beginning of massive wildfires in the LA area (Mars was also illuminated by the Cancer Full Moon). The Venus retrograde is also a factor here (Venus entered Pisces, the sign to which she'll regress later), though I don't quite agree with our hosts' decision to focus on chart for the incorporation of Los Angeles itself, as the worst-affected areas like Altadena, Malibu, and the Pacific Palisades are all separate municipalities--maybe a chart relating to Los Angeles County would be more fitting for a metropole that's so spread out. The TikTok "ban" story happened right as the Venus-Saturn conjunction went exact in Pisces, and the 75-day extension allowing it to operate right now ends on the day Venus will conjoin Saturn in Pisces while retrograde.

More Mars stories include Justin Trudeau resigning the day Mars regressed into Cancer. During the Mars-Sun opposition right on the heels of the Cancer Full Moon (January 14th-15th--midpoint of the retrograde), South Korean President Yoon Suk Yeol was arrested (who declared martial law on the Mars station). On the 15th during the Sun-Mars opposition we finally saw a ceasefire in Gaza, tying closely to Mars's position at 26 Libra on October 7, 2023. Mars-Sun developments and ~26 degrees of cardinal signs are definitely degrees to watch for this story. Venus's ingress and upcoming retrograde may also be indicating a return home for Palestinians displaced during the past 15 months.

Donald Trump's second inauguration was moved inside due to cold, the same as with Reagan's second term--another Venus retrograde in Aries time. Venus rx gives us comebacks, and not always ones we want. There was also a comet in attendance during this event, as was one during the April eclipse and during the election last year. His orders setting new ICE deportation/detaining quotas are a continuation of Mars entering Cancer last fall when this topic was first raised, and the Saturn-Neptune in Pisces story is also related.

The Sun-Pluto conjunction in Aquarius on January 20th-21st (& Uranus station surprising us) coincided with the US government investing $500 billion in AI, especially in power for the data centers (will nuclear energy come back as an alternative because of the massive power demand for this?), and DeepSeek surpassed OpenAI in popularity & use. The chart of the PRC has the Ascendant and Moon in early Aquarius, though the Pluto in Aquarius story re: China & technological innovations dates back thousands of years, pointing (in Chris's & Nick Dagan Best's opinion) to some older early chart now likely lost to time.

We entered the month of February right off Uranus's last direct station in Taurus before he enters Gemini in July, bringing disruptions and shakeups into the beginning of the month. (A/N: did anyone else have half their workplace out sick last week?) In Taurus, money can both disappear and come from nowhere--some surprises are good! Chris's electional chart was for February 1st so I'll skip it for this month.

February 1st - Venus conjunct Neptune The eclipse points, the Nodes, just changed signs, putting the North Node in Pisces with Saturn & Neptune, with Venus soon to join when she retrogrades. Events or people that seemed dreamy and rosy at the beginning of February may prove to be the opposite during the course of Venus rx. The North Node (Rahu, head of the dragon) brings a ravenous hunger to events.

February 4th - Venus entered Aries, Jupiter stationed Direct For Jupiter this is marks his last few weeks in Gemini for the next year or so. With a near-perfect trine to his ruler Mercury, we have an extra boost to our positive developments. Retrograde Jupiter is a good time to followup, and now that he's direct boons can move forward for us. Chris predicts some kind of development in voice AI technologies kickstarting around this time.

Venus ingressed from her exaltation of Pisces to exile (detriment) in Aries, and she's slowing down, making things a little more complicated than usual. With the upcoming retrograde, events we feel in our Aries houses will take three passes to full resolve this time around. She's going to be in this sign until March 27th, and will be back here from April to June. Venus in Aries can give us bombshell charisma, like that of Marilyn Monroe or Lady Gaga. Venus retrogrades have also aligned with large protest movements, especially around women's issues. Venus retrogrades in the same sign every 8 years, so look back to 2017 or 2009 for stories around this. Our hosts bring up how Lady Gaga exploded on the scene in 2009 and indeed she released a new song reminiscent of her early career right before the Venus ingress--right on time for Venus returning! In personal charts, Venus rx prompts us to reevaluate what we really want, sometimes deconstructing things to build them back up in a new way. Check your Aries house for which area of your chart where this will occur. Pay attention to cues of attraction and repulsion during this time.

February 9th - Sun conjunct Mercury This Mercury cazimi occurs closely square Uranus, an aspect that goes exact the next day. The disruptive Uranus events from the beginning of the month will come back to us.

February 10th - Mercury square Uranus

February 11th - Sun square Uranus

February 12th - Full Moon in Leo

This Full Moon occurs square Uranus just as the Mercury cazimi did. With Uranus in Taurus and the Sun in Aquarius, we can expect tech and finance to be at cross-purposes at this time. Electricity and energy will likely be key concerns around this time, especially around wrapping up the use of petroleum oil first proposed in 1855 (though it's not the only fossil fuel). Austin sees crypto as a premonition that energy may back future currencies instead of something like gold. Leo full Moons are always loud, flashy, and showy. This is the last full Moon before the Venus retrograde, before Inanna descends to the underworld, stripped of her ornaments and garments until she awkwardly meets Ereshkigal at the end of the elevator.

February 14th - Mercury enters Pisces Happy Valentine's Day!

February 18th - Sun enters Pisces

February 20th - Mercury square Jupiter

February 23rd Mars stations Direct From February 12th to March 9th, Mars will stay completely put at 17 degrees of Cancer. Anyone with placements at mid-cardinal signs, prepare for Mars to be there!

We're finally direct, but Mars gets going very slowly. "Let's train and prepare first instead of bolting ahead," he says. Projects that have been going on in this area of life may be finally paying off. Mars in the middle decan of Cancer is good for protecting, defending, and fortifying, including reinforcing or strengthening muscles or structures. The dark side of this, especially in world events, include nativism/nationalism, racism, and other us-versus-them aggression. However, Venus is set to react in a firey way to whatever events Mars sets off when she stations on March 1st. Cardinal risings will feel these stations especially strongly, possibly as turning points in conflicts, as these planets both station in angular houses for you.

February 25th - Sun conjunct Saturn

February 27th - New Moon in Pisces

The Mercury-Saturn conjunction (20-24 ♓) is still strong, possibly inhibiting communication, while Venus (10♈) and Jupiter (12♊) get about as close as they will to a sextile before she turns back to reevaluate things before fully realizing that positive thing. This stellium in Pisces (Sun/Moon/Saturn/Mercury/South Node/Neptune) takes us into a vivid, dreamy, and sometimes nightmarish space in stark contrast to the dry Aquarian energy we've experienced for much of the month. There are many strange creatures under the waves, not all of them real. Mercury will also be ramping up for a retrograde in Aries and Pisces as we get into early March, showing us even more events that we'll be returning to later. The end of February looks a lot like April; we're not gonna be done with this for awhile. With eclipse coming up, our sensory deprivation tank will become a sleep deprivation tank as we walk the edge of the coming maelstrom.

[drtanner]

[...] It found data centers will account for 8 percent of total electricity use in the United States by 2030, a near tripling of their share today. New solar and wind energy will meet about 40 percent of that new power demand from data centers, the forecast said, while the rest will come from a vast expansion in the burning of natural gas. The new emissions created would be comparable to that of putting 15.7 million additional gas-powered cars on the road.

We're in the middle of a climate crisis and tech corps are tearing down forests to build swathes of new data centres for generative AI that nobody wants, and it's sucking up so much energy that power grids are struggling to keep up with the demand. I don't care how much of the power it takes to produce AI slop comes from renewable sources; every drop of energy demanded by these data centres would be much better used literally anywhere else, and that's to say nothing about the obscene volumes of water it's using up, too.

The longstanding capitalist concept of "supply and demand" is a fucking lie, if it ever held a shred of truth in the first place. What gets sold to you has fuck all to do with what you need or want, and this is the best proof you're ever like to get. You exist to cough up the cash for whatever a billionaire wants to sell you, to grind away at your shitty little job in order to funnel more and more money to them. You are never going to exist as a human being with free will before the end of capitalism. You will buy the smart TV with AI in it, because there are no new TVs available for you to buy without it. You don't get a choice. Your purpose is to give the corporation back the money they poured into this AI shit so they don't have to take a loss on it.

Get involved in your local communities, do what you can to help people who aren't like you. If you're asking how you're supposed to help dismantle capitalism, that's where you start, by caring for people who aren't like you and doing your part to support others so that they can support you in turn. Kindness, acceptance and community with strangers is revolutionary; be tolerant of everything except intolerance, and as long as someone isn't actively trying to do you harm, welcome them in. A singular hero is not going to arise to lead everyone to the promised land and save the world. You cannot afford to sit and wait to be rescued. It has to be you and your comrades, and it has to be all of you.

If this AI shit hasn't shown you exactly how this world works and you aren't simultaneously enraged and terrified by it, I don't know what else is going to do it for you. Godspeed.

[mariacallous]

On Tuesday, President Donald Trump held a press conference to announce the signing of executive orders intended to shape American energy policy in favor of one particular source: coal, the most carbon-intense fossil fuel.

“I call it beautiful, clean coal,” President Trump said while flanked by a crowd of miners at the White House. The crowd chuckled knowingly at the now-familiar phrase. “I tell my people never use the word coal, unless you put ‘beautiful, clean’ before it.”

Trump has talked about saving coal, and coal jobs, for as long as he’s been in politics. This time, he’s got a convenient vehicle for his policies: the growth of AI and data centers, which could potentially supercharge American energy demand over the coming years. One of the executive orders signed Tuesday includes instructions to designate coal as a “critical mineral,” expedite coal leasing on federal land, and identify opportunities for expanding coal-fired power to support data centers.

Using coal to drive AI “would be one of the great technology ironies of all time: Let’s go to a 1700s technology in order to power 21st-century technology,” says Seth Feaster, an energy data analyst at the Institute for Energy Economics and Financial Analysis. “It really is a vast oversimplification of how power markets, power production, and the grid works in the US.”

In Tuesday’s presser, Trump, trodding familiar territory, targeted Democrats for the destruction of coal jobs as part of a “Green New Scam,” laying the blame on both Joe Biden and Barack Obama. In truth, though, coal retirement isn’t a function of who’s in the White House. More coal-fired power came offline under Trump’s first presidency than under either of Obama’s terms.

Unfortunately for Trump, the US coal industry suffers from some truly unavoidable economic realities. The last large coal-fired power plant built in the US came online in 2013; coal plants in the US are, on average, 45 years old. This aging fleet also has higher maintenance and upkeep costs for equipment than competing types of power. The fracking revolution in the 2010s—as well as the increasing availability of cheap renewables—has also made coal-fired power increasingly expensive. In 2023, just 16 percent of the US’s power generation was from coal, down from 51 percent in 2001.

With the executive order, Trump is “putting the thumb on one energy source in particular that happens to be one of the highest-cost energy sources,” says John Moore, a director at the National Resource Defense Council. “There are much cheaper and cleaner options.”

While coal’s downward turn in the US has been predictable, something has changed since the last time Trump was in office: AI. After remaining flat for several decades, various industry forecasts now predict skyrocketing demand for energy as companies talk a big game around plans for data centers. In September, Bloomberg Intelligence found that data center electricity use in the US could increase fourfold over the next five years, driven in large part by generative AI. Goldman Sachs, meanwhile, said in February that global energy demand from data centers could increase 165 percent by the end of the decade.

The promise of new demand is driving some utilities to reconsider scheduled coal plant retirements. In Virginia, where Amazon Web Services keeps 96 data centers and is investing $35 million to expand its campuses, the regional transmission organization, PJM Interconnection, requested a delayed retirement of two coal plants due to increased demand from data centers. Demand from Google and Meta data centers has also kept a coal-fired power plant in Nebraska online past its retirement date.

But keeping a patient on life support is substantially different than bringing a corpse back from the dead. A PJM executive said at a conference last month that he wasn’t sure if the market was “sending the signal right now that coal should actually stick around.” Building new, technologically up-to-date coal plants—an idea Trump floated at Tuesday’s presser—would be a hard sell in an economy where investors are wary of big capital investments for outdated technology. Tech companies, meanwhile, are focusing long-term energy investments on nuclear power, as well as renewables and battery technologies.

Even in states where coal wields political power, data centers haven’t proven to be a savior. In March, lawmakers in West Virginia attached provisions to juice up coal use to a bill intended to jump-start the data center industry in the state. Despite cheerleading from the governor, the bill ultimately passed without the coal provisions after Appalachian Power, West Virginia’s largest utility, intervened, claiming that the coal requirements would raise bills for customers. An executive told lawmakers that even a big new customer like a data center wouldn’t spur the utility to buy more coal-fired power; the regulatory and financial reality, he said, favors natural gas.

Regulations on coal plant emissions are a clear target for this administration. Last month, the EPA rolled out a suite of attacks on a wide swath of regulations, signaling its intent to reconsider everything from rules on power plant emissions to greenhouse gas reporting. The agency also created an email address to allow polluters to petition for a temporary exemption from mercury and air toxics standards set out under the Clean Air Act—known as the MATS rule—as the agency reconsidered a host of pollution rules. Montana’s Colstrip power plant—one of the dirtiest coal plants in the country, which was fighting upgrades mandated by an updated pollution rule—has already requested an exemption.

If the new executive orders are any suggestion, the Trump administration sees this deregulation, and the targeting of climate change policies, as a key element of propping up coal. A separate presidential proclamation released Tuesday extends the MATS exemption for an unknown number of coal plants, while another executive order tasks the attorney general with attacking state-level climate regulations, singling out Vermont, New York, and California.

It’s possible that costs for coal could come down slightly with fewer climate regulations. “You can run all these coal plants without environmental regulations or reduced environmental regulations—I’m sure that will save industry money,” Feaster says. “Whether or not the communities around those places really want that is another issue. Those environmental regulations are there for a reason.”

Costs, after all, aren’t just measured in dollars. Coal emissions include a mix of heavy metals and chemicals, including sulfur dioxide, that can be deadly to people living around power plants. A study published in 2023 in Science estimated that between 1999 and 2020, coal-fired power plants were responsible for 460,000 excess deaths in the US alone. Coal waste, meanwhile, is stored in toxic ponds of ash; spills have cost some utilities millions of dollars in settlements.

Utilities, Feaster says, have priced in the health risks of coal and the liabilities that come with coal into their decisions. But it’s not clear if the Trump administration understands these risks. Cuts at Health and Human Services this month have expelled workers involved in black lung research and other protections for coal miners at the National Institute for Occupational Safety and Health.

On Wednesday, as international markets melted down, Donald Trump posted an invite on TruthSocial to companies to move their business to the US. “No Environmental Delays,” he wrote. “DON’T WAIT, DO IT NOW!”

[public-cloud-computing]

Uncover the secrets of Gen AI in maximizing resource allocation efficiency, cutting costs, and enhancing business operations through smart tech.

[rubylogan15]

Uncover the secrets of Gen AI in maximizing resource allocation efficiency, cutting costs, and enhancing business operations through smart tech.