Real Life Uses For AI

[Paul Kelly ICHYB]

I have started using it for simple things like creating images or the odd bit of copy.

During the week, I was introduced to a platform that offers a suite of AI 'employees' (there are several) and it looks interesting - it can create a post SM content (at your instruction), sort and reply to email, do sales stuff, manage calls etc. Not sure how much I would want to really use.

Posts here have shown people writing code and doing bits and bobs, but what are your real-life uses that have made AI indispensable or, at least, worth the investment?

 

[Newchodge]

Has anyone asked their AI what the environmental cost of all AI in the world is currently?

 

[WaveJumper]

Well you did ask

Here’s a current global snapshot of the environmental cost of all AI (as of early 2026) — including energy use, carbon emissions, water consumption, and broader impacts — based on the latest research and industry estimates:

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1. Energy Consumption — Massive & Growing​

• Data centers globally (which host AI workloads) consumed about 460 terawatt-hours (TWh) of electricity in 2022 — making them roughly as significant as a medium-sized industrial nation in power demand.
• AI workloads are a rapidly increasing share of that demand: by some estimates, AI could account for roughly 20–49 % of overall data centre electricity use by 2025, with projections suggesting a dominant role by this decade’s end.
• Global electricity demand in data centers could approach ~1,000 TWh by 2026 because of AI growth, roughly comparable to the entire electricity use of countries like Japan or Germany.

What this means: AI — especially large models like ChatGPT-class systems — is already a major electricity consumer worldwide, and its share relative to other digital workloads is rising fast.

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2. Carbon Emissions — Significant and Rising​

• A recent analysis estimated AI-related data center operations produced roughly 105 million metric tons of CO₂ in 2024, a footprint comparable to or exceeding the global aviation sector’s emissions (which is ~2 % of global emissions).
• Some aggregated estimates suggest AI systems contribute ~2.5–3.7 % of global greenhouse gas emissions today, and that this could grow rapidly if powered by fossil-heavy grids.
• These figures include both training major AI models and the daily use (“inference”) by billions of users around the world.

Put another way: AI’s carbon footprint today is large in absolute terms and comparable to major industrial sectors, and it still may be underestimated due to incomplete disclosures from big tech companies.

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3. Water Use — Often Overlooked but Substantial​

• Data centers require huge amounts of water for cooling servers. One recent projection estimated hundreds of millions to over a billion cubic meters of water use annually tied to AI systems — comparable to the yearly water usage of several million people.
• With AI expansion, water use could increase severalfold by 2027, putting stress on local resources in water-stressed regions.

This is a secondary environmental cost beyond carbon and energy, but it matters because it affects water availability and local ecosystems, especially where power and water grids are already stretched.

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4. Other Environmental Costs​

Raw Materials & E-Waste​

• AI infrastructure depends on rare materials (e.g., lithium, cobalt) for chips and batteries. Mining these often has toxic pollution and social justice implications.
• Rapid hardware turnover contributes to growing e-waste challenges in many developing countries.

Efficiency & Transparency Challenges​

• Not all AI models are equally energy efficient. Some small models use orders of magnitude less energy per taskthan big LLMs.
• Conversely, the lack of public disclosures from major AI firms makes precise accounting of global environmental impact very difficult.

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Big Picture — How AI Compares​

Environmental Measure	Approximate Contribution Today
Global Data Center Electricity	~1–3 % of world electricity
AI Share of Data Center Power	~20–49 % and climbing
Global Emissions from AI Systems	~2.5–3.7 % of global GHG emissions
Water Use by AI Cooling	Hundreds of millions to >1 billion m³ annually

(These are best-available estimates with significant uncertainty — real figures may be higher or lower depending on energy sources and unpublished company data.)

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Why This Is Hard to Pin Down​

• Lack of transparency: Many tech giants don’t share detailed energy and emissions data for specific AI services.
• Rapid growth: AI compute workloads are expanding extremely fast — doubling compute demands in months — making static figures quickly outdated.
• Mixed energy sources: The carbon footprint depends heavily on where AI workloads run — whether the grid is powered by renewable energy or fossil fuels.

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In Summary​

AI already has a measurable global environmental cost — in terms of energy demand, carbon emissions, water use, and material impacts.
Its footprint is growing rapidly, and estimates suggest it rivals major sectors like aviation in carbon output.
Future projections show AI’s share of data center power demand and emissions could climb substantially by 2030 unless offset by cleaner energy and efficiency improvements.

 

[WaveJumper]

Basically it looks like with both Ed and AI we will probably be getter rolling power cuts in the very near future

 

[NickGrogan]

Use AI every day, probably too much.

written software
written WordPress plugins
written complete websites - good conversion rates and SEO
found domains to register
found large open source databases
created new products

 

[Paul Kelly ICHYB]

@WaveJumper did you use AI to research that info?

 

[WaveJumper]

Of course, plus in general use every day for research into companies quick and easy, great for breaking down company accounts AI makes it a lot easier especially in my game. There's a lot of ball out there regards AI trading "platforms" or more specifically trading tools but i would treat therm with a lot of scepticism there basically running off trading signals which already exist, but thats a whole other rabbit hole I am not going down on here.

I would say in respect of the thread my sons own business is using AI for bookkeeping, linking & making use of functions within Xero, saves employing a book keeper apparently, plus the obvious dealing with emails, email responses, creating quote responses, filing, dealing with online social media content. From the outside looking in, to me it looks like (if understood and embraced) in can save a lot of time, and helps the bottom line, more importantly is here to stay.

 

[Newchodge]

Given the environmental cost, I think there is a huge problem coming!

Thanks for the data, @WaveJumper