For years, sustainability reporting sat squarely on the shoulders of large corporations. Smaller suppliers were rarely pulled into the process, and certainly not at a detailed data level. That landscape is changing fast. With the introduction of the Corporate Sustainability Reporting Directive (CSRD), big companies are now expected to publish structured, verifiable climate information—and they can only do this with their suppliers’ support.

Tesla (TSLA) is making big progress in testing driverless robotaxis on public roads and attracting attention from analysts and investors. The company started testing its self-driving cars in Austin, Texas, on December 15. No human safety monitor was on board. This was a milestone that Tesla’s leaders said would happen by year’s end. This shift represents a key part of the EV giant’s long‑term strategy for autonomous vehicles and future mobility services.

At the same time, Wall Street firms, including Morgan Stanley, are issuing forecasts about Tesla’s robotaxi plans and their potential impact on the company’s future. Analysts calculate the scale of robotaxi fleets and potential valuation effects over the next decade.

These changes have kept Tesla’s stock in the spotlight for investors and the market, even with challenges in electric vehicle sales growth.

Driverless Robotaxis Hit Austin Streets

Tesla (TSLA stock)  began testing its self-driving cars on public roads in Austin, Texas. There were no human drivers or safety monitors in the front seats. CEO Elon Musk confirmed that fully driverless tests are happening. He sees this as an important step toward commercial operation.

Earlier in 2025, Tesla had already launched a limited robotaxi service in Austin using modified Model Y vehicles. Initially, these vehicles included a human safety monitor in the passenger seat to observe system performance.

Over the months, Tesla grew its service area and fleet size. By December 2025, reports showed about 31 active robotaxis operating in the city.

Recent tests without monitors show progress. However, they are still for internal validation, not for daily commercial use. Tesla confirmed that tests aren’t open to paying customers yet. The company hasn’t provided a specific date for when fully autonomous rides will be available to the public.

• RELATED: Tesla’s U.S. Robotaxi Launch: A New Catalyst for TSLA Stock Growth?

The Technology Behind Tesla’s Autonomous Effort

Tesla’s autonomous driving push relies on its Full Self‑Driving (FSD) software and onboard sensors. The FSD system can manage various driving situations. It uses cameras, radar inputs, and neural network processing. This differs from some competitors that rely on additional sensors such as LiDAR for redundancy.

In June 2025, Tesla shared its Q2 tech update. The company boosted AI training by adding tens of thousands of GPUs at its Gigafactory in Texas. This expansion supports improvements in FSD, where the company reported its first autonomous delivery. A Model Y drove itself without human help for 30 minutes.

Vehicles with FSD software need regulatory approval to drive on their own. In the Austin pilot, removing physical safety monitors marks progress toward that goal. Achieving fully reliable, unsupervised autonomy is still a challenge. This is true, especially when it comes to safety standards and different road conditions.

• SEE MORE on TESLA:
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• TSLA Stock Slides After Tesla Unveils ‘Affordable’ Model Y and Model 3 — Investor Confidence Wavers
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Wall Street Eyes Tesla’s Robotaxi Potential, Sending Stock Near Record Highs

Tesla’s autonomous ambitions are closely watched by financial analysts. Morgan Stanley just shared forecasts that say Tesla could greatly grow its robotaxi presence in the next 10 years.

The bank says Tesla might have 1 million robotaxis on the road by 2035. These will operate in various cities as part of its autonomous fleet plan.

Morgan Stanley’s analysis sees active robotaxi units growing in 2026. However, the first fleets will be small compared to the long-term plan. The forecasts show the possible size of the autonomous vehicle market. They also highlight Tesla’s role in this growth. However, there are uncertainties tied to technology and regulations.

Stock markets have reacted to these developments. Tesla’s stock price nearly hit record highs. It rose almost 5% during trading sessions. Investors were excited about progress in driverless testing and the promise of future autonomous revenue. Analysts say Tesla’s value might go up more if its autonomous services and AI products perform well.

Tesla’s Vision for Autonomous Mobility Services

Tesla’s robotaxi initiative fits into its broader vision of mobility services and artificial intelligence (AI)‑driven transport. The company plans to launch purpose-built autonomous vehicles, like the Cybercab. These vehicles won’t have traditional controls, such as steering wheels or pedals. They aim for mass production in April 2026.

Tesla sees a future where owners can add their cars to a decentralized robotaxi network. This could boost fleet availability and usage. This strategy could shift parts of Tesla’s revenue profile away from vehicle sales toward recurring service revenues if adopted at scale. The global robotaxi market could reach over $45 billion in 2030, as shown below.

Analysts say that major technical, regulatory, and safety issues still stand in the way of robotaxis operating widely and making a profit. Building public trust, meeting varied local regulations, and demonstrating consistent safety across different road environments will be key factors in future deployment.

Tesla vs Competitors and Safety Regulations

Tesla is not alone in the autonomous vehicle race. Other companies, such as Alphabet’s Waymo, owned by Alphabet, have been operating fully autonomous services in multiple cities for several years and continue to expand.

The company operates about 2,500 robotaxis across multiple cities. Waymo has logged millions of paid autonomous rides and already meets higher autonomy standards in some regions. In comparison, Tesla operates around 31 robotaxis in Austin, with plans to expand to several major U.S. cities by 2026.

Tesla chose camera-centric sensors over multi-sensor arrays. This decision shows their focus on scalability and cost. Critics and some experts argue that adding LiDAR or other sensors could improve safety and performance under challenging conditions.

Regulators also play an important role. In some states, pilot autonomously driven services are permitted under special testing allowances. Widespread commercial use needs approval from both state and federal agencies. This ensures that vehicles meet safety and operational standards.

What’s Next for Tesla’s Driverless Fleets

Tesla’s move to test robotaxis without onboard safety monitors in Austin marks a clear technical milestone, though it is not yet a commercial service. The company’s next steps will likely focus on scaling test fleets, improving software robustness, and navigating regulatory approvals to allow expanded operations in other cities in 2026 and beyond.

Morgan Stanley and other analysts think robotaxis might play a big role in Tesla’s growth. They could boost service revenue as traditional vehicle sales slow down. However, forecasts at this stage remain based on long‑range assumptions about adoption, pricing, and regulatory landscapes.

Investor sentiment has been mixed. Stock movements show excitement about tech advances but also worry about short-term vehicle sales and profit pressures in the auto industry.

Overall, Tesla’s autonomous ambitions continue to shape its corporate strategy and public profile. The speed of robotaxi rollout, along with improvements in Full Self-Driving software and AI, will be key to seeing if the company can shift from an EV maker to a driverless mobility platform.

• READ MORE: Tesla at a Crossroads: Sales Slump Meets Regulatory Headwinds But Stock Rises, Why?

The post Tesla Tests Driverless Robotaxis in Austin While Analysts Predict 1 Million by 2035 Growth, Sending Stocks Up appeared first on Carbon Credits.

More than 230 environmental and public-interest groups asked Congress to halt approvals for and construction of new data centers. They want a temporary national moratorium until federal rules address energy use, water needs, local impacts, and emissions. The request came from Food & Water Watch and was signed by national and local groups across the country.

They said that the fast growth of artificial intelligence (AI) and cloud services is putting big new demands on local grids and water systems. They also said current federal rules do not cover the environmental or social impacts linked to data center growth.

Why the Groups Want a Moratorium

Data centers are using more electricity each year. U.S. data centers consumed an estimated 183 terawatt-hours (TWh) of electricity in 2024. That was about 4% of all U.S. power use. Some national studies project that number could rise to 426 TWh by 2030, which would be about 6.7% to 12% of U.S. electricity, depending on growth rates.

Global data centers used around 415 TWh of electricity in 2024. Analysts expect double-digit annual growth as AI loads increase.

AI-ready data center capacity is projected to grow by about 33% per year from 2023 to 2030 in mid-range market scenarios. Industry groups say global data center capacity could reach over 220 gigawatts (GW) by 2030.

Some groups warn that data center CO₂ emissions might hit 1% of global emissions by 2030. That’s about the same as a mid-size industrial country’s yearly emissions. They say the growth rate is rising faster than the reductions in many other sectors. 

An excerpt from their letter reads:

“The rapid expansion of data centers across the United States, driven by the generative artificial intelligence (AI) and crypto boom, presents one of the biggest environmental and social threats of our generation. This expansion is rapidly increasing demand for energy, driving more fossil fuel pollution, straining water resources, and raising electricity prices across the country. All this compounds the significant and concerning impacts AI is having on society, including lost jobs, social instability, and economic concentration.”

When AI Growth Collides With the U.S. Power Grid

Several utilities have linked new power plant plans to data center growth. In Virginia, the largest power company and grid planners see data centers as a key reason for new infrastructure.

In Louisiana, Entergy moved forward with a new gas-plant plan expected to support a large hyperscale data center campus. These cases show how utilities now size new plants with AI-related load in mind.

Some utilities believe these expansions might increase local electricity rates by a few percentage points. This depends on how costs are shared. Regulators in various areas say that extra load can increase distribution and transmission costs. This might lead to higher bills for households.

Several grid operators also report congestion or long waiting lines for new power connections. Northern Virginia, Texas, and parts of the Pacific Northwest now have interconnection queues. In these areas, data center projects make up a large part of the pending requests.

• RELATED: Google and NextEra Team Up to Build Gigawatt-Scale AI Data Centers Powered by Clean Energy

Water Use and Siting Concerns

Water demand is another point of conflict. Many large data centers rely on water-cooled systems. A typical water-cooled data center may use around 1.9 liters of water per kWh. More advanced or dry-cooled facilities may use as little as 0.2 liters per kWh, but these designs are not yet common.

One medium-sized data center can use about 110 million gallons of water per year. Large hyperscale sites can use several hundred million gallons annually, and, in some cases, even more. Global estimates suggest data centers could use over 1 trillion liters of water per year by 2030 if growth continues.

These demands have triggered local resistance. In parts of Arizona, California, and Georgia, community groups have raised concerns about water use during drought periods. In some cases, local governments paused or limited data center approvals. A single campus can use more water each year than some small towns.

Trump Plans Executive Order on AI Regulation

While groups push for limits on new data centers, the White House is also preparing an executive order that would reshape AI policy nationwide, as reported by CNN. President Donald Trump has said he plans to issue an order that would block states from creating their own AI rules. 

The administration aims to create one national standard for AI. This way, companies won’t have to deal with different state regulations.

Drafts of the plan say the order may tell federal agencies to challenge state AI laws. This could happen through lawsuits or funding limits if the laws clash with federal policy. Supporters say a unified national rule could help U.S. companies compete globally and reduce compliance costs.

State leaders and consumer protection groups argue the opposite. They say states have a legal right to pass their own rules on privacy, safety, and data use. Some governors argue that an executive order cannot override state laws without action by Congress. Minnesota lawmakers, for example, continue to write their own AI bills focused on deepfakes and child-safety concerns.

The debate adds another layer to the data center issue. AI systems require massive computing power. If AI keeps growing quickly, analysts expect even heavier pressure on local grids and water systems. Advocacy groups say that this makes federal regulation more urgent.

Scale of AI and Hyperscale Build-out

The U.S. is in the middle of a major build-out of hyperscale and AI-optimized data centers. Industry trackers report that hundreds of new hyperscale facilities are planned or already under construction through 2030. Many of these campuses are designed specifically for AI training and inference workloads.

Major cloud and social media companies have sharply increased capital spending to support this build-out. Amazon, Google, Microsoft, Meta, and other major platforms, combined spending on AI chips, data centers, and network upgrades reached hundreds of billions of dollars per year in the mid-2020s. These spending levels signal how fast demand is growing.

• READ MORE: Amazon, X-energy, KHNP, and Doosan Partner on $50B Nuclear Push for AI Data Centers

Some experts track how major technology firms have changed over time. For example, one big cloud provider said its data center electricity use has more than doubled in the last ten years. This increase happened as its global reach grew. This gives a sense of how long-term trends feed current infrastructure pressures.

AI also adds new layers of demand. Training one large AI model can use millions of kilowatt-hours of electricity. Operating a popular chatbot can require many megawatt-hours per day, especially at peak traffic.

Research shows that processing one billion AI queries uses as much electricity as powering tens of thousands of U.S. homes for a day. This varies with the model’s size and efficiency.

Cities and States Move Faster Than Washington

Local governments have acted faster than federal agencies to respond to public concerns. More than 100 counties and cities have passed temporary moratoria, zoning limits, or new environmental rules since 2023. Examples include parts of Georgia, Oregon, Arizona, and Virginia, where communities plan to evaluate energy and water impacts before approving new projects.

Advocacy groups also argue that federal standards have not kept up. The U.S. does not have national energy-efficiency rules for private data centers. It also does not require detailed, mandatory reporting on energy, water, or emissions for the sector. The groups pushing for a moratorium say Congress must update these policies before more sites break ground.

What the Debate Means for 2026 and Beyond

Congress will review the environmental groups’ request in the coming months. Lawmakers are expected to weigh economic benefits against rising tensions around energy, water, and local resources. At the same time, the White House may release its AI executive order, which could shape how states and companies set their own rules.

With rapid AI growth, rising electricity use, and expanding data center construction, both debates are likely to continue through 2026. Many experts say long-term solutions will require national standards, better reporting, and closer coordination between states, utilities, and federal agencies.

• MUST READ: China Joins Google, Amazon, and xAI in the Race to Build AI Supercomputers in Space!

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