AI Video Generation: A Lower-Carbon Path for Advertising Production

Written By Guest User

Scary Robots

8 Nov 2025 - by Jason Attar

The Carbon Question We Need to Ask

As the advertising industry grapples with its environmental responsibilities, a significant development has emerged: AI-generated video content appears to offer substantially lower carbon emissions compared to traditional production methods. But what do the numbers really tell us, and how should we interpret them?

Understanding the Traditional Production Footprint

Let's start with what we know about traditional advertising production. According to AdGreen's comprehensive data from analysing over 2,300 completed projects:

  • Travel and transport account for over 70% of production emissions

  • Materials contribute approximately 10%

  • Film spaces and accommodation each represent around 7%

The carbon footprint varies dramatically by production scale. A typical advertising campaign including a TV shoot can generate up to 200 tonnes of CO2e, though smaller productions average considerably less. A standard digital campaign for a luxury brand can exceed 320 tonnes of CO2eq over one month.

For context, TV production creates 8,200kg of CO2 for every hour of broadcast-ready content. A typical 30-second commercial, depending on its complexity, locations, and crew size, generally produces between 20-100 metric tonnes of CO2.

The AI Production Alternative

AI video generation operates on fundamentally different principles. Synthesia reports that generating a minute of AI video averages around 0.00025 kg of CO2e – about 200 times more carbon efficient than boiling a kettle.

When we look at video production specifically: if traditional production methods had been used for the 136,120 hours of video generated through Synthesia in 2024, it would have led to an additional 215,712 metric tonnes of CO2 being released – equivalent to the emissions of 42,086 UK homes.

The key difference lies in what's NOT required:

  • No crew flights or ground transportation

  • No location scouting or permits

  • No physical sets, props, or costumes

  • No catering for 30+ person crews

  • No generators or production vehicles

  • No hotel accommodations

Critical Context: The Complete Picture

AI's Growing Energy Demands

While individual AI generations are efficient, we must acknowledge the broader context:

  • Google's 2024 environmental impact report revealed a 13 per cent increase in carbon emissions year over year, partly due to its generative AI initiatives

  • The energy demands of text-to-video generators quadruple when the length of a generated video doubles

  • Training GPT-3 consumed 1,287 megawatt hours of electricity, generating about 552 tonnes of carbon dioxide

Important Assumptions and Limitations

The comparison between AI and traditional production involves several key assumptions:

  1. Quality parity: These calculations assume the output serves similar purposes, which may not always be the case

  2. Infrastructure costs: AI emissions don't fully account for data centre construction and GPU manufacturing

  3. Human displacement: The social and economic impacts of replacing human creative work aren't captured in carbon metrics

  4. Rebound effects: Lower costs might lead to increased production volume, potentially offsetting carbon savings

The Business Case Beyond Carbon

The carbon advantage is just one factor. AI video generation also offers:

  • Speed: Minutes instead of weeks for production

  • Cost efficiency: Dramatically lower production budgets

  • Accessibility: Democratising video creation for smaller businesses

  • Iteration: Easy testing and refinement of content

A Balanced Path Forward

This isn't about replacing all traditional production—that would be neither realistic nor desirable. Traditional production brings irreplaceable elements:

  • Human creativity and emotional depth

  • Complex narratives and nuanced performances

  • Cultural authenticity and artistic vision

  • High-stakes brand moments requiring premium quality

Instead, we should view AI as an additional tool in the production toolkit, particularly valuable for:

  • Internal communications and training videos

  • Social media content and quick turnarounds

  • Personalised content at scale

  • Pre-visualisation and concept testing

  • Lower-budget campaigns that previously couldn't afford video

Industry Progress and Adaptation

The traditional production industry isn't sitting still. From LED lighting to virtual production stages, the industry is finding ways to reduce its impact. AdGreen's carbon calculator and industry initiatives show genuine commitment to improvement.

However, even with these innovations, the structural differences make it challenging for physical productions to match AI's carbon efficiency for certain types of content.

Recommendations for Advertisers

  1. Assess each project individually: Consider the content needs, quality requirements, and carbon implications

  2. Use AI for appropriate content: Internal videos, social content, and rapid iterations are ideal candidates

  3. Maintain traditional production: For hero campaigns and emotionally complex narratives

  4. Measure and report: Use tools like AdGreen's calculator to track emissions across all production types

  5. Invest in innovation: Support development of both cleaner AI systems and greener traditional methods

The Data-Driven Reality

When we look at the numbers objectively:

  • A traditional 30-second commercial: 20-100 metric tonnes CO2

  • An AI-generated equivalent: 1-5 metric tonnes CO2

  • Potential reduction: 80-95%

These aren't marginal improvements—they represent a fundamental shift in production emissions for appropriate content types.

Moving Forward Responsibly

The advertising industry faces a choice: embrace AI video generation where appropriate while continuing to value and invest in human creativity where it matters most. This isn't an either/or decision—it's about using the right tool for the right job, with carbon footprint as one important consideration among many.

As we navigate this transition, transparency and honest assessment will be crucial. The numbers suggest AI video generation can significantly reduce production emissions for certain content types. The challenge now is implementing this technology thoughtfully, ensuring we maintain creative excellence while reducing our environmental impact.

Traditional production will continue to play a vital role in advertising. But for the growing volume of content that doesn't require full production resources, AI offers a lower-carbon alternative that the industry can no longer afford to ignore.

What's your organisation's approach to balancing creative needs with carbon reduction? How are you evaluating AI tools in your production pipeline?

Sources and Further Reading

Key Data Sources:

Traditional Production Emissions:

AI Energy Research:

Industry Resources:

#SustainableAdvertising #AIProduction #CarbonFootprint #GreenMarketing #AdvertisingInnovation #ClimateAction #AdTech #Sustainability #tvadvertising

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