AI continues to be top of mind as a disruptive force to the ad industry as our members test, integrate and evaluate its impact to the value chain. Our Enterprise event earlier this year revealed that 89% of the IAB Canada community is currently, or planning to roll-out AI in their workstreams. Meanwhile, consumers continue to flock towards Generative AI tools furthering the mainstreaming of the technology. In the US eMarketer reports a whopping 900% growth in the use of the new technology indicating an extremely far-reaching adoption rate. Canada is not far behind.
The Canadian government is responding. The 2024 federal budget committed $2.4 billion to expand artificial intelligence initiatives in Canada. This comes on top of billions of dollars in financing from the government in previous years and a national AI policy.
While we all rush towards the mainstreaming of AI, we must carefully consider the impacts across several levels. The most common conversation tends to lean towards impact on jobs and the economy. IAB Canada and internationally has also been anticipating and monitoring other impacts associated with the immense computing power required to sustain the almost complete adoption of generative AI, and consequently, the energy usage that comes with this new reality.
Several other parties are also monitoring the situation on a macro-level. The International Energy Agency warned that “electricity consumption from data centres, artificial intelligence (AI) and the cryptocurrency sector could double by 2026.” Earth.org also reports that through a study with researchers at the University of Massachusetts, training AI models produce 626,000 pounds of carbon dioxide, or an equivalent of 300 round-trip flights between New York and San Francisco.
The struggle is hitting close to our sector. Despite major investments and general industry leadership towards reducing emissions, Google’s Annual Environmental Reports that in 2023, their total Global Greenhouse Gas (GHG) emissions increased 13% year-over-year, primarily driven by increased data center energy consumption and supply chain emissions.
It is quickly becoming clear that the growing and widespread use of AI for various applications can undermine sustainability initiatives. That being true, we must resist the quick, reflexive responses that may include halting AI research, development and usage until more environmentally friendly alternatives can be discovered. In fact, it may be that AI will produce its own solution if we allow it.
With its ability to provide knowledge, prediction, and optimization across sectors, AI has the potential to significantly reduce greenhouse gas emissions worldwide by 5–10% by 2030. Looking through Google’s reporting, there are some impressive applications for the use of AI that can help counter the emissions generated by computing alone. Here are interesting examples:
Business Optimization and ESG Reporting
AI can analyze large amounts of data. Deploying it for the purpose of analyzing energy efficiencies within an operation would be like having a sustainability specialist assess every facet of workflow in real-time that can offer suggestions as needed to keep on track with sustainability goals. Businesses may adjust in real time, avoiding possible environmental pitfalls, thanks to ongoing analysis.
Moreover, reporting on the viability and effectiveness of ESG initiatives can be simplified through AI, ensuring true and accurate understanding of its impact and potential for further development.
Minimize Emissions with Fuel Efficiency and Reduced Traffic
By utilizing AI, applications like Google Maps can determine the best fuel-efficient route by examining traffic, topography, and the car’s engine. Since the app enhancements in late 2021 until the end of 2023, it is anticipated to have enabled more than 2.9 million metric tons of GHG emissions reductions; that’s the equivalent of removing about 650,000 fuel-based cars from the road for a year.
Other traffic-related innovations include the ability to moderate traffic flow to reduce stop-and-go which is known to heavily exacerbate emissions. With the aid of an AI-based application called Green Light, municipal traffic engineers can better schedule traffic signals to minimize stop-and-go traffic and fuel usage. At crossings, this device can reduce emissions by up to 10% and stops by up to 30%.
Mitigating Impact to Environment
Machine learning has been used by Google to help consumers save energy and money at home with their Nest Learning Thermostats. Customers who used Nest thermostats in 2023 saved over 20 billion kWh of energy, which is equivalent to a reduction of around 7 million metric tons of greenhouse gas emissions.
Approximately half of the aviation industry’s overall global warming impact is attributed to contrails – clouds that occasionally appear behind aircraft. In collaboration with American Airlines and Breakthrough Energy, Google Research created an AI-based solution that securely reroutes aircraft to lessen the likelihood of contrail production. Predictive technology was used in a testing with 70 test flights, and it decreased contrails by 54%.
Apart from these, technology firms must do their part to increase sustainability initiatives to counteract any negative impact their AI development brings to the environment. Some of these initiatives may include building offices and manufacturing plants with sustainability in mind – leveraging renewable energy, developing partnerships with sustainably-committed organizations and implementing a culture of sustainability within.
Finding a balance will be crucial as we proceed. To build a more sustainable future, we must maximize the potential of AI and keep researching ecologically friendly energy infrastructure solutions. Governments, tech businesses, and individuals can ensure that AI becomes an effective tool for environmental advancement rather than a detriment by cooperating.
AI as with all emerging technology must be approached thoughtfully. Our industry has taken a significant leadership role in demonstrating not only the immense capabilities of technology but also our commitment and ability to self-regulate as we innovate.
Note: Featured Image in this articles is AI-Generated