A day doesn’t go by without another news story or report about artificial intelligence (AI) and its potential to disrupt and power to optimize. “It’s one of those game-changing technologies across almost every sector,” says Ian McCarter, director of corporate innovation partners at MaRS. “It offers companies so much more than just leveraging data.”
One area where it’s having an outsized impact is in the realm of climate solutions. AI’s ability to analyze immense amounts of data, as well as detect patterns early on and offer solutions, makes it a particularly useful tool in helping companies lighten their carbon footprint.
Decarbonizing heavy industry, electrifying transit and building new infrastructure will take years and a lot of capital to implement. In the meantime, AI platforms can help corporations and institutions start to meet their net-zero milestones. A 2022 report of the World Economic Forum concluded that in the energy, material and mobility sectors, digital technologies including AI could reduce emissions by as much as 10 percent by 2030 and up to 20 percent by 2050.
“All solutions are going to be needed to help organizations decarbonize,” says McCarter. “It’s all of the little changes that add up.” He brings up the example of a major food manufacturer that was able to reduce its energy costs by 4 percent and greenhouse gas emissions by more than 9 million pounds in just one year using Toronto-based Canvass Analytics’ AI platform. And while by no means can AI be the entire solution to carbon reduction, the opportunities the technology presents can help companies put a dent in emissions quickly and relatively inexpensively.
“No company can get to net zero without it,” McCarter adds. “Organizations need to adapt — or their competition will.”
Among the worst polluters are commercial and institutional buildings, thanks, in part, to heating, ventilation and air conditioning systems. In fact, 40 percent of annual global carbon dioxide emissions originate from the built environment, 27 percent of which comes from building operations. Montreal-based BrainBox AI uses AI to turn an existing HVAC system into a “predictive brain” to achieve ideal temperatures in all parts of a building with less energy.
In one instance, using AI and cloud computing, BrainBox enhanced a shopping mall’s HVAC system. The result: 16 percent lower HVAC electricity costs and carbon dioxide emissions decreased by 32 metric tonnes annually. Similarly, Burlington, Ont.-based Feedback Solutions’ technology uses sensors to continuously calculate the number of people in different zones in a building, so ventilation is based on actual demand. Doing so can reduce energy consumption by as much as 40 percent and preserve the life of HVAC equipment in the process.
For companies with real estate holdings, AI can provide a fast way to reach early milestones.
From local transit to long-distance trucking, AI’s real-time monitoring and prediction capabilities can help companies lower costs and energy expenditures through route planning, optimization and predictive maintenance.
One 2016 report of the U.S. trucking industry concluded that delay costs from congestion on the National Highway System were almost U.S.$75 billion and the lost productivity equivalent to 425,533 commercial truck drivers sitting idle for an entire year. And these numbers were pre-COVID-pandemic surge in e-commerce. In Canada, the transport sector is now the second largest source of GHG emissions; in 2021, it accounted for 22 percent of the country’s emissions. In fact, carbon emissions from freight travel have doubled over the last 30 years. Finding more efficient routes can help lower those stats while less carbon-heavy modes of transportation are scaled up.
Plus, there are solutions that ensure that fleets are operating at an optimal level. Startup Preteckt offers prognostics powered by AI so that maintenance issues in transit and trucking fleets can be caught earlier and fixed properly, which can help improve fuel economy. The company also leverages AI to identify issues in zero-emissions vehicles. “When it comes to those vehicles, there’s not just a technician shortage but there’s a lack of expertise,” explains Ken Sills, Preteckt’s CTO and co-founder. “AI identifies the problem and then the technician can focus on the problem without having to spend so much time diagnosing these large, complex issues.”
Its monitoring and prediction capabilities also make AI the logical choice for transit operations, balancing up-to-the-minute data about traffic and bus locations with user demand. In Belleville, Ont., for example, late-night buses spent hours-long shifts driving routes that catered to only a few dozen riders. But switching to Toronto-based Pantonium’s transit software and on-demand routes improved service dramatically. In fact, the city saw a 300 percent increase in ridership and a 30 percent decrease in vehicle mileage.
With the flow of goods slowed or stopped during the COVID-19 pandemic, supply chains were dealt significant blows — especially as companies needed to research suppliers manually. AI can help streamline the process — and provide significant cost and time savings — with up-to-the-minute supplier data. It can also help source local suppliers to help reduce emissions. “When you’ve invested millions and millions of dollars, not just in the money you’re paying your third-party providers but in the process of finding them, doing diligence, negotiating, onboarding them, the costs are ginormous,” says Stephany LaPierre, CEO and founder of Tealbook, which uses AI to collect information on every supplier that provides goods and services to an organization. “Then there’s the outcome. If you’re making decisions with limited information and poor-quality data, there’s a risk of not really knowing who you’re doing business with.”
When it comes to striving to meet climate goals, AI can also serve as a kind of sustainability officer. Toronto-based Manifest Climate, for example, offers AI-powered climate risk planning software that provides companies with analytics to ensure they stay on track. It also offers insights into climate trends and recommendations for achieving net-zero strategies.
As powerful as AI is, it’s no silver bullet. It’s simply one tool in a big toolbox. “All solutions are needed to help an organization decarbonize,” McCarter says. And as with any new, powerful tool, there are caveats. For one thing, policy and regulations around the rapidly evolving technology are lagging. And developing AI actually contributes to the climate problem; an article in the MIT Technology Review noted that developing and testing a single AI model may emit the equivalent of five American cars’ lifetime carbon dioxide emissions.
“So much of the challenge is not technical,” says Mark Abbott, who leads the Tech Stewardship program, a national initiative to train and support tech innovators on ethical AI at MaRS. “It’s about how we navigate different value tensions, like long-term sustainability and short-term needs of stakeholders. We need an energy future that’s net zero and inclusive, sustainable, as well as equitable and prosperous for all.”
To do that organizations and society as a whole must bring all voices to the table and examine all potential outcomes to decide the best way to steward this technology. “There’s really no other solution,” Abbott says. “AI has been put in everyone’s hands — the genie is out of the bottle. And if we don’t repeat the past mistake of just grabbing this shiny new tool as quickly as possible and be more reflective, we can find better ways to implement it.”
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Photo illustration: Monica Guan; Photo: Unsplash