AI-backed cleantech investment could grow fivefold


Staff reporter

Cleantech webcast says mining tech firm typical of early-stage funding spread

Increased investment in companies such as Canada’s Novamera could see venture capital deployment in AI-enabled cleantech explode over the next six years as start-up technologies build on early market traction and larger capital inflows are drawn to the nascent sector.

Ontario-based Novamera and its AI-assisted “closed-loop surgical mining process” was one of the case studies cited on a webinar this week by Cleantech Group’s Nino Lazariia and Nicholas Parker, founder of Canada’s Clean AI Initiative, to illustrate continuing growth in early-stage cleantech with integral AI product or service components at a time of falling overall cleantech VC funding.

“There are so many reasons to be interested in this,” Parker said.

“One observation about it is the integration of hardware and software. Their borehole imaging technology collects all the data, but again, now we have the ability to deal with that data.

“It’s dealing with critical minerals in a way where hopefully we won’t destroy the environment as we try to save the atmosphere.

“We’re going to need companies like this because we’re going to need the metals and the minerals to get us into the energy transition.”

Lazariia said an estimated US$28.5 billion of $223 billion of VC investment in cleantech innovation between 2018 and 2023 had been spent on AI-enabled cleantech.

“More than 12% of all cleantech solutions [developed over the past six years) have been AI-enabled,” she said.

The $28.5 billion could be expected to expand to circa-$69 billion from 2024 to 2029 under Cleantech Group’s “base case” forecasts. However, the research and advisory firm says this could accelerate to $138 billion if an exponential rate of technological development could be translated into value across pivotal industry sectors.

Lazariia said the highest level of AI-enabled cleantech investment over the past six years had been in Cleantech’s agriculture and food industry group, with more than $11.7 billion outlaid.

“About 30% of that has been in precision agriculture,” she said.

“The next biggest group is energy and power with $7 billion.

“With that group fusion and energy storage have received more than two-thirds of all venture investments.”

The resources and environment group has seen a consistent circa-$1 billion of investments in AI-enabled cleantech innovation over the past two years, up from the level in 2021.

In 2023 overall cleantech VC investment fell, but early-stage funding continued to climb.

Seed and series A investments in 2018 totalled $735 million, or 26% of total investment. Lazariia said the start-up funding share of total cleantech VC investment was 38%, or $1.9 billion, in 2023. This meant plus-160% growth from 2018 to the end of 2023.

“Investments in early-stage companies and start-ups not only did not drop, but actually have risen,” Lazariia said.

“That trend we have seen throughout the years.

“That’s [$1.9 billion in 2023] quite significant in my opinion.

“We could see a lot of investments and follow-ons for those young companies.

“Another trend that we see is that most [AI-enabled cleantech] innovators are at an early stage. Around 70% of all deals are dedicated to early-stage start-ups. A lot of innovators are early in their development.”

Canada’s global innovation cluster for digital technologies, DIGITAL, has co-invested C$3.5 million in a new Novamera demonstration project focused on a high-grade gold deposit in Newfoundland. A sample is expected to be “surgically” extracted with the aid of Novamera’s technology in the fourth quarter this year.

Novamera is also looking to advance other projects, including critical minerals extraction ventures.

Lazariia said the use of AI in mineral orebody definition and extraction could help the mining industry unlock “the estimated trillion dollars of resources in hard-to-access deposits or formerly uneconomic mines”.

“It results in an estimated 95% waste reduction and 50% cost reduction.

“It improves exploration success rates and reduces financial risks, reducing the need for invasive exploration practices.

“AI enables more accurate prediction of mineral deposits and helps to identify patterns from previous exploration.”

 

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