Canadian executives have reported unevenly increased efficiency and lack of technical talent from AI, the Georgian study found.
As many companies compete to adopt artificial intelligence (AI) tools around the world, a new report from Georgian Partners at Toronto Venture Capital (VC) companies suggests that most Canadian companies are learning to walk when they are working on improving barriers and mixed efficiency.
Approximately 48% of Canadian technical executives in the survey said lack of technical talent is a challenge that hinders AI adoption.
According to the report, Canadian companies with annual revenues of over $5 million continue to follow suit when implementing AI for marketable and product strategies, compared to their global peers.
Georgian categorizes companies based on the size of “AI maturity” in the crawl, walk, jogging and running categories. Only 7% of Canadian technical respondents identified them as “runners” with significant budgets consistent with a sophisticated portfolio of AI projects, compared to 17% worldwide.
The report was conducted in collaboration with market research firm Newtonx, and surveyed 634 business executives worldwide through a 15-minute online survey.
The findings are due to increased pressure for Canadian companies to adopt AI from leaders from leading high-tech companies with large investments in technology and leaders such as Canadian AI Minister Evan Solomon. At the Toronto Institute of Technology Weekly Panel, hosted by Toronto-based Vector Institute and hosted by Bettakit reporter Josh Scott, Georgia machine learning engineer Royal Sequiilla previewed the findings of the study along with Craig Stewart, executive director of the Vector Institute's Applied AI program.
“At Vector, the core of our principles is the safety and trust of AI,” Stewart said. “At the same time… our adoption rates in this country are too slow, so we encourage them to go to the market much faster and sell these products and services.”
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Stewart argued that while most companies focus on “back-office” capabilities as a starting point for adopting AI, they should accelerate adoption of AI in consumer-oriented capabilities. According to a Georgian report, Canadian technology teams are 12 percentage points below the global average when implementing AI for customer service capabilities.
“We want to move that bar and get to the podium,” Stewart said.
The report noted that Canadian companies face unique barriers to AI adoption. Approximately 48% of Canadian technical executives in the survey said lack of technical talent is a challenge that hinders AI adoption. According to Georgian, this is four points higher than the global average.
The next most important barrier was the high cost of model training and deployment, Georgian added. Additionally, Canadian technical teams are less likely to build their own models than their global counterparts. Instead, they are purchasing solutions from third parties. These respondents stated they manage costs associated with AI.
To offset the cost of investing in AI, 34% of Canadian technology executives surveyed say their staff is declining. This follows the recent company-wide “AI-First” delegation from prominent Canadian tech companies such as Shopify. Kitchener-Waterloo-based company Opentext fired 1,600 employees in May as part of its AI First Policy. Vancouver-based software-As-a-Service (SAAS) Startup Klue last month cited a bid to cut 40% of its workforce and increase internal and external pressures and efficiency from AI.
At StartupFest in Montreal, Georgian's lead investor Evan Kerr said it is a key concern for AI adopters, according to global and Canada-specific data in the report. Kerr encouraged founders who sell AI products to have a “solid perspective” when defining their clients' ROI.
“We see a lot of contradictions in the way businesses are talking about. [ROI]Kerr said. “Some of the answers say [they] Not translating specific revenue or cost targets into AI [they’re] Entering production. ”
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Part of the challenge is determining reliable ways to measure the direct impact of new AI tools. Fifty percent of Georgian Survey technical respondents found it difficult to connect AI projects to revenue, Sequeira said in the week of the Toronto Institute of Technology.
“This may be because they already employ AI within their teams without really thinking about how they will connect to the business,” Sekiira added.
Some companies that sell AI products for businesses have heard mixed results from client companies piloting AI projects. Cohere co-founder Ivan Zhang told Web Summit Vancouver's Betakit that many of his clients have not seen the return on investment from spending on AI proof-of-concept projects. Zhang said that costs are a barrier as AI models are expensive to implement.
Georgian's report found uneven improvements in efficiency from AI across Canadian executives surveyed. Some self-reported metrics, such as product release quality and technical debt reduction, nearly half of Canadian respondents reported benefits from AI implementation. However, in terms of business metrics, Canadian respondents reported a lower impact of AI on net retention and cost reduction compared to global peers.
Other independent studies found similarly mixed results. A recent Economic Research Bureau working paper surveyed 7,000 workplaces and determined that AI chatbots had an impact on revenue and “do not significantly affect occupational revenue or recorded time.” Another study from the Boston Consulting Group found that only a quarter of the 1,800 executives surveyed had great value from AI so far.
Features Image Courtesy Vector Research Institute Jennifer Jenkins.
