Dec 7, 2021
By Jonathan Woods
On December 2nd, Vector hosted Accelerating AI-fueled growth for Ontario’s fast-growing companies, an event marking the launch of Vector’s new FastLane program, which is focused on enabling Canada’s small and medium sized businesses to unlock new growth using AI. The event included commentary from Vector leaders, Province of Ontario Minister Victor Fedeli, and a panel of businesspeople well-versed in the application and development of AI by growing companies.
Below are some of the day’s highlights. A video of the full event will soon be available on Vector’s YouTube channel.
Vector’s Chair & CEO Introduce FastLane
Vector President & CEO Garth Gibson opened the event, describing his excitement at “the potential FastLane can offer for Canadian jobs, competitiveness, and economic growth – made possible by the effective utilization of a key business capability: artificial intelligence.”
This key point – how proficiency with AI among growing businesses can translate into competitiveness, employment, and economic recovery – was then emphasized by Vector Chair Ed Clark. He remarked, “[AI’s] biggest contribution is in how it transforms existing companies. … Ontario is in a competitive death struggle for jobs. Key to winning that struggle is to have the people with the skills to employ AI and to have institutions like Vector who will work with companies to give them access to the latest techniques before their competitors in the world get them.” Clark echoed these sentiments in an op-ed, published in The Globe & Mail the same day.
While discussing the work Vector has done to support Ontario businesses in this global contest, he referenced the Brookings Institute report, The Geography of AI, which recognized Vector as “one of the most ambitious efforts in North America to upgrade a strong ecosystem into a world-class position.” [1] Regarding the ecosystem, he noted good news: Vector’s latest Ontario AI Snapshot showed that over $2 billion in venture capital investments flowed into Ontario’s AI ecosystem in 2020-21.
Clark also recognized the Province of Ontario’s role in funding Vector and FastLane, stating, “The work we’re doing to develop Ontario’s AI workforce and support small medium enterprises is an important part of strengthening Ontario’s innovation ecosystem and economy, and this would not be possible without the province’s generous support.” With that, he introduced Vector “friend and supporter” Minister Victor Fedeli, Minister of Economic Development, Job Creation and Trade for the Province of Ontario.
Minister’s Fedeli: FastLane is good for our business community, good for our province
“Now more than ever, we’re looking to the future towards Ontario’s economic recovery,” said Minister Fedeli. “Vector has an important role to play in how we get there,” he said, and has “cemented Ontario’s place as a global leader in AI.”
The Minister continued, “With more than 300 hundred AI firms already calling Ontario home, our government is committed to building it up even further,” noting that it’s essential for Ontario companies of all stripes – not only those that are AI-first – to adopt advanced technologies in order to compete. The FastLane program “is good for our business community, and it’s good for our province, and harnessing the potential of AI will help drive Ontario’s economic growth for decades to come,” he said, concluding his remarks.
Panel: Considering AI and key questions for small and medium businesses
The event capped off with a panel discussion moderated by Takara Small, a Toronto-based technology journalist who works as an on-air tech contributor to the BBC News World Service and a tech columnist for Metro Morning. The panel featured:
Here are some insights they shared:
Bannister: “AI can give [companies] a competitive advantage. It’s not about using AI [just] to say you use it, but about solving real-world problems and taking advantage of opportunities. Think about the entire spectrum of your business. We’ve seen and invested in companies that use AI to improve the research and development process; we have companies that use AI to improve the manufacturing process; we have companies that use AI to improve supply chain or logistics; or marketing; or the backend like HR and finance. AI really can take several different forms, but it’s important to think ‘Hey, as I establish my business and strategy, how can I leverage AI to achieve a competitive advantage in one or multiple areas?’”
Cohen: “When you’re in a really hot ecosystem, as a small early-stage company, recruitment is hard and retention is probably even harder. …On the AI side of things, we donate about 30% of our time to what the AI scientists would like to work on that may be on the margins or periphery of what we’re doing. Essentially it’s about creating cool stuff and it’s all about professional development, all about engagement. That’s helped us retain.”
MacLean: “The main thing to know is what problem you’re trying to solve. What challenge are you trying to address? … That translation of the business problem to an actual solution has to be very clear. … There are lots of times when an AI model is deployed, but it completely misses the challenge for the business. It’ll be deployed, it’ll be cool, but the actual bottom line of the business won’t change. It’s that translation that is so critical.”
Minor: “It could be any business size. The biggest thing is how you tackle the challenge or the project within the business and making sure you have very clear communications about what the expectations are going to be. … The biggest question I get: “We’re at day two of deployment. When’s it going to tell me how to do my stuff?” You need time. … Clearly articulate the scope and the specific timeline based on the size of the company and the amount of data they’re willing to give to the system. Having that two-way conversation with all your stakeholders, a real clear path forward, and a project charter that spells out where success will lie and what success will look like – the KPIs – I think that’s very critical.”
Cohen: “When you create a company that’s going to create AI, you discover early on that you need a human in the loop. At the start of data training, you need someone to label it properly. Then as you iterate and create and go along, you still need to bring people back in. The problem in many industries is that the labelling of data requires a subject matter expert. … When you’re looking at complex problems in industries like oil & gas, you need someone with years of experience to sit down and label that data properly. So the question: How do you get a subject matter expert to stop their job, sit down, and label your data?”
MacLean: “One of the crucial things we have to do is be intentional on diversity from beginning to end. So hiring talent that is diverse will make sure you get diverse input, which will make sure that data is being labelled with a diversity of perspectives and opinions. … Having that really intentional diverse workforce will make sure what we’re putting into the algorithm is a diverse dataset that will better reflect the population.”
Thank you to all of our attendees and participants!
Register for Vector’s FastLane program here.
[1] https://www.brookings.edu/wp-content/uploads/2021/08/AI-report_Full.pdf
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