AI and the future of business

If AI can be most simply explained as the combination of computers and data to mimic human behavior, like performing tasks or solving problems, machine learning is just one of the ways through which AI can be developed. 

 “Machine learning is nothing on its own; simplified,  it’s  about using data to optimize business processes, said Cory Janssen, co-founder and co-CEO of AltaML, a leading Canadian applied AI company. The secret to successfully leveraging AI, he says, is to ensure that an organization’s technology strategy is fully aligned to their corporate goals, including support at the highest level. 

“Those days of just hiring a few tech people are done,” Janssen told the business audience. “Now it’s a matter of bringing the right people to the table who understand how we take our strategy and use data to further that. How do we invent new lines of business, and how do we take those core elements of business and use AI to inform and improve it?”

“The value of using the science of AI to solve business problems is huge,” added Cam Linke, CEO of Amii (Alberta Machine Intelligence Institute). 

“We are one of the top three places for artificial intelligence development in the entire world. I want to repeat that because we’re talking about the most impactful technology in the world right now. How many things in the world does Alberta  rank in the top three?  One of them just happens to be  a most important technology in the world - that is going to change economies in a way we haven’t seen since the industrial revolution. We are in a pretty special spot.”

What are companies getting wrong about AI?

Investing in AI as a means to solving our greatest problems should be the fundamental focus, said panelists. Despite its perception of being too new or flashy, “Alberta has been investing in AI for decades,” Linke said.

A commonly held misconception is that companies believe they must build a program from scratch. “One of the biggest changes industry has seen around AI is ease of adaptation, as there are more basic tools readily available,” said Godard, chief operating officer and co-founder of Verge Ag. 

Verge Ag’s purpose is to accelerate the transition to autonomous farming. “When I explain our purpose to new staff or investors, they immediately think of self-driving tractors,” Godard said. He explains that farmers are tapping into technology more than ever to improve efficiencies, output and overall productivity on their farms, and AI is helping them make the transition. While self-driving capability is useful, being able to efficiently manage all their land and equipment though remotely executed field operations is what will make them truly autonomous."

Leveraging AI in the race for autonomy is about learning from existing practices, and adopting software that uses machine learning to capture what farmers do on a daily basis. “We can train our modules for current behaviour, which can then be optimized in the future for adopting autonomous technologies,” he explained.

Another challenging issue for businesses is not having a cohesive strategy around the use of AI. This can be the result of department silos, each having their own AI teams, rather than building on and sharing information. Centres of excellence, utilizing hub and spoke models, have proven to be valuable, said Jenssen. By delivering best practices and tool sets that are standardized across an organization, teams work together with data scientists to create solutions.

The importance of developing AI in Alberta

McKinsey & Company estimates the value of AI at over $13 trillion to the global economy over the next decade. AltaML believes that hundreds of millions of dollars (if not more) of economic value are at stake in Alberta alone.

In order to sustain Alberta as an innovation centre, the province needs to attract talent and investment. “We need more companies to build an ecosystem with a talent pool that exists inside the province so we’re not fighting with external companies,” said Godard.

A good example of fostering a rich technology environment is AltaML’s Applied AI Lab, The program, sponsored in part by ATB, provides internships to individuals - often Alberta engineers seeking a new opportunity in data science - to get real-world experience;, a kind of finishing school for data scientists that opens doors and drives AI integration.

Investment for tomorrow

Godard spoke of the importance of partnerships across  academia, governments and business to build a strong community of opportunities, investment and talent.Without investment, Alberta runs the risk of falling behind its competitors.“If you aren’t investing in AI, your competitors are,” noted Linke. The opportunity for the province is to ensure the academic and business communities are incented to continue working together to lead innovation. Investment over the next four years will determine the next four decades of AI potential for the province, he said.

A possible threat is a proposed $222-million funding cut to the University of Alberta – which houses 150 grad students. There are 70-100 new grad students admitted into Computer Science every year. 

Why does funding education around AI matter? Machine learning doesn’t apply to just one industry, it works and optimizes all sectors, panelists said. “We do not need to turn our back on what made Alberta great. We do not need to turn our backs on energy, or agriculture,” said Jessen. “We can build on those solid pillars using this technology to be able to export our ingenuity – that’s how we create wealth in Alberta for 2030 and beyond. That’s why this matters.”