Canada is often touted as an early leader in the global artificial intelligence (AI) race, and in many ways this assessment is correct. We have world-leading AI researchers and research institutions, substantial public sector investments, as set out in the most recent federal budget, and a proliferation of promising AI start-ups. Unfortunately, when it comes to AI’s potential impact on Canada’s economy, we are starting the race several steps behind.
For Canadian firms to capture the value of AI and translate our strong knowledge base into future economic growth, we must make immediate and sizable complementary investments into everything from structured data to redesigned workflows. Perhaps most important, we must also invest in the leadership and talent needed to effectively integrate AI systems into existing businesses.
But to date, when we think of AI talent, we immediately focus on machine-learning experts. And while having technical expertise is absolutely indispensable, to win the AI race we need a more holistic understanding of what constitutes an effective AI team, from the C-suite to marketing and business development.
Why Canada is an underdog in the AI race
Because it is a general purpose technology (GPT), the promise of AI lies in its ability to enhance economic activity and growth in sectors across the economy — from managing supply chains in manufacturing to diagnosing diseases in health care. Unfortunately, Canada’s track record of adopting and translating new technologies into economic opportunities for Canadian companies is spotty at best.
From the 2008-09 recession until 2014, real investment in one of the most important GPTs of our time, information communications technology (ICT), shrank by an average of 1 percent per year across the Canadian economy, compared with 2.9 percent annual growth in the United States. Given ICT’s prominent role in improving productivity, it is no surprise that this slowdown in investment played a major role in Canada’s poor productivity performance during that period.
While it is still early days, there are signs we may be following the same path with AI, as many Canadian businesses are choosing not to invest in the adoption of intelligent technology. Are we doomed to repeat history? If not, what can we do to realize the full potential of AI for Canada’s economy?
The adoption puzzle
As with other GPTs, adopting AI and reaping its economic rewards requires significant complementary investments, a process that can take years if not decades. Just think of any corporate IT project that you’ve seen being launched. While the technology might be there, integrating effective technological solutions for business challenges is an exceedingly complex and difficult task that few get right, and failure is often inevitable.
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A recent study by Deloitte found that only 16 percent of Canadian firms were using AI, a proportion that has remained unchanged since 2014, and only 8 percent of companies surveyed planned to increase their AI spending by more than 20 percent in 2019. Similarly, a 2018 McKinsey study found that while 89 percent of Canadian executives agree that AI will create substantial near-term value for their company, only 34 percent have developed a corporate AI strategy. Many Canadian firms are hesitant to adopt the technology because they lack certainty about the value that AI can bring, while others don’t have a reliable playbook describing the process for integrating the technology into their companies and assessing the return on that investment.
These decisions and attitudes all represent sizable obstacles to realizing the benefits of new AI technologies. What would help Canadian companies across the economy gain an edge in the global AI race?
Building Team AI Canada
Canadian firms looking to adopt AI will need a broad range of talent, not just machine-learning experts. Integrating complex AI systems will require workers who can, for example, bridge the gap between AI technologists and business professionals, clean and prepare data, and ensure that any unintended consequences are addressed.
There are still major gaps in our understanding of the many specific roles that Canadian firms should be hiring for, what existing pools of talent they can potentially tap into, and how we should be thinking about building a talent pipeline that meets demand. New research is also needed to examine the workflow and business processes required to enable these teams to function as effectively as possible.
Strengthening our knowledge about the key factors associated with AI implementation will support businesses and policy-makers alike in their shared endeavour of boosting wide-scale adoption of this competitiveness-enhancing technology. The race to take advantage of the benefits of AI is just beginning, and while Canada has started out at the back of the pack, we have the opportunity to make informed investments in complementary components such as talent, data, and infrastructure to ensure our businesses attain a competitive advantage at the global level.
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