Two scientists working with microscope

Artificial intelligence will underpin Canadian innovation and global competitiveness

Innovation & Technology

By: Andréa Nadeau

This op-ed was originally published in The Hill Times on October 26, 2020.

Data has been called the oil of the 21st century. And Artificial Intelligence (AI) platforms and tools are commonly described as the new refineries that will convert the data into value-added products, services and platforms.

Globally, it is estimated that, by 2025, there will be over 450 exabytes of digital data generated every day—that’s equivalent to 210 million DVDs. Of course, not all of it will be directly useful for extracting economic value. However, without proper AI platforms that are set-up and trained to examine vasts amounts of data to decipher value from digital data, our businesses will not likely be globally competitive.

While Canada has established a leading-edge AI research and talent ecosystem, we have not yet seen adequate investment levels in AI from the Canadian private sector. It can lead to relatively lower productivity rates for Canada compared to other OECD countries.

The Conference Board of Canada has been examining AI adoption by Canadian companies. As part of the effort, in March 2020, we brought together a group of Canadian business executives from a range of industries to tell us more about why AI adoption has been slow and what’s needed for Canada to take more of a leading role in this space. Here are three themes that emerged:

Understand that AI impacts everyone and should be foundational to corporate strategy

While AI is generally viewed as a highly technical topic and in the domain of data and computer sciences, these perceptions have not caught up with advances in AI-enabled software platforms.

Increasingly, AI applications are being used by people without strong technical backgrounds. For example, Google Maps is used by millions of commuters daily to check their estimated time of arrival—an AI platform powers it. Similarly, human resources professionals use AI-powered resume screening software to help better prequalify potential candidates for specific roles.

As AI becomes more prevalent, it becomes critical that senior executives understand its strengths and weaknesses. After all, AI is only as good as the training data that the AI algorithm learned from provided use cases. Bias in the training data could lead to bias in the results, meaning that the software used in our example above could disproportionately rate candidates of a certain gender, economic status or ethnicity.

 Canadian executives must understand that AI impacts their employees, customers, partners, and all other stakeholders. AI adoption cannot solely be considered an internal information technology (IT) decision.

Systematically de-risk investments in emerging technology

Canadian executives need a better framework to evaluate the potential impacts of AI for their businesses, especially around revenue growth, costs reduction, and operational efficiency improvements.

Right now, many organizations are still seeing AI through a technology-driven lens. As such, we’re treating investments in AI as technology decisions, not strategic business ones. By reframing AI solutions through a business lens, companies can reduce the perceived risk associated with investing in new applications that drive new revenue opportunities and better value for end users.

For investments in AI, Canadian businesses should move from a technology-driven mindset to one that is driven by return on investment (ROI), which will help to align with strategic goals and build the required buy-in to lead in this space.

Treat data as as a critical corporate asset

One of the most significant barriers to operationalizing AI in businesses has been the lack of awareness around the value of corporate data. It can lead to substantial long-term disadvantages for Canadian firms, such as:

  • Lack of clear enterprise-wide data strategy; responsibility for data often falls under IT leadership; with heavy oversight by privacy and cyber teams.
  • Data are used only reactively (e.g. generating reports, creating dashboards, uncovering root causes, etc.) instead of proactively (e.g. new product strategy, customer churn reduction, etc.)
  • Data insights are not being made visible to other parts of the organization

The COVID-19 pandemic has expedited the digitization of the global economy, and digital data are reshaping traditional industries as they are forced to shift business models out of necessity. Canadian business leaders must act swiftly and reorient their approach to AI adoption—from an IT lens to a core business imperative. We, as a country, have laid a strong foundation for global leadership in AI with significant investments in research and talent. Our businesses must now seize the opportunity and lead with AI adoption.