Interview by Renato Cudicio, MBA, President of TechNuCom.
Three interviews – three Quebec perspectives on AI
In mid-November, members of the Gung Ho! business club held a panel discussion in Laval, moderated by Renato Cudicio, to discuss the irruption of AI in organizations.
A Boston Consulting Group study revealed last year that 30% to 40% of Canadian companies were experimenting with AI or had initiatives to integrate it. Another Gartner study indicates that 25-30% of employees are using AI without their superiors being aware of it. The penetration rate of AI is therefore much higher than we think.
Three experts were invited to discuss this hot topic with some 60 business owners and managers.
Renato Cudicio: First of all, can you tell us about the Quebec Innovation Council and its role?
Anne Nguyen : The Quebec Innovation Council was created three years ago to advise government and business on innovation. We help stimulate innovation in a sustainable way, whether it’s soft or disruptive, as is the case with AI. Our goal is to federate Quebec’s innovation ecosystem to foster the adoption, development and responsible use of AI.
A year and a half ago, we structured our mission around two axes:
- Social innovation: How can we innovate to improve the well-being of society and communities?
- Artificial intelligence: A technological lever for economic, social and environmental development. Our aim is to promote AI and maximize its positive impact on society.
Is AI profitable for companies? Can we measure the return on investment?
Quebec ranks 7th worldwide in AI innovation, and Canada 5th. We can be proud to compare ourselves with other leading nations in this field. The profitability of AI rests on three pillars:
- Adapted infrastructures: These are essential for the development of AI.
- Research and innovation: The culture of technological innovation is as important as research in the humanities and social sciences. The two go hand in hand.
- Marketing rules: These must encourage innovation while protecting users.
Concrete examples show the gains that can be made with AI. A 400-page document can be transformed into an AI-generated podcast to save time or make it more accessible. Another example: a robot equipped with advanced AI was able to identify edible objects on a table and put away dishes by analyzing the surrounding design. This is proof that AI can be a powerful tool, but you need to start with small projects adapted to your business field to reap concrete benefits.
AI can do everything today, but where do we start? Is there a priority sector for its adoption?
Automating repetitive tasks is a good place to start. This frees employees from low-value-added tasks so they can concentrate on more rewarding activities.
It’s crucial to take small, pragmatic steps. We no longer have the luxury of ignoring AI. We need to embrace and adapt to it, while developing the digital skills to stay competitive in the 21st century.
What are the main failures in AI adoption, and how can they be avoided?
Failures are often linked to poor identification of AI use cases. To succeed, you need:
- Sound AI strategies, based on a clear understanding of the data needed (quantity and quality).
- Experts capable of navigating the technology cycle.
For example, one hospital with 150 information systems had the same data recorded 18 times, with a high error rate. This highlights the need for good data governance.
A common mistake is to treat AI as a human being, rather than as a tool. We also need to know where to look for experts. It’s essential to knock on the right doors to get the right skills, whether it’s deep AI or service-oriented AI.
In short, to avoid failure, you need to:
- Have a clear AI adoption strategy.
- Understand data and technology cycles.
- Set up rigorous governance to evaluate results.