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Can generative AI save Canada’s productivity problem?
Google weighs in with insights for leaders looking to start leveraging the tech, and TELUS shares its own transformation success story
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Generative AI is often touted as a saviour to Canada’s sluggish productivity — even reversing our decades-long decline.
A new report by TD Economics backs this prediction as it highlights the tech could save Canadian employees up to 125 hours a year and boost Canada’s GDP by as much as five to eight per cent over the next decade. Yet, only around nine per cent of Canadian businesses are using gen AI — underscoring the need for more education and awareness.
So, what are some learnings that startup and enterprise leaders can benefit from today rather than years later when it comes to their own gen AI approach?
With Google Cloud having rolled out a slew of new tools and becoming the fastest-growing major cloud to nearly 90 per cent of gen AI unicorns and nearly 60 per cent of the world's 1,000 largest companies, we turned to executives from the tech giant and partner TEUS for their own take.
Critical early steps to start your gen AI journey
With all the excitement around gen AI, it can be tempting to jump right in without zeroing in on a long-term strategy.
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Photo credit: Sam Sebastian
Sam Sebastian, Google Cloud VP and Canada country manager, says the number one step he encourages founders, CEOs, and CIOs to start with is the basics.
“We usually slow them down a little bit and say, ‘Step back, what are the handful of use cases that you think would be extremely valuable for your organization? What are the problems you're trying to solve?’ Then based on those requirements, we can come back to them and say, ‘Here's a series of things we've done with other customers that can show you the power that this tech could bring.’“
Sebastian added number two would be putting together a “tiger team” — a small, cross-functional group of experts — to identify what the scope is, deploy in a test environment, and craft a hypothesis.
“Once we get a good feeling that we're solving a particular issue, we'll slowly but surely figure out how to scale this into production [...],” shared Sebastian. “We might have hundreds of proof of concepts going at once, and then the magic is figuring out what you want to put into production so it can have the biggest benefit for the most amount of folks inside an organization.”
Ongoing support for startups for their cloud and AI journey
For startups looking to speed to market solutions in a cost-effective way, Sebastian highlighted the startup ecosystem remains a critical segment for Google.
“The opportunity that Google Cloud and our Vertex AI and gen AI platform offers a startup are second to none. We're pretty much the only cloud that offers a full vertical integration of a platform [...] as well as our own first-party large language model that gives any customer the opportunity to innovate and build on a market-leading platform across the entire technical stack.”
Sebastian added Google continues to offer a series of cloud service credits for startups and has a team in place to support them on their cloud and AI journey. The company also recently launched an AI essential courses and free gen AI training.
More enterprises tapping Google Cloud to leverage gen AI
While accelerating innovation for startups is part of Google’s DNA, the company is helping more enterprises across sectors take full advantage of gen AI.
Leading enterprises building new gen AI apps on Google Cloud include Deutsche Bank, Estée Lauder, WPP, Mercedes Benz, IHG Hotels & Resorts, Verizon, and hundreds more. Among Google’s expanded enterprise partnerships in Canada includes TELUS, which has undertaken a massive technology transformation to become a digital-first, AI and cloud-enabled, insights-driven organization that’s much more than a traditional telco.
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Photo credit: Jaime Tatis
Jaime Tatis, chief insights officer at TELUS, shared that TELUS had been using AI for more than seven years to improve customer and team member experiences across functions. However, earlier AI deployments were based on Jupyter Notebooks and were not feasible for fully scalable enterprise-grade solutions. They also didn’t have a Google Vertex AI-based MLOps standard or architecture that would allow teams to accelerate the development and simplify operations of AI models at scale.
TELUS recognized that the key to a successful data strategy is to have the right foundations, and without that it’s not only difficult but almost impossible to scale the value of analytics and AI — leading to partnering with Google to modernize its data stack.
“I want to emphasize modernize as we didn’t opt for a simpler and quicker lift-and-shift approach,” added Tatis. “Instead, we radically transformed the way we leverage data, taking the opportunity to clean up our datasets — deprecating more than 30 per cent of the datasets in our legacy platform — and taking advantage of the scalability and edge of technology functions Google Cloud Platform offered.”
Tatis highlighted that TELUS is now incorporating AI and gen AI through Google Cloud in several ways, including:
Using AI insights and voice call analytics in contact centres to capture, transcribe and analyze all customer interactions — allowing TELUS to derive actionable, real-time insights from customer conversations.
Evaluating Google's Gemini Pro to enhance the team's ability to analyze the underlying reasons for support calls — converting raw data into actionable insights.
Using intelligent techniques to completely shut down our networks and minimize energy consumption when they’re not in use — with no impact to customers or performance.
Leveraging ML to create workflows that address provider burnout for knowledge workers such as doctors, pharmacists, and care coordinators.
Collaborating with Google on a data platform for various health authorities to reduce patient data leaks. The tool will also provide employers with timely and accurate reporting on the health and well-being of staff to tailor support.
“We’re seeing a consistent increase in team member adoption of AI across the business,” added Tatis. “The ripple effect of sharing success stories internally is creating a movement and opening new doors for improved solutions in the future.”
Final takeaway
Sebastian reminds startup and enterprise leaders that gen AI offers many paths for new revenue and business lines and great consumer experiences.
“In a current timeframe where we're lagging in productivity, it's an opportunity for Canada to lean in and take advantage of this type of tech to solve our productivity issue,” said Sebastian.
“Canada is among the top countries in the world that lead in research and AI startup activity. So we have a position of strength, but unless the startup world, corporate customers, and public sector take advantage of the tools that are now at their fingertips, I think we're letting a big opportunity slip through our fingers.”
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