The evidence that analytics play a central role in successful adoption of artificial intelligence (AI) strategies couldn’t be starker—especially in Canada.
A recent study of AI maturity conducted by Forbes Insights, the strategic research and thought leadership practice of Forbes Media, revealed that among leaders in AI adoption—defined as survey respondents who described their AI initiatives as “successful” or “very successful”—79 per cent worldwide said analytics played a critical role in their AI strategies, compared to 14 per cent who did not. Among Canadian firms, the divide was even wider; while half of successful AI initiatives had a strong analytics component, only three per cent of unsuccessful programs were analytics-focused.
The study, AI Momentum, Maturity and Models for Success, was commissioned this summer by SAS Institute Inc., in partnership with professional services company Accenture Inc. and computing infrastructure company Intel Corp. The survey of 305 business leaders in the Americas, Europe and Australasia defined AI as the science of training systems to emulate human tasks through learning and automation.
In general, Canadian organizations are more critical of their AI success than the worldwide average, with only 31 per cent claiming tangible benefits, compared to 51 per cent worldwide. That could be partly because of our inherently cautious approach to technology adoption: Only 30 per cent of Canadian organizations surveyed had fully deployed one or more AI use cases, compared to 46 per cent globally. Those who did cited organizational productivity (59 per cent), improved forecasting and decision-making (56 per cent) and better customer acquisition (46 per cent) as the prime benefits.
Analytics clearly offers improved economic results from AI programs, but there are other areas where Canadian firms can wring more benefits out of AI. An important one is in the domain of ethical application of AI.
Not that Canadian organizations don’t recognize the ethical issues of AI use, and their possible impact on customer engagement. As in the rest of the world, about 60 per cent of Canadian firms are concerned that AI outputs could alienate customers—that trust could be eroded. And like the rest of the world, the vast majority (91 per cent) of Canadian AI leaders have ethics training for their technologists.
But Canadian companies aren’t as assiduous about following up on those concerns. Only 55 per cent of Canadian AI leaders review or evaluate AI outputs weekly, compared to a 74 per cent worldwide average. And only 30 per cent had a process in place for overriding or augmenting AI results that were questionable, compared to 43 per cent worldwide, and 62 per cent in the U.S. Do Canadian companies trust AI more? Or do they simply have more work to do to ensure proper oversight?
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Not only are customer perceptions significant to the maturing of AI. Perceptions within organizations using AI also have a measurable impact on the development of the discipline, and the survey highlights interesting figures in that regard that warrant further exploration.
Perhaps surprisingly, those outside the corner offices are more likely to view AI initiatives as successful or very successful than are executives. Among non-C-level executives, 55 per cent perceived their organizations’ AI efforts as successful, while those in the C-suite—chief technology officers, chief information officers and chief analytics officers among those surveyed—were less likely to say implementations met their goals (38 per cent).
In terms of the affect of AI on the workforce, Canadian organizations showed an interesting divergence from worldwide patterns. Canadian operations were bang on the worldwide average (64 per cent) in believing that AI efforts elevated the work of employees, allowing them to focus more on strategic tasks than operational ones. And they were slightly less likely than the worldwide average to be worried about the impact of AI on employee relations—workers feeling threatened or overburdened (51 per cent in Canada to a worldwide average of 57 per cent).
But nearly twice as many Canadian organizations (39 per cent) consider resistance from employees over job security concerns as a challenge to their AI programs compared to the worldwide average of 20 per cent.
Taken as a whole, the survey should provide some food for thought among Canadian companies with respect to achieving better business outcomes from their AI initiatives. Some questions to consider:
- Canadian organizations are less likely to describe their AI initiatives as successful. To what extent is that a flaw in execution, or a reflection of our typically conservative approach to the adoption of new technologies?
- Even among AI leaders in Canada, we’re less likely to have a strong analytics focus in our AI implementations than in the rest of the world. How much higher would that success rate be—and how much more economic value could we wring out of our AI efforts—if analytics were to play a more central role in AI strategies?
- Where is the disconnect between our acknowledgement of the risks of faulty AI outputs and our efforts to monitor and remediate those problems? How can transparency of algorithms and processes paired with apparent human oversight improve customer engagement?
- Why are Canadian organizations significantly more likely to see employee pushback as a challenge to implementing AI? What can companies do to alleviate the suspicious perception of AI’s impact on job security?
About the Author
As the Strategy lead at SAS Canada Steve Holder is responsible for creating and driving the SAS solution strategy with our Canadian customers. A key part of this is providing thought leadership for the SAS Analytics, Big Data and Cloud portfolios including Open Source integration. A Canadian analytics evangelist Steve has seen first-hand how the use of analytics and data can help customers solve business problems; make the best decisions possible and unearth new opportunities. Steve’s passion is making technology make sense for everyone regardless of their technical skillset. Steve tweets at @holdersmTO and can be emailed at email@example.com.