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Digital hands make brighter work

Digital hands make brighter work

In the two years since Zoom.ai launched its AI-driven automated assistant, a chat-based application that integrates with enterprise systems like Microsoft Office 365 and Google G Suite, the Toronto startup has tapped into a promising seam of demand. The users are busy professionals who would otherwise have little choice but to hive off growing chunks of their work day to manage the torrent of logistical minutiae once handled by support staff, says founder and CEO Roy Pereira.

The workflow problem isn’t exactly new, but previous software solutions didn’t help and sometimes added another layer of busy-work. Zoom’s solution, which gives every company employee their own “personal assistant,” relies on machine learning algorithms that adapt to the user’s individual requirements. “The singular interface is a powerful benefit,” says Pereira. He claims that Zoom.ai can free up 15 hours a month for a typical user by automating things like scheduling meetings, generating documents and transcribing calls.

Zoom’s application falls within a broader tech niche focused on developing fresh ways to empower different employee cohorts, from large rosters of front-line hourly workers to highly skilled professionals responsible for complex client relationships. What’s clear in this sector, as well, is that firms like Zoom are reaching for evolving technologies—especially machine learning—to design products that confront the shortcomings of earlier solutions.

Employee learning is a case in point. While webinars and online learning modules have become ubiquitous for both on-boarding and continuous training processes, the experience is often unsatisfying, costly and fails to generate meaningful feedback about whether participants have retained the information, says Carol Leaman, founder and CEO of Axonify, a 170-employee firm in Waterloo that has pioneered the concept of a “micro-learning platform.”

The company’s approach has been to break down learning into small, digestible bites with a strong emphasis on personalization and engagement, for example, by gamifying the modules. It also can precisely track the results. “Everything is measured and used to optimize the learning experience to drive memory and behaviour change,” she says.

Axonify’s platform, Leaman notes, is popular in the retail and hospitality sectors, and at firms with thousands of hourly employees in multiple locations, where HR teams must contend with high turnover rates. But she says the company has also signed on pharmaceutical firms with far-flung networks of sales people who must constantly replenish their product knowledge. In both environments, time and limited resources militate against effective training. “The way we train people leads to rapid knowledge retention.”

Nudge.ai is a third company also focused on using emerging technology to strengthen customer relationships—in this case with a platform that relies on a machine learning system to enrich the client information available to professionals such as wealth advisors. Unlike more traditional customer relationship management products, says co-founder and CEO Paul Teshima, Nudge’s “topical modeling” platform is designed to adapt, prompting advisors to constantly adjust their client outreach and automatically populate profiles with new information.

With newer clients, for example, Nudge will recommend frequent interactions, but as existing accounts become more established, the system learns to pull back. Teshima says the platform’s AI algorithms also search for new information relevant to a client’s holdings.

Some clients have also used Nudge’s built-in analytics for internal tasks, such as analyzing otherwise invisible social networks within a company’s sales force to identify “collaboration dynamics,” says Teshima. “We can see the relationship strength between individuals in the company,” he says. “This is something our customers have been asking for.”