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Five ways AI will make your job easier

Rather than fret about AI stealing our jobs, here are some ways artificial intelligence and machine learning initiatives might improve your job.

Five ways AI will make your job easier
[Photo: Alex Knight/Unsplash]

We’re in the middle of a sea change in the workplace.

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Companies are currently spending big on artificial intelligence and machine learning initiatives to the tune of $12 billion, but estimates put that figure as high as $57.6 billion by 2021, according to the International Data Corporation (IDC).

With such massive shifts, the focus is usually on what we might lose, but it shouldn’t be. A recent report on the future of work from the McKinsey Global Institute suggests that while only about 5% of jobs can be completely eliminated by automation, the rise of AI requires workers to beef up both technical and soft skills in order to stay competitive.

What’s seldom discussed is how AI can revolutionize our jobs. It’s now possible to pinpoint peak productivity for a single day, improve communication in meetings (even before people ever work together face to face), or even teach you to be a better leader, all thanks to AI platforms.

1. We’ll get better and faster at finding jobs (and hiring)

AI has the greatest potential to change the way companies find candidates, according to Alexander Rinke, cofounder and CEO of Celonis. The company’s process-mining technology helps businesses to understand the areas where automation can help humans, he says. In HR departments, Celonis can help identify how fast workers come and go, the cost per hire, and which positions take the longest to fill. AI helped enable one customer’s ability to identify bottlenecks in recruitment and reduced process costs internally by 30% as well as get them hired more quickly, he says.

Crafting a resume has never been easier, nor has landing an interview. Another example is how recruitment software provider iCIMS, in partnership with Google, is helping job seekers find jobs directly through the search engine, thanks to Google’s AI and machine learning capabilities.

Susan Vitale, iCIMS’s chief marketing officer says that in addition to reducing the number of expired job postings, machine learning is underlying a private beta program of Google’s Cloud Jobs Discovery model. “For a candidate searching for, say, a CTO role, Cloud Job Discovery will serve up CTO positions as well as jobs with titles that are similar, but not verbatim, such as chief technology officer or chief technical officer,” says Vitale. This model also allows for conceptual search results, such as serving up job listings for cashiers, sales associates, and store associates when someone searches for one versus just only showing jobs that exactly match the keyword search criteria, she adds.

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2. We’ll be much more productive

John Furneaux, CEO and cofounder of Hive, says predictive analytics will help us better understand how we work. “It can tell us just about everything we want to know about teams and collaboration, for example, if men or women get more done in the afternoon, and if summer Fridays are a myth,” he says. (Everyone thinks summer Fridays aren’t productive, but in reality there’s no difference between those and other Fridays during the year–productivity is equally low.)

Using a data set of over 30,000 completed actions across Hive workspaces, Furneaux says they were able to identify some notable trends in productivity. For example, men were far more productive early in the day, with a sharp decline in the afternoon, while women had a slower start to the day but were far more productive in later hours than their male counterparts. And analyzing chat messages revealed that women appear to complete more tasks when chatting, suggesting they use communication as a key tool to completing work.

Similarly, Nintex Hawkeye analyzes data on business processes by types, users, roles, and departments to see who’s doing the work and how long it takes them to do it. Management can monitor and analyze those metrics in real time.

3. We’ll eliminate wage gaps

Tanya Jansen, cofounder of the compensation management platform beqom, says that AI and predictive analytics can eliminate unconscious bias from compensation. Jansen says that AI based on a variety of rules including education, experience, certifications, and more can make compensation more fair and help businesses move closer to closing pay gaps. “Specifically, AI can help solve gender pay gaps and the CEO-to-worker pay gap, in which pay ratios of Fortune 500 companies range from 2:1 at the low end to nearly 5000:1 at the high end,” she says. Additionally, the use of AI-driven compensation technology to make pay more fair can mitigate the risk of employee turnover, which costs businesses as much as 33% of a worker’s annual salary to replace them.

4. We’ll have better meetings

Augmented Reality (AR) is still in its infancy, but AI and machine learning are the core components that make it work. As such, Christa Manning, the vice president and solution provider research leader at Bersin, Deloitte Consulting LLP, says that AR can help workers find the right information, in the right place, at the right time to make the best decisions wherever they may be working.

For example, Manning says, as more companies adopt video meetings and collaborative workspaces, it’s likely we’ll begin to see HR-curated information like talent profiles and work styles layered over interactions through AR.

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“Imagine being in a video conference with a colleague and having direct insight into their communication style, seeing tips on how to best interact with them or reminders of what needs to be discussed,” she explains.

5. We’ll be better leaders

Indiggo, a platform powered by a proprietary AI tool called indi,” functions as a brain that has consumed all the knowledge the company has gathered in its 15 years of operation. It also uses an algorithm to provide an estimate of how much time is wasted by a company by analyzing the size of its management team. Then it taps their calendars to see how they spend their time, and walks individual managers through a type of Q&A to make sure they are clear on what their top three priorities are, and how that relates to the organization’s priorities, which will indicate if that strategy is moving forward or not.

“The counterintuitive impact of these advances is that they actually make human work truly irreplaceable,” Alexander Rinke, the cofounder and CEO of Celonis says. As such, he reminds us, “Humans are much better at processes that involve reasoning, judgment, and interaction with people.”

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About the author

Lydia Dishman is a reporter writing about the intersection of tech, leadership, and innovation. She is a regular contributor to Fast Company and has written for CBS Moneywatch, Fortune, The Guardian, Popular Science, and the New York Times, among others.

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