The third trend that Fjord highlights in its annual trends report for 2018 is ‘Slaves to the Algorithm’, which focuses on the growing role that algorithms play in our lives and our businesses. In particular, Fjord exposes how consumers are increasingly using algorithms to curate their experiences with brands.

Brands have, for the past decade and a half, focused on search as the key discovery mechanism for digital customers, but artificial intelligence (AI)-powered interfaces such as messaging, chatbots, and voice empower people with new ways to explore possibilities. Think about Spotify and how it helps people to discover new music that suits their taste.

Financial services (FS) human resource (HR) functions, too, are leveraging algorithms to optimize their interactions with employees and potential employees. HR is making more extensive use of AI and machine learning to improve its performance—from personalized career path recommendations and training programs for certain employees to offering suggestions to managers on how to mentor, motivate and reward employees based on their personality, mindset and skills.

When it comes to hiring decisions, more and more FS companies are using predictive analytics and algorithms to identify candidates who will be a good cultural fit and who will be high performers. Others are using algorithms to deliver more personalized messaging and offerings in an effort to improve the employee and candidate experiences.

Unilever is one example of an organization that is tapping into machine learning algorithms to streamline HR processes, while improving the results it generates. Candidates can apply for entry-level jobs using their LinkedIn profiles and play a few neuroscience-based games on their mobile phones. If their results reflect the right profile, they can record responses to preset interview questions via video.

Using machine learning, the system analyzes keywords, intonation, and body language to help determine whether to invite them to the Unilever office for a day-at-the-workplace scenario. Algorithms can thus enable FS organizations to scale to efficiently process millions of job applications while improving recruitment outcomes.

Traditional applicant filtering systems often eliminate qualified candidates who use the wrong keywords and phrases in their resumés; today’s advanced AI can use contextual information to make the sort of calls an experienced human recruiter might make. However, organizations also need to be mindful of the risks of poorly implemented or managed algorithms, as well as of a potential backlash if candidates or employees feel that algorithms have too much power over their destinies. For example, a recruitment algorithm can support efforts to improve the diversity of the organization, but not if the code and data reflect systemic or institutional biases.

And when it comes to using algorithms for performance management, organizations will need to ensure employees are not incentivized to game the system.

Another implication of this trend is that employee and candidate expectations and behavior may change as they make more use of algorithm-powered bots and virtual assistants in their everyday lives. There are already several job search and career development skills for Alexa—could we soon see candidates asking Alexa for help in their job hunt?

What’s more, will candidates and employees expect the same access to conversational AI and personalized algorithms from the systems they use in the workplace? As they prepare for the workforce of the future, FS organizations will need to think carefully about how they use algorithms to improve HR performance, as well as how algorithms could become the gatekeepers to the best talent.

My next post is about how people and machines can work together to enhance organizational performance. If you’d like to read the full Fjord report, it’s available right here.

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