AI Trends In 2022: What’s Real And What’s Hype? Hear From The Experts

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The end of the year is a time not just for predictions of top trends but also to watch for the biggest hype and most misleading recommendations that get dished out to business leaders. There’s no scarcity of these in the artificial intelligence (AI) space.

I asked several industry leaders five actionable questions for 2022. Inspired by Tribe of Mentors, the bestselling book by Tim Ferris, I gave the traditional questions a slight twist. (“If you want uncommon clarity and results, ask uncommonly clear questions,” advises Ferris.)

I sent the following questions to data and analytics experts, asking them to respond to up to three of them:

  1. What's a rarely discussed data and analytics trend that will materialize in 2022?
  2. What's the biggest hype in AI that will fizzle out in the new year?
  3. What is one bad recommendation you often hear being given to business leaders?
  4. What's one pandemic-triggered change you will continue in your organization in 2022?
  5. What is one data/analytics book you've gifted the most to non-technology leaders?

This article is organized around these questions. Feel free to skip around to those that interest you the most.

1. What's a rarely discussed data and analytics trend that will materialize in 2022?

A strong digital product sense can be the next big thing. This hyper-personalization will be aided by a dramatic increase in efficient data preparation. Ethics in AI could also get a much-needed boost.


  • Having a strong digital product sense will be the next big thing as more businesses move online. Digital-first business models rely on personalization to improve customer experience and retention. Product scientists who can quantify user experience on digital products, design online experiments, and use machine learning on clickstream data will be in high demand. – Nikhil Sikka, Associate Director, Advanced Analytics and Insights of Wayfair
  • We’ll see the rise of systems for efficiently cleaning and structuring data. Today, armies of individual data scientists at large companies create their own notebooks and manually work on datasets with no shared infrastructure or coordination across teams. We’ll see the rise of tools that will standardize and dramatically accelerate the creation of these data-munging pipelines. – Charles Fisher, CEO of Unlearn.AI
  • Conversations around ethical AI and ethical data analytics will attract more attention from academia and industry. Hopefully, this emphasis will work its way toward policy-makers and politicians. The recent press coverage on whistleblower documents about giant social media companies could help accelerate meaningful change in 2022. – Hadi Hosseini, Assistant Professor at the College of Information Sciences and Technology, Pennsylvania State University

 

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