As the Information Age becomes the Age of AI, it leaves many of us futurecasting what’s in store, particularly in recruiting and hiring.

Depending on whom you ask, you’ll receive different opinions on what AI is and what it isn’t. According to the White House’s Preparing for the Future of Artificial Intelligence report,

“There is no single definition of AI that is universally accepted by practitioners. Some define AI loosely as a computerized system that exhibits behavior that is commonly thought of as requiring intelligence. Others define AI as a system capable of rationally solving complex problems or taking appropriate actions to achieve its goals in whatever real-world circumstances it encounters.”

How AI Works

While there are competing definitions of AI floating around, one thing we can all agree on is that AI is not just glorified automation. To best understand how AI works, you first need to know that experts divide AI into two main categories: “weak AI” and “strong AI.”

Weaker forms of AI are present in our everyday lives. The big data algorithms used in financial market analysis and even on your Facebook feed to prioritize content are examples of what AI can do at the most basic levels.

But there are also companies working tirelessly on stronger examples of AI, and none have gone as far as IBM has with Watson. Although Watson is particularly impressive, it is not yet considered a fully strong AI. A true strong AI is one that has attained self-awareness and consciousness – the highest levels of intelligence.

Given how large the AI spectrum is – from Facebook algorithm to world-dominating robots – categorizing AI can be quite difficult. The one common denominator, however, is that all AIs learn from doing tasks – they don’t just automate activities based on rigid rules set by a user.

The goal of those working in strong AI is to develop artificial intelligence that is functionally equivalent to a human’s. However, some of the simplest human tasks can be the most complicated for AI to tackle. Small things like reading body language and identifying sarcasm make humans the smartest machines of all, and we’re just not there yet with AI.

chairsArtificial Intelligence Comes to Recruiting

The hiring process is cumbersome, and many recruiters feel overwhelmed by the overabundance of applications and resumes – not to mention the time and energy they have to invest in communicating with, sourcing, screening, and engaging candidates. For this reason, recruiters often look for ways to speed up the process by investing in tools to automate their repetitive tasks. Sending out follow-up emails and scheduling interviews are two such tasks that can be automated – but just because something is being done faster doesn’t mean it’s being done right.

That’s why many recruiting solutions are entering the market with AI capabilities. Some of these tools have the ability to conduct ongoing conversations with candidates to assess their personality traits, gauge their engagement and interest, and determine if they’re qualified. These tools also communicate to the recruiter which candidates are the most qualified, which helps remove bias from the process, improve time-to-fill rates, and reduce the recruiter’s workload so they can focus on their highest priorities. Other AI recruitment tools are able to score and rank candidates based on information submitted by the candidates.

Some solutions, like Karen, combine both the conversational and the scoring functions of existing recruiting AIs in one tool. Powered by IBM’s Watson, Karen is a good example of what might be in store for the future of AI in recruiting.

A version of this article originally appeared on Money Inc.

Noel Webb is cofounder and CEO of, a “cognitive recruiting assistant.”

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