• How can we use AI to better match skills to openings?
• How can we use AI to make the entire recruiting and hiring journey better, and improve candidate experience?

Before delving into specifics, consider this: Essentially, if A, then B. Just as AI is changing the game, we have to change how we see it: it’s a tool with multiple benefits at once. In other words: if we are better at sourcing the talent to find those with the right skills to match the right job opening, then the candidate experience will be better.

In this regard, AI is a positive disruption that not only improves how we find candidates, but how they experience the process of being found. All along the recruiting journey it works faster and more efficiently by profound degrees. And at the same time it has a tremendous impact on candidate experience. Let’s look at common pain points to recruiters and candidates and see how AI improves the outcome:

Recruiter Pain Point: Too Many Applications

A common pain point among recruiters is the sheer onslaught of digital applications — whether or not an applicant is actually qualified, with the required skills. We can’t put too fine a point on this: Job seekers spend an average of 49.7 seconds reading a job description, and 14.6 seconds of that is spent on the actual requirements of the job. Then, many just hit send. According to Glassdoor, each corporate job offer attracts 250 resumes on average. Of those, four to six are called for an interview — and one gets the job. Getting from 250 resumes and 4 to 6 callbacks per job is a whole lot of sorting.

AI Solution: Finding Soft Skills

AI can use pattern matching to connect the dots between job requirements and the skills and training listed on a resume. Machine learning means that AI can also get better at this the more it works, from building a bank of alternate phrases and variations it recognizes to tailoring its rankings to factor in other criteria. And AI can find soft skills just as quickly as hard skills. For instance, consider Leoforce: this new AI recruiting platform learns who the ideal candidate is through a combination of machine learning, big data and behavioral pattern recognition.

AI Solution: Assessing Fit

AI can also take an extremely educated and predictive guess about how a candidate may do in the long term, addressing concerns about ROI without bias. AI can use past hiring and employee records and patterns to get a clearer picture of the relative success and fit of a hire — and can identify potential blind spots of training gaps, enabling companies to put the services in place that support a better outcome.

Candidate Pain Point: an Overlong Application Process

Let’s face it: the digital environment has changed many job applicants’ perception of time. To a candidate in this digital environment, hours feel like days and days like weeks. Time, particularly for digital native generations, has shrunk — and the etiquette of responding to a message has radically changed. This is just one point of friction out of many in terms of how a candidate experiences the application process today. A delay in getting notified can feel like a rejection even if it’s not.

But while recruiters famously spend an average of 6 seconds reading a resume, finding the right hire for one job may take more than 20 hours. (And rare indeed is the recruiter tasked with filling one job at a time.) The wait — particularly if a candidate has been contacted by an organization’s hiring team — can feel like a hurry up and wait hustle, and may sour a candidate experience. Whether the result is a turn towards a different employer, or simply an element of disengagement in the process, it can stop a recruiter-candidate relationship before it starts. But recruiters simply don’t have the time or, most often, the person power to contact every applicant every step of the way.

AI Solution: Recruiters Don’t Do the Heavy Lifting

Allocating the heavy data sorting to AI frees more time for reading the resumes that actually matter. It means that unqualified candidates can be notified faster, and qualified candidates are really qualified — and the recruiter has had more time to spend getting to know them on paper before an interview. But additionally, AI can work as the messenger. For example, when a promising candidate is found with the qualifications and skills that match, Leoforce can reach out with a personalized message. If a candidate is interested, the connection has already been made — and a recruiter can take it from there. Instead of radio silence, there’s AI at work for you.

The myth that AI-powered recruiting is impersonal and inaccurate is just that: a misassumption about the power of AI. With the ability to greatly increase searches to radically cut down on searching time, as well as a way to reach out and develop a talent pipeline, AI enables recruiters to get back to what they know how to do best: spend time getting to know promising candidates, and find the best fit for each job. And for candidates, AI enables frequent contact and a faster process that improves their experience — and may just affect their decision to join your organization.

This post was published first on TalentCulture.

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There’s no reason for any organization to shy away from AI’s capability — whether a big Silicon Valley firm or a small and lean startup. And leveling the playing field and reaching the same candidates as a larger organization, let alone a direct competitor, is just a matter of knowing how to use AI.

So, we decided to break down AI into five best practices along the hiring journey. We’re using a hypothetical hiring team we’re calling Talent Inc. to look at the five critical phases of talent acquisition, and how Talent Inc. draws on AI for tremendous advantages that result in better hires. This is an approach any hiring team can take:

Finding Talent

Our ambitious recruiting team at Talent Inc. has been tasked with sourcing 250 new hires for a growing company. These are positions from entry-level to senior management, covering a whole range of functions. Talent Inc.’s objective is to stretch their reach as far as possible to find the largest pool of talent they can.

Their last AI-powered hiring campaign for this company was highly successful — and they still have all the data on the search patterns and strategies that found the best hires. This time, the team draws on that data to source a larger pool of similar candidates for the company’s new locations. They create a wireless “geofence” around specific locations.

Automatically, the sourcing program gathers hordes of resumes of geographically segmented and promising candidates. Meanwhile, the team looks at the existing data on previous candidates and hires to see where there might be interest in relocating or moving up the ranks.

Making Connections

Since AI tools have done the heavy lifting for them, the team at Talent Inc. is ready to start sorting through the resumes of qualified candidates and reach out. They tailor their approaches to what they already know about these candidates — collected via AI — to make these vital first connections, using hiring events, social and mobile messages, and personalized emails. They begin to put together prospective talent pools for each level of hire, and start digging into resumes to see if they’re coming up short or sourcing sufficiently. They automatically set up and maintain an ATS. Since the whole team is working on the same platform with access to the same information, they can quickly set up automated tasks for AI to complete that will help them pinpoint ideal candidates for each position, and they can start reaching out to candidates who stand out.

Tending to the Talent

Even before they start screening for skills, competencies and experience, there are already conversations going on between prospective candidates and the hiring team. It’s not the hiring people doing the talking: there’s no phone tag or cumbersome emails. Instead, the candidates are engaging with a sophisticated virtual assistant. Candidates who show interest can do a pre-screening quickly with a chatbot, asking questions and getting a clearer picture on the position. Each conversation offers dynamic, responsive messaging and produces data on the candidate that the virtual assistant can share with the team at Talent Inc.

In the time it might take to reach out and have one initial conversation with one candidate, countless exchanges have already taken place and candidates are already engaged in the application process. There’s now a whole pool of candidates entering the talent pipeline, already having a positive experience and interested in finding out what comes next. Many of these candidates are digital natives, well used to interacting with chatbots and at ease with the process — and to them, the process implies that the employer is appealingly forward-thinking in its approach to business and people. Now candidates can start having real-time conversations with the recruiting team, who already know a great deal about each candidate before they talk — and can tailor their conversations based on what they know.

Making Sure the Fit Is Just Right

With 250 positions to fill, there’s little time to spend on potentially poor hires. But AI has already created predictive analytics on who may make the grade and be a great fit. A whole array of criteria has been used to create screenings and pinpoint promising matches, and the HR team can rely on the data to help narrow down the best candidates for each position — and find candidates that might be better fits for other positions they may not have applied for.

In each case, the hiring team can take time to get to know each candidate, whether in conversation or formal interviews, as the human recruiters are freed up from repetitive and tedious administrative tasks now being executed by the AI software. While the average recruiter only spends six seconds on a candidate’s resume, the team at Talent Inc. gets to know all the great candidates they can — and based on the data already gathered, there’s lots to talk about

Keeping the Hiring Process Going

Providing an outstanding candidate experience that really conveys the potential employer’s brand is a one of Talent Inc.’s core values. All the portals and dashboards prospective hires are using during this process are layered with the look, feel, mission and message of the employer. Interviews are being set up with the top-tier prospects within the company, but the employer and the hiring team have partnered on a new initiative of different interviewing tools.

A recent study on LinkedIn found that key hiring trends for 2018 include different kinds of interviews and conversations, adding more of a human side to the classic mano-a-mano. That may include online skills assessments — which may be built around the data AI has gathered already on candidates. There are VR options for “trying out” the position in the virtual workplace, job “auditions,” video interviews, and far more casual interviews that set both interviewer and candidate at ease and allow for more meaningful and spontaneous conversations. The data intelligence has enabled recruiters to use their emotional intelligence. Soon Talent Inc. has recommended a pool of terrific candidates for the expanding firm, is monitoring and facilitating the application process, and has also maintained connections with those who may not apply this round, but may in the future.

“21st-century HR isn’t about playing it safe,” noted IBM’s David Green in a recent article by Leoforce on the role of AI in HR. AI has enabled our hypothetical recruiters at Talent Inc. to keep their employer ahead of the competition — sourcing the best talent in an extremely short window of time using the power of data and AI, and the freedom these tools give them to provide a terrific candidate experience that reflects the employer and sets up hires for engagement and success.

Every interaction has added to the data gathered on each candidate, and improved the recruiter’s understanding of the relative strength and fit of that candidate with regards to the company. AI has predicted outcomes and suggested plans based on previous successes to drive better hires and forecast future hiring needs. AI has also kept a close watch on any skills gaps or problematic screenings, reducing risk and paying attention to ROI, while recruiters are spending more time with each candidate, establishing a connection and a relationship. The result is a whole crop of promising new hires who can help the organization continue its growth.

And based on the data gleaned during this hiring phase and over the course of onboarding, development, and indeed the employee journey, AI can improve the next hiring push even more. If I could pat the team at Talent Inc. on the virtual back, I would.

This post was published first on TalentCulture.

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AI conducts its own version of futurecasting. It’s a fast and efficient supporting player that can scale up our efforts and free us the bandwidth so we can focus on the one-to-one. Fact is, AI is rapidly disrupting recruiting in a good way. But ask someone what it means and you may get a head-scratch. For anyone who’s been looking for a simple basic explanation of what and how AI recruiting works, here it is. One caveat: let’s not call this “AI for Dummies.” No one here is a dummy, and no matter how sophisticated AI is, talent acquisition needs your acumen, intelligence, and expertise.

Here’s a breakdown of five ways AI is taking recruiting to the next level, and knowing how to leverage what it’s capable of — that’s the ace up our sleeves.

Machine Learning

Machine learning is sometimes defined as the ability to “act without having to be programmed,” but what that means is that AI can comprehend, reason, and learn from every data point, interaction, and outcome. AI puts incredible muscle and speed into analyzing vast amounts of data and arriving at very specific, data-driven observations and predictions.

One way it works: It can find out if a certain hire might be a good fit or whether an employer is going to suffer from a skills gap. It can look at how we’ve been recruiting and find the weak points to make predictions and recommendations. And it can refine its own processes, looking at prior successes and failures to amplify or reframe its own approach.

Big Data

The cloud has essentially blown open the universe as far as the capacity for data. We’re now measuring data in terms of hundreds of zettabytes, being processed and archived and reprocessed and parsed at incredible speed. What we have to work with now was inconceivable even a year ago, let alone a decade, and its revolutionized talent sourcing. It’s not just about static information: this is data that can be accessed and analyzed from countless angles — with statistical models, predictive algorithms, innovative filters, with actionable results.

One way it works: Instead of a recruiter having to devote long hours to manually search through 200 contacts on a spreadsheet, AI creates a recruiting nerve center that can search and analyze massive volumes of applicants.

Pattern Recognition

Old-school recruiting, particularly for rapidly expanding organizations, could feel like searching for a needle in a haystack and like reinventing the same wheel over and over. AI can identify and learn from a recruiter’s most successful patterns — and then replicate them, adjusting for all manner of contexts or requirements. It can also find instances of bias and create ways to overcome them.

One way it works: we can take a job description, and use hiring successes from the past to find the most likely qualified candidates — wherever they are, from a database to a job board to social media. We can identify the likelihood of a hire being a success, identity the potential skills gaps or blind spots of weak points, clarify our best sources, and above all, retain the information. It becomes part an organization’s proprietary wisdom, building up a strong foundation for recruiting successes to come.

Messaging

There’s message — the DNA and brand culture an organization conveys, and then there’s messaging — which is, often, the way that DNA and culture are carried out into the talent market. What AI does is facilitate fast, effective, and dynamic messaging. It begins to build relationships with the right candidates as soon as they’re identified, engaging and even pre-screening them before they have their first real contact or interaction with a recruiter. But it’s not an alienating or generic form of messaging. It’s multilayered, highly attuned and customized to the individual organization and the individual candidate — based on the information already learned and collected, and integrated with an ATS.

One way it works: Chatbots are no longer an alien life-form online: they’re a part of our entire system of communication, commerce, fact finding, an accepted form of exchanging information. AI can provide meaningful, relevant answers to candidate’s questions, and then share this with the recruiter. It makes it possible to spark engagement, maintain and build a connection, and then pass the best candidates to the recruiter to get them started on the actual process of hiring. All without cumbersome emails threads, phone tag, or awkward texts.

Pipelining

AI packs a powerful punch: it can process massive amounts of recruiting, hiring, engagement, performance and behavioral data from millions of prospects. It can focus and search for skills, behavioral and even cultural matches. But even more than that, it empowers recruiters with the single most important resource to stay on target: a viable, dynamic, visible talent pipeline.

Frankly, it’s a game-changer: AI is a game-changing innovation that brings the best of HR to organizations no matter their size, location, or field. In this highly competitive talent market, it gives recruiters a vital resource. It enables recruiters to move candidates into the pipeline and keep track of them automatically, an effective way to maintain visibility across the broadest possible spectrum of talent that enables recruiters to act when they see a potential great fit. It’s also another way to overcome unconscious bias and increase diversity and inclusion.

What AI does is enhance the recruiting across the whole journey. It provides recruiters with a far broader and more accurately gathered pool of candidates, the tools to engage candidates sooner and more effectively, and the means to tend to a pipeline that can be searched and refined according to scaling or changing needs. It’s not really an option, either — as AI becomes part of how organizations function now, it’s changing the very Future of Work — even before we bring the talent to the door.

This post was published first on TalentCulture.

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