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Why You Need To Start Training Your Recruiting Teams for AI-Related Hiring

AI is here to stay. You are going to need to hire AI talent no matter what your industry is — and now is the time to start preparing your organization to do that effectively and efficiently. It’s just not going to happen on its own.

Once upon a time in recent history, businesses made the switch to PCs, email, networks, the Web — and experts in information technology became vital for any company. Now we’re racing headlong into another evolution as AI transforms business applications. We’re going to need people who are experts in AI. It’s that simple.

Even if you don’t know you’re going to be hiring AI architects, AI product managers, software engineers and AI ethicists, assume that you will. We all know that innovations don’t wait. They just happen, and it’s up to us to be there.

It’s best to accept that AI will be a part of how your business functions, if it’s not already, and start planning your investment in AI-skilled hires now. You don’t want to wind up with a substantial hole in your roster or your operations due to all the talent being snapped up. Here are three steps to take now to start preparing for the robot revolution.

Start Training and Building Infrastructure Around AI

AI, machine learning and big data are all transformative tools, which means your recruiting team needs specialized training in how to effectively hire for positions related to these technologies.

Or, take it a step further and consider AI-dedicated recruiting teams. We’re already grappling with recruiting, hiring and retention. Most HR teams are still mired in day-to-day tasks that should not still be on their plates — not when there are countless new platforms and service providers who can take over.

A team that’s dedicated to recruiting for AI roles is going to have to be very fast and very efficient. It will also need to be extremely focused in terms of pinpointing the hard skills and training for a specific AI job position — and also very smart about identifying and discerning the right soft skills. It will need to make sure the outward-facing materials are truly aligned with the organization and free of bias.

One way to accomplish this is to redesign the recruiting team so they’re not all looking for talent, but are instead more task-oriented, so the focus is divided among people and hopefully speaks to their strengths. Here are a few possible recruiting functions that could pop up in the very near future.

A Q&A czar — This person or team is the landing point for questions the chatbot sends to a human (please have a human on hand to answer questions as well as chatbots).

Initial pre-screening — This function works with cognitive assessment and screening tools to identify the best potential candidates in terms of both hard skills and soft skills

Skills specialist — Once the first tier of potential candidates is identified, this function takes a much closer look at the technical and functional hard skills, then assesses key soft skills such as problem solving and situational challenges that match each candidate better with the requirements of specific jobs.

The decision team — This team combines all the information and feedback on each candidate and takes it to the next level in terms of a hire. They’re also the team that interfaces with the hiring organization.

Let the Chatbots Help with Recruiting

As we head toward filling AI roles, here’s an irony: Our concerns about machine learning and AI may hurt ourselves even more in the next few years. Tighten up your recruiting and hiring processes with automation, self-service, and other future-facing tools. Let the chatbots help. It will free your team to ramp up on how to find the best AI talent — how to screen for training, skill sets and experience.

We need to be better and smarter about how we recruit, hire and manage our hard-won talent. Many of us are looking at the solutions presented by machine learning and AI. It’s not that I want you to lift the needle off that record. But no one wants to be caught off guard, waltzing to the possibilities of sentiment analysis and virtual teams, while your competitors are searching for tech talent to fill their brand-new AI-related jobs.

We need to make sure we’re still in control of the hiring process, but that doesn’t mean rejecting innovative technologies because we feel like they’re too opaque. Automation and self-service are vital for today’s candidates — this is how they interact with all the other aspects of their life, and it has to be part of the candidate experience just as it’s part of the consumer experience.

They also provide a far better and clearer picture of how candidates are responding, and how they’re behaving during the recruiting and hiring process — vital information that helps HR departments learn and improve.

Get Outside Help If Necessary

If you can’t train up your team, bring in reinforcements. You need specialized experts on board who know the difference between Hadoop and PySpark — just a for instance. You also need to know where to find AI talent, how to attract them, how to get them to say yes, and then, how to keep them.

Consultants are one way to do it because hiring for AI roles is not in everyone’s wheelhouse and requires very specialized awareness of training, tech and tasks. Bringing in outside services are another: use the tools developed and administered by organizations that are highly advanced in background screening, in self-service platforms, in video interviewing channels, in tools that can be integrated with your existing hiring software.

Companies that are smaller and not entrenched in AI are not necessarily going to want to do this alone. They’re also not going to have the resources to commit to automation or self-service tools. But those tools are vital, and your organization is going to have to integrate them one way or another in the coming years.

#WorkTrends: How AI Will Change HR

We have big news this week in the #WorkTrends community. We’re re-launching the podcast, and we’re welcoming back an old friend, Kevin W. Grossman, as my #WorkTrends co-host. We’re also changing up our format. Each episode of #WorkTrends will now include a quick look at what’s happening in the world of HR tech, plus interviews with people who are doing interesting work in HR and leadership.

On this week’s episode we’re talking everything AI — what it really means, what HR leaders need to know and how it’s going to reshape the way we work. For a look at where artificial intelligence and automation are already taking HR, we’re turning to my friend and expert Ben Eubanks, an analyst at Lighthouse Research as well as a podcaster, blogger and author of a forthcoming book on artificial intelligence in HR.

Listen to the full conversation or read the recap below. Subscribe so you never miss an episode.

AI for Recruiting

Over the past several years AI has transcended its status as a cultural buzzword and found its way into practical applications for many HR leaders. Eubanks says the most prominent AI use case in HR is probably on the recruiting side, because of the sheer size of the problem that talent acquisition presents for large organizations. Chatbots are already enabling companies to take on some conversations with candidates without having to have a recruiter physically sitting in front of them.

“The more volume there is, the easier it is to try to automate that and more value there is,” he says. “When I was interviewing someone for the book, we were talking about what things you should prioritize, and they said if it’s got a high volume and there’s a high cost of making an error, those are the things you really want to automate.”

Improving the Candidate Experience

Eubanks says his discussions with HR leaders indicate the initial reaction by candidates to these types of automations in recruiting has been surprisingly positive. Candidates seem to be appreciative of any chance to break through the often-opaque job-search process and have a chance to have their voices heard — even if it’s by a piece of software.

He says one manager told him candidates often go through a dialogue with a bot about their desired positions, submit their resume, then say “thank you” before signing off. “Candidates love it, because they have a chance to really feel like someone is listening to them,” he says.

Sentiment Analysis

Beyond recruitment, Eubanks says there are already a handful of companies successfully leveraging intelligent automation to perform sentiment analysis to suss out valuable trends in large employee surveys — a process that would take humans hours upon hours.

“What if we had a tool, a piece of technology, that would automatically go through that, not just look at what the issues are, what the trends are, but also look at the sentiment, the underlying emotions and moods of the employees?” he says. “You find out, ‘wait a minute, all the people in this function over here are actually kind of upset’ — or ‘people that are working in this office, this location, are actually having some issues with infrastructure or management or communication.’ ”

Resources Mentioned in This Episode

Let’s continue the conversation. Join us on Twitter (#WorkTrends) for our weekly chat on Wednesdays at 1:30 p.m. Eastern, 10:30 a.m. Pacific, or anywhere in the world you are joining from to discuss this topic and more.

How AI Makes Hiring More Accurate and More Personal

AI is projected to catapult from a $643.7 million market today to $36.8 billion by 2025. Bersin by Deloitte calls it one of the ten major trends changing everything about how we build and manage the world of work. It’s becoming an incredibly powerful tool for recruiting, though not always understood. There are two questions I often hear:

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 Arya: 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, Arya 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 is sponsored by Leoforce.

5 Ways AI Makes Hiring Easier

It’s one thing to see AI coming our way in HR. It’s another thing to know the best ways to harness it to improve sourcing and hiring success. AI isn’t just on the horizon — it’s part of some very forward-thinking recruiting and hiring programs already. Given how tight the job market is, AI is a way to give organizations a tangible edge on the competition. It facilitates a far more accurate way to see a far greater range and depth of talent — which means it’s easier to find better candidates — and more of them. And AI enables hiring teams to make and maintain radically better connections with talent, garner a far better sense of fit over a whole spectrum of criteria and frankly, be more human than we’ve been in a long time.

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 Arya 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 is sponsored by Leoforce.

How to Leverage AI Recruiting to Make Better Hires

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HR and recruiters don’t tend to take things at face value. For good reason: we’re called on to rely on our educated judgments. We’re in the business of futurecasting, person by person. We find the best talent with the most potential for doing great things for an employer in the near future, and we do it over and over again. But we’ve been up for a turbocharge for a long time. A career path that is this intense, combining administrative, personal, and strategic tasking constantly needs sophisticated ways to advance above old archaic practices we no longer want to rely on. With AI, we have it.

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 is sponsored by Leoforce.

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How Machine Learning is Changing Recruiting

Companies approach recruiting in different ways. Facebook’s method, for example, involves acquisitions for human capital and a six-week onboarding boot camp. Of course, that’s not the norm: On average, a recent study found it takes 42 days—and a cost-per-hire of $4,129—to fill an open position. That adds up, especially since Bloomberg recently reported that approximately 10,000 members of the baby boomer generation reach retirement age every day. With numbers like that, it’s no wonder efficiency-boosting advancements in machine learning are beginning to challenge the HR status quo. Let’s explore how machine learning is changing recruiting.

How Businesses Use Algorithmic Assessments

Spotify. Waze. Netflix. Amazon. These are just a handful of the many companies that have opted-in to some form of AI or machine learning. Why the boom? There are lots of reasons, of course, but there’s a primary one that comes to mind: Using algorithmic assessments—i.e., a kind of machine learning—can speed existing processes for consumers and even predict their needs ahead of schedule. In other words, these companies know that to get ahead in this digital marketplace, they’ll need to compete on customer experience (CX). They’re using technology to get there.

The same principle holds true for HR and, more specifically, recruiting. Algorithmic assessments use statistics and historical data to predict whether or not a potential employee will perform well. The benefits of this process are numerous: Recruiters can consider more applicants in less time and with less effort. In addition, they have the added peace of mind that their decisions are backed by more data than subjectivity.

Let’s examine an international startup harnessing the power of algorithmic assessments.

From Reviewing Resumes to Reviewing Social Behavior

It’s impossible to tell everything about potential hires from resumes alone. What if you could incorporate that resume data with information about who applicants really are—their values, likes and dislikes, etc.—and then use machine learning to plug that information into an algorithm that could predict how well they fit within your corporate culture? That’s the premise behind the Indian startup Belong, a brand recently profiled by Forbes as one company leading the machine learning and recruiting charge.

Belong’s algorithms do two things: First, they analyze behavioral data from social networks, blogs, and other digital platforms in addition to the standard information like education, experience, and stated objectives found in CVs to gather “a more holistic and accurate” profile of each candidate. They also use machine learning to better understand the preferences and patterns of each hiring company. From all that data, Belong generates a tailored, SERP-esque database of matches, each unique to the company and the position.

Does it work? Belong’s method reportedly gets a minimum of a threefold increase in company-candidate engagement rates. With numbers like that and customers like Cisco and Amazon, I’d say they’re onto something.

Now, Belong was by no means the first to dip its toes into social when it comes to recruiting. Their application of machine learning to their solution, though, is their secret sauce. Note that my friend and colleague, Megan Biro, CEO of TalentCulture, has written extensively about the power of social media, especially in passive recruiting. The trifecta of relationships, conversation, and unprecedented access to digital tools is a veritable hotbed of HR potential—Meghan has even referred to it as the “tech meets HR marriage,” and I couldn’t agree more. We’ve both got eyes on what’s next.

Speaking of what’s next, are there any plans to shake up what recruiting looks like at your organization in the next year? If you’re looking for a change, what potential do you see in machine learning and HR? What challenges? Let me know in the comments.

Photo Credit: martinlouis2212 Flickr via Compfight cc

 This article was first published on FOW Media.

How Machine Learning is Changing Recruiting

Companies approach recruiting in different ways. Facebook’s method, for example, involves acquisitions for human capital and a six-week onboarding boot camp. Of course, that’s not the norm: On average, a recent study found it takes 42 days—and a cost-per-hire of $4,129—to fill an open position. That adds up, especially since Bloomberg recently reported that approximately 10,000 members of the baby boomer generation reach retirement age every day. With numbers like that, it’s no wonder efficiency-boosting advancements in machine learning are beginning to challenge the HR status quo. Let’s explore how machine learning is changing recruiting.

How Businesses Use Algorithmic Assessments

Spotify. Waze. Netflix. Amazon. These are just a handful of the many companies that have opted-in to some form of AI or machine learning. Why the boom? There are lots of reasons, of course, but there’s a primary one that comes to mind: Using algorithmic assessments—i.e., a kind of machine learning—can speed existing processes for consumers and even predict their needs ahead of schedule. In other words, these companies know that to get ahead in this digital marketplace, they’ll need to compete on customer experience (CX). They’re using technology to get there.

The same principle holds true for HR and, more specifically, recruiting. Algorithmic assessments use statistics and historical data to predict whether or not a potential employee will perform well. The benefits of this process are numerous: Recruiters can consider more applicants in less time and with less effort. In addition, they have the added peace of mind that their decisions are backed by more data than subjectivity.

Let’s examine an international startup harnessing the power of algorithmic assessments.

From Reviewing Resumes to Reviewing Social Behavior

It’s impossible to tell everything about potential hires from resumes alone. What if you could incorporate that resume data with information about who applicants really are—their values, likes and dislikes, etc.—and then use machine learning to plug that information into an algorithm that could predict how well they fit within your corporate culture? That’s the premise behind the Indian startup Belong, a brand recently profiled by Forbes as one company leading the machine learning and recruiting charge.

Belong’s algorithms do two things: First, they analyze behavioral data from social networks, blogs, and other digital platforms in addition to the standard information like education, experience, and stated objectives found in CVs to gather “a more holistic and accurate” profile of each candidate. They also use machine learning to better understand the preferences and patterns of each hiring company. From all that data, Belong generates a tailored, SERP-esque database of matches, each unique to the company and the position.

Does it work? Belong’s method reportedly gets a minimum of a threefold increase in company-candidate engagement rates. With numbers like that and customers like Cisco and Amazon, I’d say they’re onto something.

Now, Belong was by no means the first to dip its toes into social when it comes to recruiting. Their application of machine learning to their solution, though, is their secret sauce. Note that my friend and colleague, Megan Biro, CEO of TalentCulture, has written extensively about the power of social media, especially in passive recruiting. The trifecta of relationships, conversation, and unprecedented access to digital tools is a veritable hotbed of HR potential—Meghan has even referred to it as the “tech meets HR marriage,” and I couldn’t agree more. We’ve both got eyes on what’s next.

Speaking of what’s next, are there any plans to shake up what recruiting looks like at your organization in the next year? If you’re looking for a change, what potential do you see in machine learning and HR? What challenges? Let me know in the comments.

Photo Credit: martinlouis2212 Flickr via Compfight cc

This article was first published on FOW Media.

AI: 5 Ways to Reenvision the Workforce Before the Next Big Wave

What do you do when you’re not ready? Either get ready or wing it. So, imagine that waiting outside that door is your brand new team. They’re nice and shiny and, per the paperwork, each is extremely well qualified. In fact, they are specifically qualified to do their job. Because they are robots.

Let’s not get all I, Robot here. But I’m watching a new wave of artificial intelligence (AI) heading towards today’s world of work, and you’re probably watching it too. You may be wondering when we’re going to have to face this new trend. “Trend” is not actually the term I’d use to describe such a profound and inevitable shift, but that’s what Deloitte calls it in their 2017 Human Capital Trends study. They’re certainly not wrong, but the reason this is more than a trend is that it’s not going to go away.

We’re now in the early stages of adoption — including denial, curiosity, and a whole lot of “not ready.” As Deloitte reports:

  • 41 percent of companies report they have fully implemented or have made significant progress in adopting cognitive and AI technologies within their workforce.
  • 34 percent are in the midst of pilot programs.

Well, I recommend graduating to acceptance. And here are five ways to prepare for the world of work 4.0, or as we like to call it, Here Come the Machines:

  1. Get leadership and managers in gear. Deloitte’s study also found that a mere 17 percent of global executives believe they’re ready to manage a blended workforce of people, robots, and AI. (Remember when a blended workforce meant multigenerational?) That’s the lowest readiness level for a trend in the five years of the Global Human Capital Trends survey, according to Deloitte. The first blind spot is how to actually run things with this new shift — tasking, decision making, workflow, time to execute, who checks what, and the analytics to track how it’s all working.
  2. Leverage its strengths to fix your weaknesses. Jobvite’s CEO, Dan Finnigan, has an interesting take on AI. A Jobvite survey found that 56 percent of the job seekers it polled are concerned about being outsourced or replaced by robots. Instead, as he says, AI and machine learning can help us be better recruiters, and help job seekers find positions that fit. Chatbots are already used in sourcing and hiring that (or, who) can answer potential applicant questions, and increase the odds of their turning in a resume. Chatbots can also screen for skills, measuring responses and engagements in ways humans may overlook. What we need more of, as we know in this era of Big Data, is intelligence. What we need less of: bias. AI can offer a bias-free, objective layer in recruiting and hiring: there are a lot of interesting takes on that.
  3. Seam it into existing functions. This is related, but not entirely the same thing: how can you tap into AI, robotics, and cognitive tech to augment your existing processes? Use AI in your L&D (learning and development) to capture meaningful employee data, and better tailor the learning experience to each user. In terms of work functions, if you can shift a battery of tedious tasks to machines, you not only free up your people, you may also be able to leverage machine learning to find out how to make these tasks far more efficient, with a better outcome.
  4. Don’t underestimate the value of humans. You can free your workforce from some of the mind-numbing busywork, enabling them to take on more supervisory roles. And, raise their skill levels in the process. Another byproduct may be better work/life balance — since people are freed from in-house tasks. As Deloitte’s 2016 report on millennials found, 16.8 percent of those surveyed listed work/life balance, and 13.4 percent listed the opportunity to grow, as key factors in assessing job opportunities. The two will remain a key concern as the workforce becomes even more dominated by this generation.
  5. Bolster the people side of your organizational culture. It’s critical that companies be transparent and positive about what’s happening here. Some in the workforce will see clear benefits to letting machines take over certain jobs, while others may feel downright devalued. At the cusp of change once again, focus at your workforce: Do you recognize them on a regular basis? Are you soliciting and taking their feedback? If not, get on that. Yes: the best recognition software is actually made possible by AI. But it’s going to help: We want to be appreciated, praise has a direct correlation to engagement, and whatever can make it work, I say go for it.

Our view of work is going to change in ways we still don’t understand. As the World Economic Forum (WEF) reported, some 65 percent of children entering primary schools today will likely work in roles that don’t even exist yet. Certainly, we can anticipate how AI and cognitive technology will change office and administrative functions, manufacturing, and production roles. But we also need to envision learning instead of simply data; tasks instead of jobs. And it’s happening soon. According to WEF, by 2020, there will be a new normal. Get ready.

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A version of this was first posted on fowmedia.com

3 Ways Recruitment Automation Will Change Recruiting Forever

The growing need for recruitment automation tools has fueled the recent popularity in AI for recruiting.

With hiring volume predicted to increase next year but recruiting teams remaining the same size or shrinking, interest in recruitment automation will only get stronger.

In 2017, finding top talent will depend on a recruiter’s ability to intelligently automate their workflow.

Recruiting teams are also facing increased pressure to demonstrate data-based KPIs. Talent acquisition leaders are increasingly measuring their recruiting teams by quality of hire in addition to time to fill.

According to LinkedIn’s data, the most important recruiting KPIs are:

  • Quality of hire is the top priority for 60% of talent acquisition leaders
  • Time to fill is the top priority for 28% of talent acquisition leaders

Advances in technology have transformed finance, sales, and marketing departments and industry experts believe recruiting technology will be the next big adoption.

By streamlining some aspects of the recruiting workflow, experts predict recruitment automation will enhance a human recruiter’s capabilities.

Here are three major ways recruitment automation is changing recruiting.

1. Recruitment automation for resume screening

One of the most promising applications of recruitment automation is for resume screening due to three main reasons.

  1. Manually screening resumes is still the most time-consuming part of recruiting.
  2. Up to 88% of resumes received for a role are considered unqualified.
  3. A recruiter spends on average 23 hours screening resumes for a single hire.

Although screening resumes is still the biggest bottleneck in recruiting, technology to address this problem has only recently become available.

Powered by AI for recruiting, intelligent screening software automates the resume screening process. Designed to integrate with an ATS, the software learns what the job requirements are and then learns what qualified candidates look like based on previous hiring decisions.

Using employee data on performance and tenure, the software figures out which candidates went on to become successful and unsuccessful employees.

This type of recruiting software can also enrich resumes by using public data sources about previous employers and candidates’ social media profiles.

Intelligent screening software applies the knowledge it learned about employees’ experience, skills, and other qualifications to automatically screen, rank, and grade new candidates.

Recruitment automation applied to resume screening promises to be a boon to reduce time to hire because it automates a low-value, repetitive task that most recruiters hate to do anyway.

Automated resume screening allows recruiters to re-focus their time on higher value priorities such as talking to candidates to assess their personalities and culture fit.

2. Recruitment automation for pre-qualification

In the current candidate-driven market, candidate experience can make or break whether a top candidate accepts your job offer. Recruitment automation in the form of chatbots holds the promise for improving the candidate experience.

CareerBuilder’s data found 67% of job seekers have a positive impression of a company if they receive consistent updates throughout the application process.

Recruitment automation in the form of chatbots allows human recruiters to provide these consistent updates in real-time by asking pre-qualifying questions related to the job requirements and providing feedback, updates, and next-step suggestions.

By automating repetitive tasks such as answering the same questions about a job, chatbots enhance the pre-qualification capabilities of a human recruiter without additional strain on their time.

3. Recruitment automation for interviews

Recruitment automation for interviewing augments recruiters’ capabilities by allowing recruiters to conduct interviews anywhere any time.

Digitized interview technology records candidate interviews and assesses factors such as their word choices, speech patterns, and facial expressions to predict how well a candidate fits the role.

Recruitment automation applied to interviewing promises to improve quality of hire by providing additional data points on how well the candidate fits the job requirements or company culture.

The takeaways for recruitment automation

Industry experts believe recruitment automation will augment and enhance human recruiters’ abilities, rather than completely replace them.

Recruitment automation is changing recruiting in three major ways:

  1. Automated resume screening that reduces time to hire by saving recruiters the hours spent manually reading resumes.
  2. Automated pre-qualification through chatbots that enhances the candidate experience by providing continuous, real-time feedback.
  3. Automated interviews that improve job fit by analyzing candidates’ words, speech patterns, and facial expressions.

As the adoption of recruitment automation continues to increase, the recruiter role will change.

Talent acquisition is a marketing role, not a sales one. ~ Maren Hogan

Industry experts predict that by reducing time to fill and improving quality of hire, technology will enable recruiters to become more strategic by freeing up time to spend on proactive hiring and workplace planning.

Ironically, recruitment automation will enable recruiters to become more “human” as their skills in candidate engagement and persuasion become more important to compete for talent.

This article was first published on Ideal.com.

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Send in the Robots: The Good and Bad of Automating Your Hiring Process

Futurist and tech billionaire, Elon Musk, believes we may not be far from a time where robots and various forms of artificial intelligence (AI) will perform most jobs. He cautions that a day will come when there will be few jobs a robot will not do better than a human being.

But this reality is still years away.

In the meantime, we need people to fill an increasing number of jobs—today. And we can use AI to our advantage to automate the more tedious tasks of HR, speed up the recruiting process, save companies money and enable them to be more competitive in the race to attract top talent.

Sound incredible? It’s not. It’s very real. Of course, like any technology, AI also has some downsides. Let’s take a look at the positives and the negatives of AI in three areas of recruiting that are most likely to face digital disruption this year.

AI Takes Over the Tedium of Resume Screening

What if you could take one of the most difficult, time-consuming aspects of HR and automate the process to do it faster and more effectively than any human being could accomplish? More than half (52 percent) of recruiting managers say finding potential applicants in giant talent pools is the most challenging part of their job.

Finding a single qualified candidate from predictive screening, which shares the traits of successful hires with just a glimpse at a resume, can take up to 23 hours of a recruiter’s time.

“Candidate screening is a process better handled by algorithms that can effortlessly, accurately, respectfully, and predictively screen thousands or millions of candidates per day (or hour) for business success,” states Greta Roberts, writing for SalesForce.com. These powerful algorithms accomplishes this feat by filtering for keywords and other factors that match those of successful past hires.

Some job seekers fear that AI software won’t view candidates as individuals or will misunderstand aspects of their resume. But when a recruiter makes a decision after a 6-second glimpse at that same resume, he or she isn’t necessarily taking time to think about the person behind the buzzwords either.

AI programs don’t get tired and overlook important indicators that someone may be the right person for the job. In fact, the more resumes AI reviews, the better it gets at finding top candidates. The numbers are in and the case for AI is compelling. According to recruiting software firm Ideal, companies that have adopted AI for recruiting software who use it have seen a:

  • Performance increase of 20 percent
  • Revenue per employee grow by 4 percent
  • Employee turnover drop by 35 percent

Chatbots Keep Prospects Looped In

AI-powered chatbots are already being used in the food service industry to assist customers with placing orders, and in retail to answer questions and manage some customer complaints. It’s easy to make the leap to chatbots that can schedule interviews and answer job candidates’ frequently asked questions. From an HR director’s perspective, it’s all about being able to deliver the information candidates need, when they need it, in their preferred format.

Certainly, no one reaches out via chat interface with the thought, “I really hope I get to speak to a robot today!” But it definitely beats being ghosted by an HR director after you thought that first interview went so well.

And recruiters who spend less time sending follow-up emails can now focus on the high-touch areas of their job, such as connecting with candidates after they’ve passed the initial screening process, slam-dunked the first and second interviews, and now require some personalized attention to convince them to sign on.

Streamline Onboarding with AI

It’s important to make new employees feel at home with a personalized tour, but so many aspects of onboarding simply don’t need the expertise of an HR director. Enter Jinie, an HR chatbot that can help walk new hires through those first confusing days on the job, share information about programs and policies, and answer common questions.

However, to gain widespread adoption, these bots need to be:

  • In a familiar format—perhaps integrated into existing communications platforms like Slack
  • Secure enough to transmit sensitive HR data
  • Seamless, so the experience feels more like speaking to a human being than a bot

Will AI Replace HR?

Clearly, AI can streamline and simplify many aspects of HR. But HR directors and recruiters won’t be replaced anytime soon.

AI can handle screening applicants, initial outreach, schedule interviews, and even manage aspects of the onboarding process. For example, Wendy, an AI chatbot developed by tech startup WadeandWendy, can complete the first interview on behalf of the HR team.

By automating these tasks, HR professionals are freed up to step in when their strategic expertise is required, and to oversee the entire process for quality control. After all, AI is only as good as the data we feed it. Biases can (and do) creep in—all based on what we, the human users, may inadvertently teach the AI algorithms over time.

As an HR professional, you take extra care to ensure you evaluate all candidates on equal footing, in the same way, you will have to oversee the use of AI to help provide unbiased decisions—and to make the final calls on hiring and promotions.

If you could save time and money by implementing tools to help you do your job more efficiently, wouldn’t you? For HR departments, those tools exist and improving every day. When it comes to streamlining your HR processes, it may just be time to send in the robots.

A version of this was first posted on Converge.xyz

#WorkTrends Recap: How Artificial Intelligence Can Change HR and Recruiting

Are robots coming to work? Not entirely, but something that is going to be a game changer is about to take over the world of HR. Artificial Intelligence or AI is coming to an HR department near you and maybe sooner than you think.

Artificial intelligence is going to do for HR what the car did for transportation. It’s going to transform how we look at data, what data is worth considering and help us to interpret the intricacies of big data.

This week, I hosted special guest Jessica Miller-Merrell, founder of Blogging4Jobs, to discuss this timely topic.

Jessica and I discussed ways AI has already impacted HR. She also shared her predictions for the future.

Here are a few key points that Jessica shared:

  • AI has the potential to make work easier for our teams
  • AI can remove the unconscious bias from hiring and find candidates that might otherwise be overlooked
  • You need data for AI to be effective

Did you miss the show? You can listen to the #WorkTrends podcast on our BlogTalk Radio channel here:  http://bit.ly/2fhS10Y

You can also check out the highlights of the conversation from our Storify here:

Didn’t make it to this week’s #WorkTrends show? Don’t worry, you can tune in and participate in the podcast and chat with us every Wednesday from 1-2pm ET (10-11am PT). Next week, on Nov 9, special guest host Tim McDonald will be joined by Elaine Orler, chairwoman of the Talent Board, to discuss recruiting trends and predictions for 2017.

Remember, the TalentCulture #WorkTrends conversation continues every day across several social media channels. Stay up-to-date by following our #WorkTrends Twitter stream; pop into our LinkedIn group to interact with other members; or check out our Google+ community. Engage with us any time on our social networks, or stay current with trending World of Work topics on our website or through our weekly email newsletter.

 

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Artificial Intelligence and HR: The New Wave of Technology

It’s no secret that I love technology. From the domination of mobile to the latest in recruitment tools and gamification, and how video and live streaming is having an impact on hiring and training—changes are afoot that many of us couldn’t have imagined 15 or so years ago. And I love it all.

The reason this “tech meets HR” marriage is so exciting is how quickly the technology evolution has disrupted HR and enhanced the way HR professionals get things done. Now there’s another big disrupter on the horizon, one that you would be wise to keep your eyes on: Artificial intelligence.

What is Artificial Intelligence?

In layman’s terms, artificial intelligence (or, AI as it’s commonly referred to), is an area of computer science where computers are “developed” to behave much the way humans do. There are three levels when it comes to AI, depending on how advanced the computers get, and the measuring stick is “human reasoning.”

Strong AI genuinely simulates human reasoning. These systems not only think, but can also “explain” how humans think and reason.

Weak AI includes systems that can “think” (computers playing chess against human chess masters, for example), but don’t tell us anything about how humans think, and the systems don’t really think themselves.

In-between AI includes systems that are informed by, or inspired by human reasoning. Examples include Google’s Deep Learning (driven by big data) and IBM’s Watson, a system that can answer questions by analyzing thousands of pieces of text, discerning patterns, and weighing evidence, a sort of “layered learning,” much like the way our brains learn. This in-between area is where most AI work is being done today.

Artificial Intelligence Meets HR

The biggest driver of AI’s impact in the HR industry is the massive growth of big data. Until now, we haven’t had access to simple software systems with which to track and analyze internal employee data (think sick days, vacation requests, hiring trends, workflow, etc.). Today, most businesses have undergone some degree of digital transformation, and rely on this type of technology. HR professionals are recognizing that this valuable data and the insights teased from it play a major role in reducing riskand driving decision-making, when it comes to talent management and organizational performance.

Here are four ways AI has the potential to have an enormous impact on HR.

  1. Personalization: It’s not news that people have very different styles of learning, and, with the many generations now filling the workforce, embracing modern training practices has never been more important. AI is helping to personalize corporate learning, by capturing meaningful employee data relating to a wide range of learning experiences and behaviors. The same machine learning computer algorithms that “learn and recommend” by analyzing your choices of where to shop or what to eat, will “learn and recommend” when it comes to employee training. In fact, these systems will continue to parse and analyze as more and more employee interactions occur, and be able to tweak training programs accordingly, making training more efficient, and training outcomes more effective.
  1. Workflow Automation: Scheduling, scheduling, and rescheduling. The bane of many of our existences, yes? Well, AI is poised to be a game-changer when it comes to workflow problems. According to a recent com article, the next few years should see software that automates hiring processes like “…interview scheduling, employee performance reviews, employee onboarding, and even the answering of basic HR questions.” I, for one, can’t wait.
  1. Improved Recruitment: HR is, by its very name, one of the most human-centric industries out there. But human beings are complicated, and it’s very difficult to get base-level data on individual people—enough to run an analysis on—especially when hiring. Enter predictive analytics using natural language. Still, in its (relative) infancy, the software driving natural language processes and predictive language analysis will help speed up recruitment by allowing you to weed people out faster, and with fewer mistakes.
  1. Better prediction models: AI will get to know your company almost better than you do. Whether it’s predicting future turnover rates, reduced (or increased) employee engagement levels, concerns about internal employee communications, project completion problems, and any other unexpected hidden issues that would usually take years to surface, artificial intelligence will (most likely) be one step ahead of you. And when it comes to cost savings and overall organizational efficiencies, that’s a very good thing.

The pace of technological change in our work worlds is happening so quickly that a recent World Economic “Future of Jobs” report estimated “…some 65 percent of children entering primary schools today will likely work in (jobs) that don’t currently exist.” And many of those jobs will probably be related to computer learning and predictive analytics. Human resources professionals need to start embracing big data today, so they can be prepared to embrace the incredible advancements in artificial intelligence of tomorrow.

A version of this was first posted on Converge.

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