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10 Ways in which Artificial Intelligence (AI) is revolutionizing Talent Acquisition practices

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10 Ways in which Artificial Intelligence (AI) is revolutionizing and disrupting talent acquisition practices - The rise of the Cognitive Recruiter

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10 Ways in which Artificial Intelligence (AI) is revolutionizing Talent Acquisition practices

  1. 1. HOW ARTIFICIAL INTELLIGENCE (AI) IS REVOLUTIONIZING TALENT ACQUISITION PRACTICES CHARLES COTTER PhD, MBA, B.A (Hons), B.A www.slideshare.net/CharlesCotter SIERRA HOTEL, RANDBURG 16 AUGUST 2018
  2. 2. PRESENTATION OVERVIEW • The current context and the future of talent acquisition – the rise of the robots and the dawn of smarter (cognitive) recruitment • The business case for AI in talent acquisition • 10 Ways in which AI is revolutionizing talent acquisition practices
  3. 3. FUTURE OF WORK “There are really three themes that’ll shape the future of talent, Artificial Intelligence and automation, the skills gap and the rise of independent work.” (Jeff Weiner, CEO LinkedIn)
  4. 4. THE FUTURE OF HRM • Strategic goal: To transform to be a HR Business Partner (role) • Strategic objective: To create a HIPO (High performing organization) • Transform from recruitment to Talent Acquisition: ❑Acquire talent faster ❑Acquire better quality talent ❑Acquire talent more intelligently (smarter) • Q1: So how strategic is HRM? • Q2. Is AI the solution – the driver/accelerator of change?
  5. 5. RESEARCH: DIAGNOSIS OF STRATEGIC HRM (COTTER, 2018)
  6. 6. SABPP HR AUDITED RATINGS (X39 COMPANIES)
  7. 7. HOW HAS RECRUITMENT CHANGED? (COTTER, 2017) • Savvy, future-focused recruiters have transitioned from face-to-face recruitment to facilitating the interface between people and technology, which is at the coalface of business strategy. • The employment landscape has changed from “talent wars” – battlefield to a “talent economics” – trading floor. • Smart recruiters have to transform to “behavioural economists.” • Next level (future-fit) recruitment in the Gig Economy?
  8. 8. DELOITTE’S HCM TRENDS 2017 – THE RISE OF THE COGNITIVE RECRUITER • Leveraging new technologies—from social to cognitive • Evolution toward cognitive capabilities that build on mobile and cloud technologies, as well as social networks e.g. LinkedIn. • The more innovative ideas and solutions are centered around cognitive technologies such as artificial intelligence (AI), machine-to-machine learning, robotic process automation, natural language processing, predictive algorithms and self-learning. • Chatbots are becoming popular, including the recently launched Olivia, which guides candidates through an application process with sequenced questions.
  9. 9. DELOITTE’S HCM TRENDS 2017 – THE RISE OF THE COGNITIVE RECRUITER • IBM’s AI pioneer, Watson, is now moving into the space with three new technologies: ❑ A machine learning platform that ranks the priority of open requisitions; ❑ Social listening for an organization’s and competitors’ publicly available reviews on Glassdoor, Twitter, and newsfeeds and ❑ A tool that matches candidates to jobs through a “fit score” based on career experiences and skills. • These technologies take pre-existing social data and information and then apply advanced cognitive capabilities to deliver actionable analysis.
  10. 10. THE BUSINESS CASE FOR AI IN TALENT ACQUISITION • A.I. is empowering recruiters today to become smarter and more efficient by reinventing the hiring process. • #1: Machines as matchmakers • #2: Using AI to reduce unconscious bias • #3: Liberating employers to focus on the human side of hiring • #4: Improved Candidate Experience • #5: Faster Time to hire - AI streamlines the recruiting process by automating high-volume and often time-consuming tasks
  11. 11. THE BUSINESS CASE FOR AI IN TALENT ACQUISITION • #6: Superior engagement with passive candidates • #7: Balancing recruitment risk • #8: Improved quality of hire • #9: Real-time skill-set testing and evaluation • #10: Measure the impact of new hires over time
  12. 12. STRATEGICALLY CAPITALIZING ON AI – APPLING THE 3 A’s (MEISTER, 2018)
  13. 13. AGREE OR DISAGREE? WHY?
  14. 14. 10 WAYS IN WHICH AI IS REVOLUTIONIZING TALENT ACQUISITION PRACTICES • #1: SOURCING OF CANDIDATES • #2: PROGRAMMATIC JOB ADVERTISING • #3: CANDIDATE OUTREACH • #4: CANDIDATE EXPERIENCE AND RELATIONSHIP BUILDING (JOB SHOPPERS) • #5: AI-POWERED ASSISTANTS (CHATBOTS) AND MACHINE LEARNING ASSISTING APPLICATION
  15. 15. 10 WAYS IN WHICH AI IS REVOLUTIONIZING TALENT ACQUISITION PRACTICES • #6: PROMOTING EFFICIENCY • #7: CV SCREENING • #8: DEEPER AND RICHER CANDIDATE INSIGHTS • #9: ELIMINATING UNCONSCIOUS HUMAN BIAS BY MEANS OF PREDICTIVE ANALYTICS • #10: ADVANCED COMPETENCY TESTING
  16. 16. #1: SOURCING OF CANDIDATES • Arya, a sourcing app that uses machine learning (ML) to identify the patterns of successful employees and draws potential candidates out of the millions of online profiles by applying this algorithm to a company’s existing résumé database and beyond. • Arya adapts and learns based on the performance of new hires by analyzing data like performance reviews, turnover rates and the timing and frequency of promotions. • It could significantly reduce the time it takes to identify top candidates. • By automating the candidate sourcing process, AI can double recruiters’ efforts by scouring the internet for promising candidates while the recruiter focuses on other tasks.
  17. 17. #1: SOURCING OF CANDIDATES • AI in the form of machine learning sources qualified candidates online or within resume databases such as CareerBuilder for recruiters to follow up with. • ClearFit saves recruiters sourcing time by automatically finding and ranking candidates. • Predictive analytics is increasingly important to TA, as sophisticated analytics teams begin to prioritize recruiting workflows, conduct workforce planning, evaluate different recruiting sources, assess quality of hire and use pre-hire assessments e.g. PredictiveHire, a cloud-based SaaS analytics solution provider. • The applicant tracking system (ATS) is being reinvented by innovative solution providers who are augmenting the ATS with other TA technologies, including candidate relationship management, video interviewing and analytics.
  18. 18. #1: SOURCING OF CANDIDATES • HC Trend: Optimizing sourcing channels (Deloitte, 2017) • Gamification - Forward-looking organizations are also beginning to employ simulations and gaming to connect with talent, particularly Millennials, and analyze whether candidates are primed to succeed in a given role (Deloitte, 2017). • Ansaro is unifying all the data companies have about their employees to build predictive models that will help them hire in smarter way.
  19. 19. CASE STUDY: A HIRING ALGORITHM AT GOOGLE • One of the few firms to approach recruiting scientifically, Google developed an algorithm for predicting which candidates had the highest probability of succeeding after they are hired. • Its research also determined that little value was added beyond four interviews, dramatically shortening time to hire. • Google is also unique in its strategic approach to hiring because its hiring decisions are made by a group in order to prevent individual managers from hiring people for their own short-term needs. • Under Project Janus, it developed an algorithm for each large job family that analyzed rejected resumes to identify any top candidates they might have missed. • They found that they had only a 1.5% miss rate and as a result they hired some of the revisited candidates.
  20. 20. #2: PROGRAMMATIC JOB ADVERTISING • Berendt (2018) emphasizes the strategic business imperative of programmatic advertising. This technique gives recruiters the ability to place highly targeted ads in front of the right people at exactly the right time, based on their browsing history and online activity. • Cognitive recruiters can understand candidate browsing activity using cookies to track candidates who visit their company career page, allowing them to compile records of what other pages they’re browsing. • By using data management processing (DMP), recruiters can then select a target set and find other candidates who match up. • Plug this data into an online advertising platform and it ensure that a specific group of users sees your job posting, wherever they are, expanding your reach significantly beyond the local talent pool. • This can help recruiters grow the top of the recruitment funnel with qualified and interested talent from different regions e.g. LinkedIn already offers similarly targeted job posts , shown to the most relevant candidates.
  21. 21. WRITING THE PERFECT JOB ADVERT • The job advert is the genesis of a job applicant’s journey and it’s likely to be the initial window of contact with a prospective company. • Textio is an example of a company that gets how important a high-quality job post is for the number of qualified and diverse candidates that will apply as a result. They aim to help companies create better job postings that will help differentiate them. • Their approach is twofold: ❑ Data and predictive analytics. Textio uses algorithms to assess and analyze meaningful language patterns that cause some posts so succeed where others don’t. ❑ Using those keyword terms that make an ideal post, depending on the candidate the company is looking for, the software then suggests language choices that will lead to a more successful placement. ❑ Even better is the fact that the software can learn. As the number of analyzed postings, adverts and descriptions increases, so does the accuracy of the language predictions. ❑ Textio leverages an extensive database to help write better job adverts • Job postings: Technology that uses sentiment analysis helps recruiters identify potentially biased language and provides suggestions on creating job descriptions that attract a more diverse candidate pool.
  22. 22. CANDIDATE PROFILE AUGMENTATION • Berendt (2018) predicts that AI will soon make it possible to see far more than a candidate’s job history. • Using the same technology that allows companies to model people’s behaviour based on their browsing histories and interests, recruiters could infer a person’s interests and latent skills. • This would allow recruiters to recommend jobs related to what they want to do, not just what they currently do. • This could be especially useful for roles that are difficult to fill. • If recruiters were able to augment the profile of people on LinkedIn with data on their interests, intent and activity, they would be able to find them.
  23. 23. #3: CANDIDATE OUTREACH • Most companies currently have one version of their employee value proposition (EVP) that they use for all outreach. • Savvy recruiters now have access to new technologies to forge connections with candidates and strengthen the employment brand. • HC Trend: Building a strategic and digital employment brand (Deloitte, 2017) • Berendt (2018) states that companies will soon develop thousands of personas, allowing recruiters to quickly hyper-personalize candidate outreach to speak more directly to an individual’s needs.
  24. 24. #3: CANDIDATE OUTREACH • Using intelligent targeting and Crystal Knows, cognitive recruiters can attract people using a value proposition that’s tailored exactly to their needs. • Rediscovery: Similar to sourcing, recruiters are able to use AI that analyzes a job description and then searches their existing ATS database to rediscover candidates who applied for a prior role who fit the requirements of a current open requisition.
  25. 25. #4: CANDIDATE EXPERIENCE AND RELATIONSHIP BUILDING (JOB SHOPPERS) • Savvy recruiters now have access to new technologies to forge connections with candidates and strengthen the employment brand (Deloitte, 2017). • Beamery focuses on treating candidates like customers. The company’s candidate relationship platform ‘proactively builds relationships with passive candidates, reduces hiring cycles and creates a single source of truth for all your hiring data’. • This means that the AI and ML elements of the platform identify so-called priority (passive) candidates and better yet, even suggest what times best to reach out to those candidates. • Beamery is a good example of how a company is using AI in recruitment to create better, more human relationships with candidates and to truly treat them like customers. • Engage Talent allows recruiters to discover passive job seekers and target them with personalized messages at the right time.
  26. 26. #4: CANDIDATE EXPERIENCE AND RELATIONSHIP BUILDING (JOB SHOPPERS) • AI in recruitment can significantly improve candidate engagement through improved communication between candidates and employers. According to Mya, a product developed to simplify recruitment, its system has averaged “a 9.8 out of ten on overall candidate experience”. • This is because it can provide candidates with updates, feedback and guidance, as well as answer their questions in real-time. • This communication - which has a significant impact on candidate experience - is generally lacking in most companies. • Messaging - recruiters are aided by chatbots that use natural language processing to collect information from candidates, ask screening questions, answer FAQs about the job, and schedule an interview. • Information collected by the chatbot is then fed into an ATS or sent directly to a human recruiter to follow up.
  27. 27. AGREE OR DISAGREE? WHY?
  28. 28. #5: AI-POWERED ASSISTANTS (CHATBOTS) AND MACHINE LEARNING ASSISTING APPLICATION • Some companies are already using chatbots in recruiting. Sutherland, for example, uses a bot called, Tasha to answer basic questions from an applicant, responding 24-7. • Bots can also follow up with candidates if they aren’t actively progressing with an application. • They can facilitate the conversation with once [people] arrive at the website, and they can guide [them] across the funnel. • By means of NLP, Olivia engages with candidates via the web, various mobile platforms and/or social channels and she also handles the scheduling part of the recruitment process. • Tools like Mya can decode a candidate’s responses through Natural Language Processing to spot certain skills. • Mya can also ask questions to fill in gaps in the candidate’s résumés, giving recruiters a clearer picture of their suitability for a role.
  29. 29. #6: PROMOTING EFFICIENCY - SCHEDULING MEETINGS WITH CANDIDATES • X.ai, a solution that can help tackle the administrative nightmare of scheduling interviews. • According to Berendt (2018), automated appointment setting will help recruiters to quickly and easily schedule meetings with candidates. • Software reviews the recruiter’s calendar, asking a few basic questions and offering viable options to the candidate. • However, the human element won’t disappear entirely from recruiting. Meeting with candidates to give them a good feel for your company culture will remain vital. • With so much automation elsewhere, recruiters’ time will be freed up to focus on things like the candidate experience, so these meetings could become even better.
  30. 30. #6: PROMOTING EFFICIENCY - ELIMINATING TEDIOUS TASKS • For most recruiters, the worst part of their job is often the most time-consuming—the administrative tasks of screening candidates and scheduling interviews. • With the help of AI, recruiters and hiring managers can reduce wasted time by automatically screening obviously unqualified candidates’ resumes using keyword and qualification searches. • AI can also help schedule interviews with those qualified candidates with an auto-email interview request service or chat-based program that surprisingly brings a bit more personalization to the process. • Not only does this save time for recruiters to focus on more important tasks, it also accelerates the screening process, reduces time-to-hire, and ultimately gives those companies an advantage when competing with other companies for talent.
  31. 31. #7: CV SCREENING • According to Berendt (2018), some companies are already using résumé screenings to find talented candidates and remove unqualified ones. • ML technology helps recruiters automate screening by learning what existing employees’ skills and other qualifications are and applying this knowledge to screen and grade new candidates. • Once a new résumé is received, recruiters can benchmark that with the knowledge that they have from their existing employer base. • It can be screened not only for the keywords, but also for the meaning. So, if someone has used a different term to describe what they do, the solutions are now clever enough to decode it. • These solutions can quickly and effectively compare prospective candidates to those who’ve proven talented in the past. With this data, you can more efficiently find those best suited for the job.
  32. 32. #7: CV SCREENING • AI can find patterns. By knowing who got a job within your company, these systems are able to predict who would be a successful candidate going forward. • Recruiters know all too well how resumes are an incomplete picture of someone’s skills, achievements, capabilities and most importantly, personality and company fit. • AI technology is enhancing screening measures e.g. software Harver uses engaging tests to assess candidates on the types of tasks they’ll actually be asked to do on the job. • Ansaro goes a bit beyond that to cull all the data and metrics companies have on their employees to build predictive models and personality profiles that help lead them to candidates who fit the company culture and job requirements more accurately.
  33. 33. #8: DEEPER AND RICHER CANDIDATE INSIGHTS - NATURAL LANGUAGE PROCESSING (NLP) According to Berendt (2018), AI will help cognitive recruiters learn even more - analyzing more than just the words themselves. These solutions use natural language processing to check the fluency of the speech, the pronunciation, the vocabulary and even the progression of ideas. This is beneficial for checking language competency when hiring in diverse markets, but it will also be useful for testing native speakers. The AI will analyze their speech to learn what type of person they are and tell recruiters how engaging or trustworthy they sound. For jobs where talking plays a big part e.g. sales, this will be particularly important.
  34. 34. #8: DEEPER AND RICHER CANDIDATE INSIGHTS - VIDEO INTERVIEWS & FACIAL AND SPEECH RECOGNITION SOFTWARE Berendt (2018) believes that in a future video interview scenario, a candidate may only have to speak to the camera while the machine takes them through a list of questions. As the candidate talks to the machine and the machine processes their speech to give the recruiter a detailed report, there is no need for human interaction - a huge time-saver. This will free up a lot of time for recruiters, who can still meet with top candidates but won’t need to laboriously interview every single applicant. Companies like HireVue use facial and speech recognition software to analyze the candidate’s body language, the tone of their voice, their stress level etc. It might also help eliminate unconscious bias, since the technology won’t have the same hardwired preconceptions as humans.
  35. 35. #8: DEEPER AND RICHER CANDIDATE INSIGHTS – DETECTING IRREGULAR CANDIDATE BEHAVIOUR DURING VIDEO INTERVIEWS • Using video as a tool for a compelling candidate experience. (Deloitte, 2017) • Video interviews are rapidly becoming an integrated part of (mobile) recruiting. Apart from promoting efficiency, it also allow them to get a feel for a candidate’s energy, the way they present themselves and a more tangible overall impression. • Paññã is an AI-driven platform, specialized in technical hiring. The platform provides AI hiring, an ever-growing repository of dynamic questions, expert evaluation, recorded interviewing, video conferencing and voice and face recognition. • The company uses ML to verify the applicants’ video interviews and see if there is any type of strange behaviour going on. This means the system can detect if the candidate is regularly looking away from the screen – which may indicate the use of cue cards – or if there is another voice on the recording – which may indicate that the applicant has a friend on the phone for help. • Although Paññã is powered by AI, there is also an intuitive interface.
  36. 36. #8: DEEPER AND RICHER CANDIDATE INSIGHTS – DETECTING IRREGULAR CANDIDATE BEHAVIOUR DURING VIDEO INTERVIEWS • With the help of emotion recognition software like Affectiva, companies can better assess candidates' emotional intelligence and truthfulness during video interviews by analyzing facial expressions, their word choice, speech rate and vocal tones. • These types of software not only help recruiters determine if a candidate is being honest and showing genuine interest in a position, but they also help remove human biases. • AI software can help identify whether their judgement is correct or if this individual isn’t all that interested and they’d be better off spending their time with other potential candidates.
  37. 37. #9: ELIMINATING UNCONSCIOUS HUMAN BIAS BY MEANS OF PREDICTIVE ANALYTICS • Studies have shown that humans are notoriously poor at picking the right applicant and a meta-analysis illustrated that algorithms can outperform human experts in hiring. • According to IBM Watson Talent, gut-based decisions are no longer acceptable - it’s time for HRM to rethink its talent strategies – intuition to intellect. • According to a 2017 Glassdoor report, as much as 66% of Millennials are considering to leave their current jobs by 2020. • Therefore, an AI recruitment tool using predictive analytics to recommend candidates may be just be the solution for many companies that struggle with unwanted turnover.
  38. 38. #9: ELIMINATING UNCONSCIOUS HUMAN BIAS BY MEANS OF PREDICTIVE ANALYTICS • However, only 7% of companies use analytics to make sourcing predictions and take future actions on those issues. • Harver, pre-hiring platform, uses data and predictive analytics to make predictions on an applicant’s likelihood to succeed in the role that they’ve applied for. • Based on criteria that are specific to the job and others that are linked to a company’s cultural requirements, algorithms calculate a matching score for every candidate. • Cognitive systems increase the likelihood of recruiters identifying the best fit.
  39. 39. #10: ADVANCED COMPETENCY TESTING • According to Berendt (2018), sophisticated companies are providing neuroscience games, with the objective of determining the candidates’ emotional and cognitive traits. • These games are an excellent tool to measure candidates’ soft skills that may otherwise be difficult to detect. • They can also help recruiters assess a candidate’s willingness to take risks e.g. companies like Pymetrics.
  40. 40. #10: ADVANCED COMPETENCY TESTING • This AI functionality enables recruiters to place the candidate in a better role or disqualify them from the job application process. • Filtered can help assess technical candidates through auto-generated coding challenges.
  41. 41. CONCLUSION • Key points • Summary • Question and Answer session
  42. 42. LIST OF SOURCES • https://business.linkedin.com/talent-solutions/blog/future-of- recruiting/2018/9-ways-ai-will-reshape-recruiting-and-how-you-can- prepare • Deloitte Consulting LLP. 2017. Global human capital trends report for South Africa 2018. Oakland, CA: Deloitte University. • Deloitte Consulting LLP. 2018. Global human capital trends report for South Africa 2018. Oakland, CA: Deloitte University. • https://www.forbes.com/sites/valleyvoices/2018/01/29/how-ai-is- changing-the-game-for-recruiting/#2fa583811aa2 • https://harver.com/blog/uses-ai-in-recruitment/?cn-reloaded=1 • http://www.yoh.com/blog/future-recruiting-4-ways-artificial-intelligence-is- changing-the-hiring-process
  43. 43. CONTACT DETAILS • Dr. Charles Cotter • (+27) 84 562 9446 • charlescot@polka.co.za • LinkedIn • Twitter: @Charles_Cotter • https://www.facebook.com/CharlesACotter/ • http://www.slideshare.net/CharlesCotter

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