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IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESAI in HR: The New FrontierINTRODUCTIONThe robots have arrived. Only they don’t look like robots. AI- and machine learning-based technology is embedded in thetools you likely interact with every day—navigation apps; predictive text in e-mail and messaging; digital assistants likeAlexa and Siri; and recommendation engines on Netflix, YouTube and Spotify. Today, AI-powered technology seamlesslyintegrates into the things we already do—and it’s poised to do the same for HR.Since AI-based solutions predict, recommend and communicate based on data, AI has the opportunity to transformHR practices in areas where there is adequate data and where that data can be utilized to create greater efficiency,communicate at scale, provide recommendations and predict outcomes. Many companies already have a vast amount ofdata on candidates and employees that can help them source, assess, hire, train, develop and pay people more efficientlywith the application of AI-driven tools.The International Data Corporation(IDC) estimates that worldwide spending on AI systems will reach 35.8 billionin 2019 and 79 billion by 2022. And Gartner estimates that, by 2022, AI-derivedbusiness value will reach 3.9 trillion.With its vast amount of underutilizeddata, HR has the potential to lead digitaltransformation and drive business valuewith AI-powered solutions.RECRUITINGRecruiting is the most well-developedarea of AI in HR, for several reasons. Thevast size of the recruiting funnel—fromjob ad impressions, careers site visits,applications and hires—offers a wealthof data that AI-powered tools can learnfrom. Additionally, the recent talentshortage in a strong economy means thatcompanies are paying closer attention tocandidate experience and investing morein recruiting tools to improve it. Finally,shortening employee tenure has drivencompanies to seek out ways to makesmarter hiring choices that ensure quality hires while eliminating hidden biases.The recruiting process is filled withnumerous repeatable tasks such as resume screening and interview schedulingthat, when given to AI, free up recruiters’time to focus on what matters: the humaninteraction between candidates and company personnel. And that can be done atscale with an intelligent chatbot trainedto conduct preliminary screening andmanage the interview process.The interview process is rife with bias,and many of these tools help reduce race,gender, education and age biases. A keycaveat is that an AI-based system can onlyreturn results as good as the data and thetraining put into it. For instance, if youremployee population leans toward certainprofiles, algorithms based on matching thecharacteristics of current employees withcandidates will not help increase diversity.However, with oversight, AI can correcthidden biases. (See the final section of thispaper for a discussion on the ethics of AI.)1 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New FrontierNOVEMBER 2019PRODUCED BYEXECUTIVE NETWORKHR P E O P L ES T R AT E G YWRITTEN BYJosh Bersin HR People Strategy 2019. hrps.org
IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESRecruiting ProcessAI SolutionCandidate SelectionScreen candidate resumes, rediscover talent from existing poolsSourcingSurface appropriate candidates from online profiles, facilitatereferralsRecruitment MarketingAutomated job ad placement and biddingScreeningNatural language processing (NLP) based chatbots to screencandidates, re-engage talent poolsInterviewingVideo interview analytics, chatbot-enabled scheduling,interview process analytics and predictionsAssessmentAssessments based on skills and cultural fitDiversity and InclusionIdentify and reduce bias in job descriptions, candidatecommunications, and interview patternsLEARNING AND EMPLOYEE DEVELOPMENTTalent availability, rapid technologychange, and shifting candidate behavior are some of the factors contributingto companies’ increased focus on retention through reskilling employees, providing better learning and onboardingprograms, and developing top employees into leaders.An Edelman study found that 59 percent of global employees fear job lossdue to a lack of retraining and skills.Companies that invest more in “learning in the flow of work” are well poisedto attract and retain employees, as wellas to ensure their business stays competitive: 62 percent of global executives believe they will need to retrainor replace more than a quarter of theirworkforce by 2023 due to advancingautomation and digitization.AI-powered tools facilitate employeegrowth through automated matching ofinferred skills, recommending adjacentskills, and serving up relevant learningcontent. Additionally, AI-based coachFunctionmatching, virtual reality (VR) trainingand micro-learning help provide employees with the knowledge they needto succeed on the job.Internal mobility is a growing areaof focus, and some companies are having success using AI-based systemsthat look at job experience inside andoutside the company, and match thisinformation against open positions,offering employees guidance on wherethey might go next.CORE HR AND SERVICE DELIVERYCore HRAI-powered toolsfacilitate employeegrowth throughautomated matchingof inferred skills,recommendingadjacent skills, andserving up relevantlearning content.Time tracking, payroll, expense reportingand benefits administration are benefiting from AI-powered analysis, employeenudges and predictive capabilities. Animportant area is compensation.PayScale’s 2019 study of compensationpractices found that less than 40 percentof companies do any compensation equity analysis for race or gender. With amassive set of pressures facing companiesAI SolutionLearningLearning/training matching, learning content deliveryCoaching/MentoringCoach/mentor matchingInternal MobilitySkills matching and recommendations against openings2 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New Frontier HR People Strategy 2019. hrps.org
IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESright now for gender pay equity reporting,it’s prime time for AI-based tools to helpcompanies determine fair pay and ensureall employees are being paid fairly.Compensation is a tricky topic becausethere are so many objective factors thatshould determine pay: education, experience, work responsibilities, performanceratings and market competition. AI canhelp determine fair pay in a way thateliminates subjective biases like gender,race, age and favoritism and that identifiespotential inequities.HR Service DeliveryWith the trend toward employee experience, employers now have to design HRservices relating to pay, benefits, expenses and paid time off (PTO) requests foremployee audiences expecting consumer-grade experiences in the workplace.The largest organizations have builtemployee service centers and self-service portals that merge HR, IT and otherworkplace services like badging, commuter passes and gym discounts.AI-based chatbots already have a foothold with customer service organizations:37 percent of service leaders are either piloting or using artificial intelligence botsand virtual customer assistants (VCAs),and 67 percent of those leaders believethey are high-value tools in the contactcenter.Chatbots based on natural languageprocessing (NLP) have t he ever-increasing intelligence to answer routineemployee questions and assist with employee journeys, freeing up HR administrators to focus on more complex tasks.HR AreaAI IN ENGAGEMENT, PRODUCTIVITYAND WELLNESSEmployee Engagement andFeedback SystemsIn the evolution of employee engagementto employee experience, companies nowconsider every aspect of how an employee engages with his or her job, the company and colleagues.The annual survey has gone by thewayside in favor of continuous feedbackin the form of pulse surveys and otherfeedback systems that can be analyzedwith NLP-based tools. Such tools can surface key themes, help diagnose managereffectiveness and detect risks stemmingfrom discrimination or harassment.Organizational Network AnalysisThe highly networked workplace hasvast amounts of data from e-mail, calendaring, messaging platforms and motionsensors that can be fed into systems usingorganizational network analysis (ONA).This technology can help companiesidentify strong influencers, patterns ofstrong or weak teamwork, micro-management and nondiverse or noninclusivecommunications.The applications of ONA are as vastas the data available. By analyzing timespent in meetings, it can help eliminatetime wasted in unproductive meetings.Analyzing the behavior of sales teamsagainst performance can help identifynew sales processes. Looking at motionpatterns from embedded sensors can create more efficient processes and realisticguidelines based on data versus hunches.The largestorganizations havebuilt employee servicecenters and self-ser viceportals that merge HR,IT and other workplaceservices like badging,commut er passes andgym discounts.AI SolutionCompensationPay equity, recommended salary adjustments and raisesHR Service DeliveryAI-based chatbots for routine employee questions, employeejourney assistance, process automation for HR transactions3 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New Frontier HR People Strategy 2019. hrps.org
IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESProductivityThe above ONA scenarios have the abilityto be great productivity drivers. In addition,many of today’s productivity platforms aswell as engagement tools have embeddedAI that sends nudges, action plans and tipsto help increase productivity. Domain-specific (non-HR) tools with embedded AI arealready automating routine tasks, freeingup workers for work that requires humansoft skills and strategic thinking.WellnessIn 2019 the World Health Organization declared burnout an occupational phenomenon from chronic workplace stress in itsInternational Classification of Diseases.Employers are beginning to address burnout with employee wellness programs andspending on global workplace wellbeinghas become a 48 billion market, growingat nearly 5 percent a year.New AI-powered tools track and analyze health metrics, exercise and sleep toimprove wellness, lower health care costsand prevent burnout. Other AI-poweredtools can diagnose mental health and assign psychologists or other medical practitioners.PREPARING FOR THE DISRUPTION—HOW TO GET STARTEDBringing on any new tool requires a shiftEngagement andProductivity Areain processes, organizational thinkingand role responsibilities. AI-driven toolsrequire a unique set of adjustments thatwe’ll cover here.Data Governance for AIEthics is a major consideration when you’relooking at highly personal data such as thatheld by HR. Employees need to trust thatthe data is being used for good purposes,that their privacy is protected, that thedata is secure and that it won’t be used tofurther existing bias. Following is a framework for ethics of data and AI that can helporganize your thinking and action stepsas you move forward with any AI project.PrivacyWhen employees join your company, theygive you the rights to collect a lot of data,but employers do not have the rights toexpose this data, share it or link it withpersonally identified information. According to general data protection regulation (GDPR) rules, organizations alsohave to “forget” this data if the employeeasks, so there are some important business practices to consider. Who can access this data, and have these people beentrained on privacy rules and procedures?Ethics is a majorconsideration whenyou’re looking at highlypersonal data such asthat held by HR.SecurityIs the data system and algorithm safe?AI SolutionEngagement andFeedbackPulse surveys, sentiment analysis, feedback toolsOrganizational DesignONA that identifies strong influencers, patterns of strongor weak teamwork, micro-management, nondiverse ornoninclusive communicationsProductivityTracking time spent in meetings, time wasted in unproductivemeetings, tracking of motion efficiency, e-mail usage patternsWellbeingHealth metrics, exercise, sleep, diagnosis of mental health, AIassignment of psychologists or medical practitioners4 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New Frontier HR People Strategy 2019. hrps.org
IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESA Framework for Ethics of Data and AIPeopleImpactFairnessBiasor surreptitious performance assessment?People trust the data more when they areoffered some level of transparency intothe inputs of AI and know that it isn’t being used to reinforce existing biases.Data IntegrityPrivacySecuritySafety and TrustSource: JoshBersin.comAre you protecting your employees’ confidentiality and providing security fromcyber snoops? Who has access to thisdata, and how will you audit its use andpath through the company?BiasIs the data and algorithm you’re usingfair? Does it accurately reflect the performance or productivity data you wantwithout excluding, discriminating orinadvertently biasing the results? Sinceall algorithmic systems are based onexisting data, if that data is biased, thepredictions and recommendations willbe biased. Unknown bias that creeps intothe hiring process can open companiesup to discrimination lawsuits, so it’s important to correct any biases in the algorithms and data used.People ImpactWill your people trust your use of thisdata and the recommendations the AIprovides? This entails being clear aboutyour intent for capturing and using thedata. The big question to ask is this: Whyare you implementing this particular analytics or AI tool? How will it help employees? Or is it being used for monitoringUnderlying all these issues is the collectionand maintenance of the data itself, whichcan present challenges when bringing onan AI-powered solution. Since data is theall-important factor underlying any AIbased tool, any data that goes into the toolmust be high quality. The data requirements may be different from those yourteam is used to working with. The tool mayalso need to ingest data from sources thatdon’t typically talk to each other.As you look at these solutions, be sureto consider if you can meet the data requirements. If not, decide what practicescan be put in place to collect enough datafor an AI-based tool to work effectively.Monitoring and TrainingWhile some AI-driven tools such as chatbots may already come with pre-trainedmodels, most companies will have totrain the algorithms used to achieve reliable results. Without training, an off-theshelf AI model will probably be based onassumptions that don’t quite meet yourcompany’s exact needs. HR teams have totake responsibility for understanding underlying algorithms and adapting themto the unique needs of the business andits employees. Algorithms also have tobe monitored and adjusted on a regularbasis to ensure the tools don’t return incorrect, wacky or dangerous results.When employees joinyour company, theygive you the rights tocollect a lot of data, butemployers do not havethe rights to exposethis data, share it orlink it with personallyidentified information.AI IN YOUR ORGANIZATIONBringing on AI-powered tools has the ability to lead digital transformation withinyour organization. A substantial AI project5 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New Frontier HR People Strategy 2019. hrps.org
IN FOCUSHR PEOPLE STRATEGY’S WHITE PAPER SERIESwill require you to gather cross-functionalteams to understand how to configure anduse the data. Teams should include representatives from the business unit that willuse the tools, HR and compliance staff, andIT and analytical staff.Since the point of AI is reduce humanwork by automating time-consumingprocesses, there will likely be a shift inroles and responsibilities within HR andrecruiting. Some tasks will go away orbe reduced, while other tasks related totechnology management will increase.Your HR organization will need to beupskilled along with other areas of theorganization impacted by automation.AUTHORJosh Bersin is an analyst, author, educator, andthought leader focusing on the global talent marketand the challenges and trends impacting businessworkforces around the world. Earlier this year, Joshlaunched the Josh Bersin Academy, the only professional development community for HR and talentprofessionals. Josh is the principal research partnerfor HR People Strategy.References1IDC, (2019, March 11). Worldwide Spending on Artificial Intelligence Systems Will Grow to Nearly 35.8 Billion in 2019, According to New IDCSpending Guide. Retrieved from https://www.idc.com/getdoc.jsp?containerId prUS449114192Gartner, (2018, April 25). Gartner Says GlobalArtificial Intelligence Business Value to Reach 1.2 Trillion in 2018. Retrieved from -20183Edelman, (2019, January). 2019 Edelman TrustBarometer. Retrieved from les/2019-03/2019Edelman Trust Barometer Global Report.pdf?utm source website&utm medium global report&utm campaign downloads4McKinsey, (2018, January) Retraining and reskilling workers in the age of automation. Retrievedfrom ge-of-automation5PayScale, 2019 Compensation and Benefits BestPractices: Findings From PayScale’s New Research. Retrieved from best-practices-report6Gartner, (2019, March 4). Gartner Survey Shows 37Percent of Service Leaders Are Piloting or UsingArtificial Intelligence Bots and Virtual CustomerAssistants. Retrieved from vice-leaders-ar7World Health Organization, (2019, May 28) WorldHealth Organization Mental Health. Retrievedfrom https://www.who.int/mental health/evidence/burn-out/en/8Global Wellness Institute, (2018, October) GlobalWellness Economy Monitor. Retrieved /uploads/2018/10/Research2018 v5webfinal.pdf9Deloitte, (2018, October) State of AI in the Enterprise, 2nd Edition. Retrieved from tomation-in-business-survey.htmlEVALUATING AND SELECTINGAI-POWERED TOOLSThere’s a lot of hype around AI, and it’scurrently a buzzword that companiesare latching onto for differentiation. Instead of buying AI just to be part of thetrend, consider the most pressing problems of your business and the areas withtime-consuming routine tasks and adequate data. Focus your evaluation on toolsthat can best solve these problems. As youspeak to vendors, listen carefully to makesure they understand HR-specific problems and provide answers that directlyaddress your concerns. Also look for customer references in your industry.Looking AheadThere is great potential for business returns from AI. A Deloitte survey of 1,100business leaders found that 82 percenthave gained a financial return from theirAI investments, and 88 percent plan toinvest more in AI technologies in the coming year. It is truly the wave of the future,and your company will be poised to leadthe digital transformation in the comingyears by implementing AI solutions now.6 HR People Strategy’s White Paper Series IN FOCUS AI in HR: The New Frontier HR People Strategy 2019. hrps.org
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