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AI in HR: The New Frontier INTRODUCTION The robots have arrived. Only they don’t look like robots. AI- and -based technology is embedded in the tools you likely interact with every day—navigation apps; predictive text in e-mail and messaging; digital assistants like Alexa and Siri; and recommendation engines on Netflix, YouTube and Spotify. Today, AI-powered technology seamlessly integrates 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 transform HR 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 of data on candidates and employees that can help them source, assess, hire, train, develop and pay people more efficiently with the application of AI-driven tools.

he International Data Corporation smarter hiring choices that ensure quali- T(IDC) estimates that worldwide spend- ty hires while eliminating hidden biases. ing on AI systems will reach $35.8 billion The recruiting process is filled with in 2019 and $79 billion by 2022. And Gart- numerous repeatable tasks such as re- ner estimates that, by 2022, AI-derived sume screening and interview scheduling business value will reach $3.9 trillion. that, when given to AI, free up recruiters’ With its vast amount of underutilized time to focus on what matters: the human data, HR has the potential to lead digital interaction between candidates and com- transformation and drive business value pany personnel. And that can be done at with AI-powered solutions. scale with an intelligent trained to conduct preliminary screening and RECRUITING manage the interview process. Recruiting is the most well-developed The interview process is rife with bias, area of AI in HR, for several reasons. The and many of these tools help reduce race, vast size of the recruiting funnel—from gender, education and age biases. A key job ad impressions, careers site visits, caveat is that an AI-based system can only applications and hires—offers a wealth return results as good as the data and the of data that AI-powered tools can learn training put into it. For instance, if your from. Additionally, the recent talent employee population leans toward certain shortage in a strong economy means that profiles, algorithms based on matching the NOVEMBER 2019 companies are paying closer attention to characteristics of current employees with candidate experience and investing more candidates will not help increase diversity. PRODUCED BY EXECUTIVE NETWORK in recruiting tools to improve it. Finally, However, with oversight, AI can correct HR PEOPLE STRATEGY shortening employee tenure has driven hidden biases. (See the final section of this WRITTEN BY companies to seek out ways to make paper for a discussion on the ethics of AI.) Josh Bersin

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Recruiting Process AI Solution Candidate Selection Screen candidate resumes, rediscover talent from existing pools Sourcing Surface appropriate candidates from online profiles, facilitate referrals Recruitment Marketing Automated job ad placement and bidding Screening Natural language processing (NLP) based to screen candidates, re-engage talent pools Interviewing Video interview analytics, chatbot-enabled scheduling, interview process analytics and predictions Assessment Assessments based on skills and cultural fit Diversity and Inclusion Identify and reduce bias in job descriptions, candidate communications, and interview patterns

LEARNING AND EMPLOYEE DEVELOPMENT matching, virtual reality (VR) training Talent availability, rapid technology and micro-learning help provide em- change, and shifting candidate behav- ployees with the knowledge they need ior are some of the factors contributing to succeed on the job. to companies’ increased focus on reten- Internal mobility is a growing area AI-powered tools tion through reskilling employees, pro- of focus, and some companies are hav- facilitate employee viding better learning and onboarding ing success using AI-based systems growth through that look at job experience inside and programs, and developing top employ- automated matching ees into leaders. outside the company, and match this An Edelman study found that 59 per- information against open positions, of inferred skills, cent of global employees fear job loss offering employees guidance on where recommending due to a lack of retraining and skills. they might go next. adjacent skills, and Companies that invest more in “learn- ing in the flow of work” are well poised CORE HR AND SERVICE DELIVERY serving up relevant to attract and retain employees, as well learning content. as to ensure their business stays com- Core HR petitive: 62 percent of global execu- Time tracking, payroll, expense reporting tives believe they will need to retrain and benefits administration are benefit- or replace more than a quarter of their ing from AI-powered analysis, employee workforce by 2023 due to advancing nudges and predictive capabilities. An automation and digitization. important area is compensation. AI-powered tools facilitate employee PayScale’s 2019 study of compensation growth through automated matching of practices found that less than 40 percent inferred skills, recommending adjacent of companies do any compensation eq- skills, and serving up relevant learning uity analysis for race or gender. With a content. Additionally, AI-based coach massive set of pressures facing companies

Function AI Solution Learning Learning/training matching, learning content delivery Coaching/Mentoring Coach/mentor matching Internal Mobility Skills matching and recommendations against openings

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right now for gender pay equity reporting, AI IN ENGAGEMENT, PRODUCTIVITY it’s prime time for AI-based tools to help AND WELLNESS companies determine fair pay and ensure all employees are being paid fairly. Employee Engagement and Compensation is a tricky topic because Feedback Systems there are so many objective factors that In the evolution of employee engagement should determine pay: education, experi- to employee experience, companies now ence, work responsibilities, performance consider every aspect of how an employ- ratings and market competition. AI can ee engages with his or her job, the com- help determine fair pay in a way that pany and colleagues. eliminates subjective biases like gender, The annual survey has gone by the race, age and favoritism and that identifies wayside in favor of continuous feedback potential inequities. in the form of pulse surveys and other feedback systems that can be analyzed HR Service Delivery with NLP-based tools. Such tools can sur- With the trend toward employee experi- face key themes, help diagnose manager ence, employers now have to design HR effectiveness and detect risks services relating to pay, benefits, expens- from discrimination or harassment. es and paid time off (PTO) requests for The largest employee audiences expecting consum- Organizational Network Analysis organizations have er-grade experiences in the workplace. The highly networked workplace has built employee service The largest organizations have built vast amounts of data from e-mail, calen- employee service centers and self-ser- daring, messaging platforms and motion centers and self-ser­vice vice portals that merge HR, IT and other sensors that can be fed into systems using portals that merge HR, workplace services like badging, commut- organizational network analysis (ONA). IT and other workplace er passes and gym discounts. This technology can help companies AI-based chatbots already have a foot- identify strong influencers, patterns of services like badging, hold with customer service organizations: strong or weak teamwork, micro-man- commut­er passes and 37 percent of service leaders are either pi- agement and nondiverse or noninclusive gym discounts. loting or using artificial intelligence bots communications. and virtual customer assistants (VCAs), The applications of ONA are as vast and 67 percent of those leaders believe as the data available. By analyzing time they are high-value tools in the contact spent in meetings, it can help eliminate center. time wasted in unproductive meetings. Chatbots based on natural language Analyzing the behavior of sales teams processing (NLP) have the ever-in- against performance can help identify creasing intelligence to answer routine new sales processes. Looking at motion employee questions and assist with em- patterns from embedded sensors can cre- ployee journeys, freeing up HR admin- ate more efficient processes and realistic istrators to focus on more complex tasks. guidelines based on data versus hunches.

HR Area AI Solution Compensation Pay equity, recommended salary adjustments and raises HR Service Delivery AI-based chatbots for routine employee questions, employee journey assistance, process automation for HR transactions

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Productivity in processes, organizational thinking The above ONA scenarios have the ability and role responsibilities. AI-driven tools to be great productivity drivers. In addition, require a unique set of adjustments that many of today’s productivity platforms as we’ll cover here. well as engagement tools have embedded AI that sends nudges, action plans and tips Data Governance for AI to help increase productivity. Domain-spe- Ethics is a major consideration when you’re cific (non-HR) tools with embedded AI are looking at highly personal data such as that already automating routine tasks, freeing held by HR. Employees need to trust that up workers for work that requires human the data is being used for good purposes, soft skills and strategic thinking. that their privacy is protected, that the data is secure and that it won’t be used to Wellness further existing bias. Following is a frame- In 2019 the World Health Organization de- work for ethics of data and AI that can help clared burnout an occupational phenom- organize your thinking and action steps enon from chronic workplace stress in its as you move forward with any AI project. International Classification of Diseases. Employers are beginning to address burn- Privacy out with employee wellness programs and When employees join your company, they spending on global workplace wellbeing give you the rights to collect a lot of data, has become a $48 billion market, growing but employers do not have the rights to Ethics is a major at nearly 5 percent a year. expose this data, share it or link it with consideration when personally identified information. Ac- New AI-powered tools track and ana- you’re looking at highly lyze health metrics, exercise and sleep to cording to general data protection regu- improve wellness, lower health care costs lation (GDPR) rules, organizations also personal data such as and prevent burnout. Other AI-powered have to “forget” this data if the employee that held by HR. tools can diagnose mental health and as- asks, so there are some important busi- sign psychologists or other medical prac- ness practices to consider. Who can ac- titioners. cess this data, and have these people been trained on privacy rules and procedures? PREPARING FOR THE DISRUPTION— HOW TO GET STARTED Security Bringing on any new tool requires a shift Is the data system and algorithm safe?

Engagement and AI Solution Productivity Area Engagement and Pulse surveys, , feedback tools Feedback Organizational Design ONA that identifies strong influencers, patterns of strong or weak teamwork, micro-management, nondiverse or noninclusive communications Productivity Tracking time spent in meetings, time wasted in unproductive meetings, tracking of motion efficiency, e-mail usage patterns Wellbeing Health metrics, exercise, sleep, diagnosis of mental health, AI- assignment of psychologists or medical practitioners

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or surreptitious performance assessment? A Framework for Ethics of Data and AI People trust the data more when they are offered some level of transparency into the inputs of AI and know that it isn’t be- People Bias ing used to reinforce existing biases. Impact

Data Integrity Underlying all these issues is the collection Fairness and maintenance of the data itself, which Privacy Security can present challenges when bringing on an AI-powered solution. Since data is the all-important factor underlying any AI- based tool, any data that goes into the tool Safety and Trust must be high quality. The data require- Source: JoshBersin.com ments may be different from those your team is used to working with. The tool may Are you protecting your employees’ con- also need to ingest data from sources that fidentiality and providing security from don’t typically talk to each other. cyber snoops? Who has access to this When employees join As you look at these solutions, be sure data, and how will you audit its use and to consider if you can meet the data re- your company, they path through the company? quirements. If not, decide what practices give you the rights to can be put in place to collect enough data Bias collect a lot of data, but for an AI-based tool to work effectively. Is the data and algorithm you’re using employers do not have fair? Does it accurately reflect the per- the rights to expose formance or productivity data you want Monitoring and Training While some AI-driven tools such as chat- without excluding, discriminating or this data, share it or bots may already come with pre-trained inadvertently biasing the results? Since link it with personally models, most companies will have to all algorithmic systems are based on train the algorithms used to achieve reli- identified information. existing data, if that data is biased, the able results. Without training, an off-the predictions and recommendations will shelf AI model will probably be based on be biased. Unknown bias that creeps into assumptions that don’t quite meet your the hiring process can open companies company’s exact needs. HR teams have to up to discrimination lawsuits, so it’s im- take responsibility for understanding un- portant to correct any biases in the algo- derlying algorithms and adapting them rithms and data used. to the unique needs of the business and its employees. Algorithms also have to People Impact be monitored and adjusted on a regular Will your people trust your use of this basis to ensure the tools don’t return in- data and the recommendations the AI correct, wacky or dangerous results. provides? This entails being clear about your intent for capturing and using the data. The big question to ask is this: Why AI IN YOUR ORGANIZATION Bringing on AI-powered tools has the abil- are you implementing this particular an- ity to lead digital transformation within alytics or AI tool? How will it help em- your organization. A substantial AI project ployees? Or is it being used for monitoring

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will require you to gather cross-functional AUTHOR teams to understand how to configure and Josh Bersin is an analyst, author, educator, and use the data. Teams should include repre- thought leader focusing on the global talent market sentatives from the business unit that will and the challenges and trends impacting business use the tools, HR and compliance staff, and workforces around the world. Earlier this year, Josh IT and analytical staff. launched the Josh Bersin Academy, the only profes- Since the point of AI is reduce human sional development community for HR and talent work by automating time-consuming professionals. Josh is the principal research partner processes, there will likely be a shift in for HR People + Strategy. roles and responsibilities within HR and recruiting. Some tasks will go away or References 1 IDC, (2019, March 11). Worldwide Spending on Ar- be reduced, while other tasks related to tificial Intelligence Systems Will Grow to Nearly technology management will increase. $35.8 Billion in 2019, According to New IDC Your HR organization will need to be Spending Guide. Retrieved from https://www.idc. com/getdoc.jsp?containerId=prUS44911419 upskilled along with other areas of the 2 Gartner, (2018, April 25). Gartner Says Global organization impacted by automation. Artificial Intelligence Business Value to Reach $1.2 Trillion in 2018. Retrieved from https://www. gartner.com/en/newsroom/press-releases/2018-04- EVALUATING AND SELECTING 25-gartner-says-global-artificial-intelligence-busi- AI-POWERED TOOLS ness-value-to-reach-1-point-2-trillion-in-2018 There’s a lot of hype around AI, and it’s 3 Edelman, (2019, January). 2019 Edelman Trust currently a buzzword that companies Barometer. Retrieved from https://www.edelman. are latching onto for differentiation. In- com/sites/g/files/aatuss191/files/2019-03/2019_ Edelman_Trust_Barometer_Global_Report. stead of buying AI just to be part of the pdf?utm_source=website&utm_medium=glob- trend, consider the most pressing prob- al_report&utm_campaign=downloads lems of your business and the areas with 4 McKinsey, (2018, January) Retraining and reskill- time-consuming routine tasks and ade- ing workers in the age of automation. Retrieved from https://www.mckinsey.com/featured-in- quate data. Focus your evaluation on tools sights/future-of-work/retraining-and-reskill- that can best solve these problems. As you ing-workers-in-the-age-of-automation speak to vendors, listen carefully to make 5 PayScale, 2019 Compensation and Benefits Best Practices: Findings From PayScale’s New Re- sure they understand HR-specific prob- search. Retrieved from https://www.payscale.com/ lems and provide answers that directly hr/canadian-compensation-best-practices-report address your concerns. Also look for cus- 6 Gartner, (2019, March 4). Gartner Survey Shows 37 tomer references in your industry. Percent of Service Leaders Are Piloting or Using Artificial Intelligence Bots and Virtual Customer Assistants. Retrieved from https://www.gartner. Looking Ahead com/en/newsroom/press-releases/2019-03-04-gart- There is great potential for business re- ner-survey-shows-37-percent-of-service-leaders-ar turns from AI. A Deloitte survey of 1,100 7 World Health Organization, (2019, May 28) World Health Organization Mental Health. Retrieved business leaders found that 82 percent from https://www.who.int/mental_health/evi- have gained a financial return from their dence/burn-out/en/ AI investments, and 88 percent plan to 8 Global Wellness Institute, (2018, October) Global invest more in AI technologies in the com- Wellness Economy Monitor. Retrieved from https://globalwellnessinstitute.org/wp-content/up- ing year. It is truly the wave of the future, loads/2018/10/Research2018_v5webfinal.pdf and your company will be poised to lead 9 Deloitte, (2018, October) State of AI in the Enter- the digital transformation in the coming prise, 2nd Edition. Retrieved from https://www2. years by implementing AI solutions now. deloitte.com/us/en/insights/focus/cognitive-tech- nologies/state-of-ai-and-intelligent-automa- tion-in-business-survey.html

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