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How to Transform HR with AI

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implementing ai in hr

At IBM, employees turn to Myca for career advice.

She listens, scans their CVs and listed initiatives and skills, and shows them potential career paths within the company. She even points to job opportunities fitting their competence levels.

The employees trust Myca, an AI assistant.

They don’t want to settle for human advice only, largely gut-driven and subjective. Myca’s reliability stems from her access to employee data and interactions within IBM systems.

And of course, as an AI-tool she never calls in sick, clocks out early or goes on Diwali break.

A clear growth path is important for employees. Business professionals believe offering growth opportunities is the most important factor in making work fulfilling and exciting. Offering such opportunities can also boost retention efforts, according to ‘HRs as Change Agents, 2023’ report by Keka.

Thus, AI plays a strategic role in managing human resources at IBM. There are around 280 different A.I. automations for this at the company.

The most significant benefit is the hours saved. IBM’s Chief Human Resources Officer Nickle LaMoreaux told Fortune magazine that it had saved around 12,000 hours in 18 months by automating HR processes.

With the time saved, managers can focus on coaching employees and aiding their career progression, she said.

As AI technologies advance, their potential use in human resources is being explored. The key is to link such interventions with business goals and retain the ‘human’ in HR practices.

AI is an umbrella term that encompasses areas such as machine learning and cognitive computing. AI is a branch of computer science that deals with the simulation of intelligent behavior in computers. AI has been successfully used in visual perception, natural language processing, speech recognition, speech-to-text conversion, language translation, tone analysis, and other areas.

– The Business Case for AI in HR, IBM

Will AI replace HR professionals?

Before answering this, you need to visualize the ‘moon shot’ for AI in HR, which signifies a future possibility, suggests an IBM report.

For instance, a moon shot imagined by former US President John F. Kennedy in 1961 was the goal of sending a person to the moon within 10 years even when appropriate technologies didn’t exist. Yet, in 1961, the first human landed on moon.

In case of AI in HR, the moon shot could be “that employees are in complete control of their careers because AI helps their skills evolve at the same speed that technology evolves.” Moon shots are different for different organizations. But they are achievable with the right strategies.

Deloitte researchers propose reimagining work as a collaborative effort in which “humans define the problems, machines help find the solutions, and humans verify the acceptability of those solutions.”

– ‘AI for work relationships may be a great untapped opportunity’, Deloitte 

However, this doesn’t eliminate the scope of human intervention. According to ‘HRs as Change Agents, 2023’ report, every third business professional believes both AI and HR professionals will coexist. AI may even empower the HR function. Still, 20% of the professionals feel it’s premature to draw conclusions as the role of AI in HR is still being explored.

If at all any jobs are at risk, those are the transactional ones, believes IBM. “In the short-term we don’t see a lot of HR jobs going away that have not already disappeared due to technology prior to AI (e.g., the internet),” it asserts.

In a Harvard Business Review article, H. James Wilson and Paul R. Daugherty pitch ‘collaborative intelligence’, a paradigm where both humans and machines work together and help organizations excel.

Companies that automate their operations mainly to cut their workforces will see only short-term productivity gains

– H. James Wilson and  Paul R. Daugherty in Harvard Business Review

Their research suggests that the biggest performance improvements for companies are realized when humans and smart machines work together.

“People need to train AI agents, explain their outputs, and make sure they are used responsibly. AI agents, in turn, can assist people with information gathering, data crunching, routine customer service, and physical labor, thereby freeing them for higher-level tasks that require leadership, creative thinking, judgment, and other human skills,” write the authors.

perceptions about the role of ai in hr

Source: HRs as Change Agents, 2023, Keka

Therefore, implementing AI technologies will in fact require humans, those who can work at the intersection of the human-machine interface. And AI technologies will free HR professionals from administrative tasks so that they can focus on becoming strategic and business decision-makers.  

Industry experts, who took part in Keka’s ‘HR Katalyst’, a two-day online summit in June, 2023, attest to this.  

Ashish Mittal, Group Chief Human Resources Officer, Sreenidhi Educational Group,  

AI is not meant to replace the HR professional. It is meant to support and enable the HR. In HR processes, human errors are significant. AI can work on predefined rules and deliver consistent answers. If routine tasks are taken over by AI, HRs can focus on more strategic issues.  

Yashika Kaushal, Director – Global Head Talent, Learning & DEI, OpSec Group 

As organizations, we need to reflect on areas requiring automation and skills we want AI to work on. Automation can help more in transactions but not driving transformations.

In addition, some enterprises that are using intelligence automation (IA) are achieving an ROI of 200% or more, primarily owing to improved productivity, suggests an Everest Group study.  

“…the impact of IA on reducing jobs is highly exaggerated, so enterprises should not view IA’s primary benefit as being headcount reduction,” suggests the study.  

 

Benefits of using AI in HR 

As many as 64% of people would trust a robot more than their manager and half have turned to a robot instead of their manager for advice.

– Oracle and Future Workplace AI at Work Global Study, 2019

McKinsey & Company has identified ‘machine powered’ as among the five emerging HR operating models. 

It believes that “CHROs are looking for ways to harness the power of deep analytics, AI, and machine learning for better decision outcomes.” 

The benefits of using AI in HR are many: 

  • Improves employee experience 

By automating employee touchpoints, AI can ensure a positive employee experience. It can help analyze data on job satisfaction and engagement and identify areas needing intervention. By 2025, 50% of knowledge workers will use a virtual assistant on a daily basis, up from 2% in 2019, finds Gartner.  

  • Boosts learning and development  

AI technologies are being applied to deliver tailor-made development programs based on systemic information such as employee skills, training needs and possible career paths.  

  • Aligning HR strategies to business goals

 Linkages leveraged by AI can help align efforts across the length and breadth of organizations. It can help track progress of HR efforts in relation to achieving business objectives, thereby advancing the role of HRs as business partners.  

  • Improving engagement and retention 

AI analytics, including sentiment analysis, can identify how an employee is feeling, explains SAP. “It can predict the level of an employee’s engagement, burnout, depression, and anxiety – allowing for early, customized intervention,” it suggests.  

  • Saving time on repetitive tasks 

By automating administrative and repetitive tasks, AI can empower the HR to focus more on strategic tasks. Research from Hibob has suggested that the average HR manager spends 38 days a year sorting through spreadsheets and struggling with data sources.  AI tools can alleviate this condition.  

  • Improving emotional intelligence 

The implementation of emotion AI tools can help understand emotions better, suggests an MIT Sloan article. The tools gauge emotional reactions to different situations and provide recommendations.  

  • Boosting workplace diversity

Diversity at the workplace starts with making hiring fair. A Deloitte paper suggests AI can enable ‘blind hiring’, that is removing identifiable attributes from resumes unrelated to the candidate’s competence. This can remove human bias. Further, AI tools can provide insights into representation at workplace and suggest ways to make it inclusive.

How is AI used in HR (Examples)

Organizations are eager to reap the benefits of AI in people management. For business professionals, the priority areas for implementing AI in HR are going to be administrative tasks (27%) and candidate sourcing and screening (20%), according to ‘HRs as Change Agents,2023’ report.  

Currently, many companies are deploying AI across different phases of the employee lifecycle. Here are a few examples of them:  

  • Attracting and recruiting talent

Use case: AI can help automate repetitive tasks such as screening resumes, scheduling interviews or sending out mails to candidates. It can also help candidates find suitable jobs based on their experience, interests and skills. Even for assessments, AI can be deployed.  

Example: Unilever uses AI to screen job candidates. This is done by letting AI analyze candidate interviews and determine suitability for the role based on facial expressions, voice tone and word choice.  

Onboarding 

Use case: AI can help personalize onboarding experience of employees, providing them with tailor-made information based on their needs. It can provide real-time support to employees. This can keep new employees more engaged, reducing the burden on HR professionals. Further, AI can be used to track onboarding of candidates.  

Example: IBM has developed a virtual assistant to guide new employees. It answers questions about company policies, benefits and even helps employees navigate the office space.  

priority areas for future use of ai

Source: HRs as Change Agents, 2023, Keka

  • Performance management 

Use case: AI-backed technologies can process data from various sources, including performance metrics, project outcomes, customer feedback and praises by colleagues. This can enable evidence-backed performance review. Some AI tools also help in providing real-time feedback to employees. 

And as for employees requiring upskilling, AI can suggest personalized development plans to improve performance. AI can also aid succession planning by suggesting potential leaders based on their past performance.  

Example: Accenture’s ‘Performance Achievement’ tool aids managers in providing employee feedback. It parses employee surveys, performance reviews and project outcomes to suggest areas of improvement.  

  • Employee engagement 

Use case: AI can be deployed to conduct sentiment analysis and study several pulse surveys to identify areas needing action. Chatbots can aid employees in seeking support and guidance on company processes. Further, AI can facilitate a data-backed rewards and recognition system. Also, it can foster team building and knowledge sharing as well as suggest ways to improve work-life balance. Gamification of employee experience to spread awareness on policies or company goals is another use.  

Example: Deloitte has developed ConnectMe which provides employees personalized learning-related guidance. It connects employees with peers, experts and coaches for guidance. Further, it rewards employees with badges and certificates.  

  • Retention 

Use case: Through predictive analysis, AI tools can help identify early signs of attrition by analyzing engagement levels and sentiment analysis. AI can facilitate continuous feedback and support in addition to well-being support to make employees feel valued. AI can also help employees visualize clear career paths. It can help identify cultural elements inhibiting an inclusive space and can offer insights into why people quit based on analysis of exit interviews. 

Example: Credit Suisse deployed an AI tool to predict who might quit the firm. It could identify the reasons for it, which were conveyed to managers, who in turn tried reducing turnover risk factors. The program helped the company save around $ 70,000,000 a year, reports the Wall Street Journal.  

  • Learning and Development  

Use case: AI can make learning adaptive for employees, depending on their learning capacities. It can also facilitate AI mentors who can clear doubts. Certain tools can be used to suggest learning modules required for suggested career paths.  

Example: Google’s AI-backed tool ;My Learning Journey’ lets employees identify the skills they need to progress in their careers. It provides them with a personalized learning path to acquire those skills.  

  • Driving innovation and managing change  

Use case: By studying the ‘digital exhaust’ of employees, their digital trail on department communication channels, AI can help leaders identify networks and relationships. This is called relational analytics. They can leverage this knowledge to form innovative, diverse teams and improve change acceptance.  

Example: General Motors analyzed connections among employees to identify influencers from different teams who had innovative ideas. They then brought them together along with other interested employees to design better products. 

Step-by-step model to implement artificial intelligence in workforce management 

IBM and World Economic Forum (WEF) have both, in separate reports, suggested measures to implement artificial intelligence in human resources management. These incremental steps are:  

Step 1: Form representative assessment team 

The decision-making process to consider the adoption of AI-based HR tools should involve multiple parties from an early state, suggests the WEF. You must involve:  

  1. Subject matter experts 
  2. Organization leadership 
  3. HR department  
  4. Employee representatives  
  5. IT team  
  6. Legal team  

Step 2:  Identify business case 

The problem you’re planning to solve using AI must require improved insights, information and data. Having a business case will help you define the right structure and strategies for AI implementation and focus on specific problems.  

You may also develop an AI policy or set of principles. An example of a principle, suggests the WEF, could be the commitment to use AI to augment rather than replace workers.  

IBM suggests that the business case should specify the minimum viable product (MVP) and how you will work with your sponsors to define the MVP. 

Step 3: Buy tool or build it? 

This depends on resources and time availability with an organization and the conviction of the leadership. In case your organization is new to AI, you may rely on external time-tested solutions.  

For in-house development, you may employee-source ideas. For instance, IBM’s Watson Career Coach is a result of ideas generated by employees who suggested different AI applications.  

Step 4: Identify skills levels 

IBM explains that AI implementation in HR requires two kinds of skills, that is, development-related, if you are creating a tool on your own, and those relating to implementation.  

In case of implementation, “AI expertise is not required, but an analytical approach is needed. Also needed are good hypothesis forming skills, and the experience to ask questions such as where the data came from, who trained the AI application, what their motives are, and whether it is appropriate to use the data in the way intended.” 

Step 5: Pick tool fitting organization needs  

The tool should be designed well and be able to resolve the problems you need it for. Your team should be capable enough to implement it. But in case of skills gap, you should be ready to train your teams. WEF advises background and expertise checks of developers since creators strongly influence the creation of AI tools.  

Most early adopters face an AI skills gap and are looking for expertise to boost their capabilities, according to a Deloitte report. Among those surveyed, 68% executives report a moderate-to-extreme skills gap while 27% rate their skills gap as “major” or “extreme.  

People analytics expert Josh Bersin believes today’s HR tech vendors fall in three categories with respect to AI integration: those who are completely AI-centric in their approach (often led by PhD AI engineers and scientists); those who are adding AI “features” to their existing systems; and those who are not sure what to do.  

While examining an artificial intelligence tool for HR, you may consider the following assessment questions or checklist:

  1. Which HR processes can the AI tool be used for?
  2. Can the tool be integrated easily with existing HR systems?
  3. Does the tool foster transparency?
  4. How well does the tool handle data security and privacy?
  5. What capabilities are required to implement the tool?
  6. What is the reliability of the tool’s assessments and predictions?
  7. Does the tool developer offer reliable support?
  8. What is the cost of the tool and the implementation timeline?
  9. Can the tool be customized to suit the organization’s needs?
  10. Is the tool compliant with laws?
  11. Does the tool require a separate governance framework at your organization?
  12. Are there testimonials or case studies of other organizations having implemented the tool?
  13. What is the return on investment in implementing the tool?

You may also consider the risk levels of tools by considering the following areas, as suggested by WEF:  

  1. The tool’s intended use  
  2. Its potential for misuse (intentionally or unintentionally) or misunderstanding  
  3. How it might change surrounding behaviors, including attempts to game the system 
  4. The consequences for both the organization and individuals if the tool fails to perform as expected or provides false predictions  
  5. The consequences if people start over-relying on this tool  
  6. The risks involved with how the organization is currently completing the task and how adopting the tool might change this.  

With the AI’s adoption in HR, Bersin believes the thrust should still be on ‘Systemic HR’. This means “understanding the role of skills, culture, diversity, pay, and other factors on improvements in hiring, development, internal mobility, job design, productivity, and growth.” 

Step 6: Implement tool  

You may roll-out the tool phase-wise. Provide the necessary training to tool users and specify how to act on outputs generated by the tool outputs. Also highlight areas where human input is essential. You should involve employees in the decision-making process relating to the tool implementation from the beginning, so that it doesn’t appear as imposed.  

Step 7: Audit, finetune implementation 

After the implementation, track the tool’s progress on achieving desired outcomes. Carry out changes to the implementation strategy, if needed. Take employee and users feedback on the implementation. Facilitating third-party audits can boost transparency, trust and robustness.  

List of AI tools for use in HR 

There are several artificial intelligence tools that may be used for different phases of the employee lifecycle: 

  • Recruitment and onboarding 

Keka HR: The SME HR Tech leader has integrated with Open AI to enable recruiters generate job descriptions. This will free them from the repetitive task.  

Recruiters can specify the designation, the role and the required years of experience on the Keka Hire module and generate job descriptions in a few seconds.  

Using keka AI for job descriptions
Mya: It can be used to screen candidates, engage with them by answering their questions and schedule interviews.  

HireEZ: IT helps find candidates faster by sourcing them from different groups. It also automates interview scheduling and offers email templates.  

  • Learning and development  

Interflexion: It is a role-play application which aids professionals develop leadership and interpersonal skills. The platform offers practice sessions and personalized feedback. 

Coach Marlee: This tool helps individuals and teams set goals and guides them to achieve them. Through 5-10 minutes sessions, the tool determines actions required for the achievement, creates accountability and lets participants see obstacles.  

  • Performance Management 

Keka: The SME HR tech leader is offering users personalized goal-setting using AI. This may boost their performance and help them align their work with organizational goals.  

Individuals can specify the designation, the role and the period for which they wish to pick goals. A list of possible goals they may choose from is generated.  And employees may pick SMART goals from these. 

Keka AI for individual goal setting

MgrWorkbench.ai: It speeds up and simplifies some of the business-writing tasks such as writing performance reviews, development plans and business letters. 

  • Employee Engagement 

Leena AI: This virtual assistant can be used to answer employee questions, resolve issues, and provide support. It brings the HR helpdesk on a single interface. It can also be used to collect feedback from employees and identify areas where they need more support. The tool can be used to conduct sentiment analysis and secure actionable insights.  

Erudit AI: This tool mines business communications to provide anonymous, aggregated workforce sentiment and insights. This is done without relying on surveys.  

Viva Glint: The Microsoft tool can help conduct surveys. It offers an interactive dashboard to deliver a visual breakdown of trends and results. It also embodies predictive analytics to identify business risks.  

  • Employee experience 

SoWork Digital Workplace: The tool allows you to create a virtual office space. More useful for remote workers, the tool may facilitate better employee collaboration and integration with company culture.  

  • Inclusion 

Dost for inclusive messaging: The tool, designed for Slack and Teams, helps teams communicate respectfully and promotes diversity and inclusion in digital conversations. 

  • Employee retention 

Obviously.ai: This can help predict which employees are at the risk of leaving a company and facilitates closer engagement with them.  

Retention.Ai: This tool claims it can help forecast how many people are going to leave an organization in the next 30, 60 or 90 days. 

Challenges in using AI in HR 

There are many risks and challenges associated with the use of AI in people management.

More than 90% of business professionals are concerned about the ethical implications of using AI in HR, found Keka’s ‘HRs as Change Agents, 2023’ report.

Yet, they can be overcome through various interventions: 

1. Bias 

According to the ‘Human-Centred Artificial Intelligence for Human Resources’ report, there are various ways in which bias enters AI algorithms such as non-representative training data, imperfect measures and real-world biases.  

In the case of non-representative training data, algorithms may be biased towards certain groups when the data used to train them are not representative of the population of users.  

The report cites the case of Amazon, which shut down its AI hiring tool as it favored men. The training data was based on its past employees, who were mostly men.  

Mitigation strategy: Define what is ‘fair’ and ‘bias’ first. Then proceed with testing for bias in the AI tool before its rollout. After the implementation, monitor progress and track outcomes. You must also invest in systems that optimize for both fairness and accuracy, avoiding a tradeoff, as Harvard Business Review suggests.

2. Data Privacy and Security 

Using AI tools poses two risks, says World Economic Forum (WEF): reputational and legal. On the reputational front, if a tool is perceived as violating privacy, it may breach trust between employees and employer. It may also damage the company’s reputation.  

There is also the legal risk of violating regulations such as the General Data Protection Regulation (GDPR) and EU’s Ethics Guidelines for Trustworthy AI.  

Mitigation Strategy: Secure the consent of those involved in AI use and justify the ‘legitimate use’ of data. Set up a data governance framework to protect user data. Anonymize data and follow ‘minimization’, limiting data to the extent required only.

In addition, researchers Tomas Chamorro-Premuzic, Frida Polli and Ben Dattner in the Harvard Business Review article believe AI systems should be designed to predict and explain “causation,” not just find “correlation.”

3. Transparency

This should involve the awareness of AI use among the parties involved. “They should be provided with information about the data collected, how the tool works, and how the output will be used,” says WEF.

IBM’s factsheets on AI use

In a bid to boost transparency, IBM makes available to its employees factsheets explaining the deployment of AI tools, covering their lifecycle. This can help users understand how the model captures data and reaches a decision.

Retaining ‘Human’ in HR with AI use

Despite the efficient use of artificial intelligence in HR, some elements of managing human resources are believed to be better performed by humans. These include empathy, creative decision-making and emotional intelligence.

Thus, retaining the ‘human’ in HR while implementing AI in HR is essential. This is especially important for high-stakes decisions, which merit human intervention.

Professionals tend to prefer to take “recommendations” from AI—not instructions. As such, it’s important to make it clear in the social AI user interface that the application is playing the role of a coach or buddy and not that of a gatekeeper or enforcer.

– ‘AI for work relationships may be a great untapped opportunity’, Deloitte

As per World Economic Forum (WEF), there are two extreme trends relating to AI use in HR management. While on the one hand there are those who accept recommendations of AI tools unquestionably, on the other there are those who fear and mistrust them.

Keeping humans incharge of AI tools requires three approaches, believes the WEF:

  1. Involve multiple stakeholders and equip them with the necessary skills.
  2. Provide a balanced understanding of AI tools.
  3. Establish an organizational infrastructure

If you want to experience the transformative power of AI in HR for free, click here

FAQs 

1. What is the application of AI in human resource management? 

Artificial intelligence can be applied to various aspects of the employee lifecycle, from hiring to retiring. It is being used to screen better candidates, improve performance management, retain employees and even foster suitable company cultures. 

2. Is AI going to replace HRs and should they be worried? 

Survey results in Keka’s ‘HRs as Change Agents,2023’ report reveal that 75% of the business professionals believe both AI and HRs will coexist. AI will complement and empower the role of HRs. Yet professionals need to train themselves to use AI responsibly and for meeting business outcomes.  

3. How to choose the right AI tool for workforce management? 

Pick a tool that fits your organization’s business needs, has a return-on-investment and is configurable. Make sure the AI tool protects data, privacy and is legally compliant. It should also be easy to set up and scale, requiring minimal technical expertise of users. Insights generated from the tool should be actionable.  

4. What are the ethical challenges posed by AI use in HR? How can I overcome them? 

The application of artificial intelligence in people management poses the challenges of fairness and bias, discrimination, data privacy, surveillance, consent and transparency. To deal with them, organizations can start by involving all stakeholders, including employees, in the AI implementation process. Special attention must be paid to training AI algorithms using representative data. For high-stakes decisions, human input on AI-based recommendations must be the norm.   

5. What are the benefits of using artificial intelligence in HR? 

There are many. It can help improve the employee experience by automating people processes to remove time-taking administrative hurdles and gut-led decisions. AI can also help align the workforce to business goals. It saves HRs time and effort, freeing them from repetitive tasks, so they can focus on a strategic role.  

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    Meet the author

    Sidharth Yadav

    Storiesssssssss…Ah! That was a long one. I am already high. Pass me the wordstray please. I need to stub my thoughts.  A chainwriter. A stash of wit is found on me, always. Rolling Tones of sentences to suit your taste. Sniffing books for inspiration. The only addiction I ain’t giving up. And it’s natural.

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