From cost savings to improved performance, AI has had a significant impact on every aspect of HR. In this article, we will explore how AI-powered tools are increasing efficiency in hiring processes, improving employee satisfaction, enhancing data analysis, streamlining onboarding and training, and reducing bias and discrimination. You will also learn about the challenges that AI brings, and read about successful examples of implementing AI in HR.
Artificial intelligence (AI) in human resources (HR) is defined as the use of cognitive technologies and advanced statistical models to improve employee management by introducing automation, improving decisions, and reducing reliance on human HR executives.
The adoption of AI in HR is soaring, spurred by employee demand for richer workplace experiences on one hand and organizational goals to drive profitability on the other. AI technologies like chatbots, recommendation engines, and data dashboards are becoming increasingly commonplace in modern workplaces – and that’s great news for all.
Here are some of the benefits of AI in HR before we discuss its many applications.
Benefits of AI in HR
There are several reasons to use artificial intelligence in HR management, from efficiency to better decision-making. Here are some of the major benefits to implement AI in HR:
Increased efficiency in the recruitment and hiring process
AI-based recruiting tools are a vital component in any HR technology toolkit. When closely integrated with the applicant tracking system (ATS), they add a talent intelligence layer to the recruiting process, automating the screening of countless resumes and reducing time-consuming manual tasks.
AI recruitment software also utilizes the abundance of data in the ATS to generate findings about your talent pool. Further, blind screening means there's no unintentional bias locked into the hiring process – and the insights gleaned from past hires will refine the process as a whole.
Recruiter chatbots can also enable interactions with candidates in real-time. They can ask questions based on job specifications and share feedback, notifications, and recommendations for the next stage, all of which improve candidate experiences.
Improved employee engagement and satisfaction
AI not only enhances employee satisfaction and efficiency; it also lets you meet the remote and onsite demands of your employees. For instance, you can streamline everyday tasks like sharing feedback or rewarding employees. Moreover, automatic event scheduling decreases the workload of your HR department.
AI can also use pre-existing employee data to deliver better recommendations for upskilling, thereby sustaining employee engagement. It can predictively match individuals with appropriate career advancement opportunities where they'd be happier, like shifting roles or divisions
AI analytics brings greater insights into staff expectations and facilitates proactive employee dissatisfaction mitigation – at a pan-enterprise level – before it can lead to attrition.
Enhanced data analysis for better decision-making
People analytics transforms disparate information sources from across the company into actionable insights that optimize your talent strategy. People analytics become even more potent and accurate when powered by AI, enabling HR executives to foresee workforce issues and leverage talent opportunities.
The greatest aspect of AI-driven information systems is that multiple evaluations are possible. Variables can be adjusted to predict the many possible outcomes of an action. Let's say that the data indicates that your most standout achievers feel disengaged. AI in HR lets you assess the impact of promotions and learning initiatives on metrics like engagement and attrition.
Using AI also allows managers to make more informed choices regarding their style of leadership and how they can encourage their teams. When supervisors have insights based on data about their team members, they can be far more tactical when it comes to improving performance, development of skills, and career planning.
Streamlined onboarding and training processes
New recruit training is a complex framework involving multiple individuals, departments, and organizational processes. This isn't just a labor-intensive activity, but it also requires a lot of paperwork.
Using AI, businesses can more efficiently gather, organize, segment, and interpret data on new employees. It can integrate with a digital documentation workflow to keep the whole process paperless. Moreover, AI can modify the induction process by sending carefully crafted messages. It correlates the new employee's core personality type with those of current staff members to determine the best onboarding partner according to their role.
From introductory events to training sessions and logging into accounts, an assortment of matters need to be addressed thoroughly on Day 1. You can automate the onboarding protocols with AI to make it simpler for the new employee to comply with (and for you to monitor progress).
This makes onboarding much more streamlined.
HR is then in charge of employee training shortly after a successful induction. AI helps with this process.
AI-based tools for training leverage its adaptive machine-learning capacities to acquire and evaluate data on the learners' preferences. This lets it constantly modify the training to meet the expectations of the participants. This degree of customization empowers new employees to take charge of their skill development. Individuals can set their very own targets, pace, and learning methodology, which increases completion rates.
This can also be advantageous for neurodiverse employees, who may have trouble with conventional approaches to learning, specifically recalling auditory and written content.
Reduction in bias and discrimination
Usually, recruitment or appraisal processes can't be totally objective because of the undeniable element of human bias. AI eliminates all discrimination and preconceived notions that individual reviewers might bring to the table.
It evaluates a candidate based on their proficiency and skill sets, whereas, in a manual-only system, a candidate's or employee's race, gender, caste, ethnic background, or socioeconomic status may at times influence or color the decision-making process.
AI writing tools can also assist HR executives in creating reliable and tonally uniform material that's impartial (like establishing business guidelines or job postings). You could use AI to detect biases/discrimination in the workplace and notify HR, initiating steps that ameliorate the adverse impacts (limiting legal accountability for discriminatory actions).
However, keep in mind AI may have biases of its own that creep in due to training data errors or programming flaws. This is a vital consideration when you introduce AI into your culture of diversity, equity, and inclusion (DEI).
Learn More: Is HR ready for AI?
Applications of AI in HR
Given its incredible versatility, it can be difficult to know how AI can be used in HR processes in your company and where you should begin. Fortunately, there are some quick wins you can target. Companies globally are achieving positive outcomes by deploying HR for:
Resume screening and candidate shortlisting
The goal of hiring managers is to employ the most qualified candidates as soon as practicable. Nevertheless, one of the most common complaints from job applicants is that the recruiting process is too lengthy. By using AI to assess and select the most qualified candidates faster, the entire process becomes easier for all parties.
It can even identify individuals who may not have applied for the position but have the necessary skills and qualifications. It can effectively sift through large quantities of resumes, aligning job postings with applicants' qualifications and experience.
AI can employ predictive analytics to examine candidate data, such as resumes, social media accounts, and online behavior, in order to forecast which applicants are most likely to succeed in the role. Video interviewing tools enabled by artificial intelligence can be put to use for pre-screening interviews, saving time and costs, across the end-to-end shortlisting process.
And, as we previously mentioned, AI-powered resume assessment can decrease unintentional bias in the recruiting process. By masking names and other personally identifiable data contained in resumes, AI will assist recruiters in staying on track and focusing on the candidate's skills and qualifications.
Chatbots for employee support and FAQs
As per research, workers spend eight hours weekly, carrying out ineffectual tasks in search of answers to their questions. A conversational AI bot fundamentally changes this situation by providing employees prompt, 24/7 support.
Imagine the employee wishes to learn about the various worker guidelines in effect. Instead of setting up a call with HR or going through a stack of records, they only need to pose the query to a conversational AI chatbot. It processes the request, retrieves the data, and presents the response in a matter of seconds.
Occasionally, the leadership team is interested in learning what types of queries employees have so that they can design appropriate workplace experiences. The conversational AI device can automatically generate management reports.
Lastly, AI in HR will work with other online resources when replying to employee FAQs. This enables data synchronization and optimizes output, since workflows across access management, collaboration, email, documents, and expense management are now connected.
Predictive analytics for employee performance evaluation
Artificial intelligence-based predictive analytics can play an important role in performance evaluations and improvements.
It analyzes immense quantities of employee performance-related data, including key performance indicators (KPIs), personal goals, suggestions, and past information. Then, it generates correlations, trends, and patterns inside the data to provide useful insights for executives and staff members.
If the AI finds a decline in activity or other discrepancies in performance, it immediately notifies the employee's superior of the imminent challenge. Even when there are no apparent shifts in the performance of the workforce, it continues to analyze all activity and compare this against various behavior patterns.
By correlating historical performance information with the data from workers who eventually left the company, AI can figure out if anyone else is heading down that same route. With these evaluations, it's possible to find employees who are on the brink of resigning, even if what they're doing now is satisfactory.
This lets administrators resolve performance issues proactively before they can happen, thanks to AI in HR. This is because the technology can determine the factors that influence high levels of performance and anticipate the odds of achieving predetermined targets.
Virtual reality for remote onboarding and training
While virtual reality (VR) may be unrelated to artificial intelligence on the surface, it is a key trend that HR teams must know – and aim to implement. VR can solve several of the problems that AI analytics detect, like low engagement, poor learning retention, and difficulties in onboarding.
With the help of virtual reality, you can recreate a real-world setting and let new employees rehearse processes until they are comfortable. In the real world, where everything alters depending on the learner's actions, VR fosters that essential repetition factor. This significantly enhances training outcomes.
Another incentive for using virtual reality for induction is that learners can make mistakes when using VR without placing themselves or others at risk or inflicting damage to materials and equipment and not when they are actually engaged in a task.
VR can also be used to train employees in the interpersonal skills that will be needed as they progress in their careers. Virtual reality (VR) training can help prepare workers for challenging circumstances wherein there is more than one right way to act, but they still have to conform to the company's values or guidelines.
Therefore, virtual reality is a necessary complement to AI if you want to close skill gaps or act on the talent opportunities you discover through analysis.
Sentiment analysis for employee feedback and sentiment tracking
Engagement surveys that ask for spontaneous answers produce enormous quantities of emotional or sentiment-charged responses. But it soon becomes impractical to read each item of open-ended suggestions, let alone react to it. Further, a manual review always has a chance of introducing bias into an assessment.
An AI-led sentiment analytics platform employs machine learning to understand the feelings in the text. As patterns are recognized, each employee observation or input can be labeled with the pertinent theme or emotion — for instance, favorable, unfavorable, or indifferent. The algorithms carry out mundane tasks, which include perusing qualitative comments and sorting remarks into different groups with corresponding keywords.
Additionally, AI enables HR to gauge employee emotions with more accuracy.
A basic automation tool, for instance, would designate both perplexity and anxiety as "negative." This fails to help HR departments in enhancing employee engagement or satisfaction with work. Sentiment analytics powered by AI can correlate employees' misunderstandings about their perks with their worries about pay equity. This facilitates the resolution of actual business problems.
Challenges and Considerations of Implementing AI in HR
Despite these compelling benefits and so many powerful applications, it isn’t enough to only know how to use AI in HR. Organizations also need to be aware of and judiciously navigate the challenges of using AI in HR management. These include:
Data privacy and security concerns
Large datasets are used to educate and optimize AI algorithms. This often involves sensitive employee data. An AI-powered talent analytics framework, for instance, requires permission to view staff compensation and performance documentation, which, if breached, could have serious consequences for the worker and the organization.
Likewise, AI-driven systems introduce new vulnerabilities that might be exploited by malicious actors, resulting in data theft and the disclosure of sensitive employee information to unknown individuals. A data intrusion in an employee benefits platform driven by artificial intelligence could reveal employees' financial data, leading to identity fraud or financial misconduct.
That is why HR teams need to collaborate with IT to put in place security measures that safeguard private employee information at rest and in motion. Establish a data minimization plan by accumulating and storing only the data needed by AI algorithms, thereby containing the possible impacts of a data breach.
As part of regular training programs, inform employees about the use of AI in HR, the information that is being gathered, and the safeguards for confidentiality in action. Execute routine safety audits and risk evaluations to detect AI system and HR database vulnerabilities and gaps.
Ethical considerations and potential bias in AI algorithms
AI tools can inadvertently introduce discrimination and prejudice into HR processes if they aren't carefully selected and managed. Incorrect discrimination against certain groups may result from the use of skewed training data or defective algorithms.
Additionally, it may perpetuate discriminatory HR practices. For instance, if the AI identifies an arrangement in which a recruiting firm can make the majority of its earnings by matching candidates within existing biased frameworks -– such as only higher education or socioeconomic standing -– then this will be the case.
Several AI algorithms are, unfortunately, only refined "black boxes," making it challenging to figure out how decisions are made. This opaqueness can erode confidence in artificial intelligence systems and hinder the ability of stakeholders to challenge or mitigate potential biases.
Further, there is a possibility that the use of AI in human resources could reduce human contact and empathy, leading to a highly mechanized and deracinated experience for job applicants, especially those from minority backgrounds.
Organizations must employ post-hoc equality & fairness testing so as to assess the effects of AI decisions on various demographic groups and adjust their algorithms accordingly.
Equal Employment Opportunity (EEO) laws are equally important as they mandate fair treatment of candidates, banning prejudice against legally protected characteristics such as racial or ethnic origin, age, gender, and disability. Organizations must choose AI tools that adhere to these laws, ensuring that algorithms are not perpetuating bias or generating discriminatory outcomes.
Integration and compatibility with existing HR systems
AI relies largely on data. Confirm that your human resources records are precise, current, and thorough to optimize the efficacy of AI models. Businesses with a very small team or no previous data-capturing systems may have problems launching their AI in HR initiatives.
Also, you have to make sure that AI in HR solutions can integrate seamlessly with your current HR systems. Compatibility and data transmission are essential for AI to do its job.
Harmonizing data from multiple sources can lead to disparities, discrepancies, and errors. Therefore, data cleansing and processing is a crucial task that requires substantial effort and time. Failure to fix data quality issues may culminate in skewed AI models and erroneous outcomes.
Factor this into the vendor selection process – check for open application programming interfaces (APIs) and pre-built connectors that will actually allow AI to fetch, ingest, and process the data it needs.
Integrating AI into your training program requires significantly more than, for example, installing a few modules on your LMS. You need to take additional time to find out if you have the required storage spaces. processing units, and infrastructure for the system to run effectively. Meanwhile, your staff members must be directed to use these new tools, resolve basic issues, and inform you whenever the AI algorithm is malfunctioning.
Evaluate the scalability of AI solutions as your business expands. It is important to select versatile platforms and extensible algorithms that can adapt to changing HR requirements.
Employee resistance and fear of job displacement
As HR departments rush to adopt AI, they frequently face a formidable obstacle: resistance from staff members. This can originate from apprehensions regarding employment displacement or an absence of experience with AI technologies.
While artificial intelligence in human resources offers greater efficiency, less human error, and greater convenience, it can cause apprehensions among long-time employees. Many feel that AI will take over their jobs, compelling them to acquire new skills or seek out other opportunities. Some worry that it'll be too difficult to use or manage these AI-powered machines. In many cases, it is simply the issue of a culture shift.
Resistance can not only hold back AI outcomes, but it can also stymie organizational growth as a whole. Individuals who are unhappy with artificial intelligence might be less productive. If employees don't fully engage with these tools, key insights from AI analytics might remain unexplored. A climate of resistance inhibits creativity, as workers hesitate to suggest AI-driven solutions.
Throughout the implementation process, HR specialists need to adopt a proactive stance to change management and guarantee efficient communication, training, and support. Training courses can demystify uncertainties around AI and prepare employees to make the best use of these technologies. Offering accreditation or incentives for the learning of AI skills will also encourage participation.
HR must also reiterate that AI was created to augment human responsibilities, not replace them. Sharing actual instances of AI-driven breakthroughs will help alleviate this atmosphere of dread and anxiety. This encourages confidence and highlights the tangible benefits associated with AI.
Continuous monitoring and updating of AI systems
AI models are trained on large datasets, and as new data is generated, the system needs to be continuously monitored to ensure it remains accurate and unbiased. This requires ongoing efforts and resources to collect, label, and validate data.
Further, AI models can suffer from algorithmic bias, which can perpetuate discrimination or unfairness in HR processes. Regular monitoring is necessary to identify and address any biases that may arise, requiring organizations to invest in robust evaluation methodologies and diverse datasets.
To resolve these challenges, organizations can implement several measures. First, they should establish a dedicated team responsible for monitoring and updating AI systems, consisting of data scientists, HR professionals, and ethicists. This team can regularly assess the performance and impact of the AI system, conduct audits, and address any biases or inaccuracies.
Next, clear guidelines and policies are necessary for AI deployment in HR. These should include regular assessments of the AI system's performance, ongoing training for HR personnel, and mechanisms for employee feedback and transparency.
You may also need to factor in the cost of infrastructure observability, as the physical systems powering AI will also need your constant attention.
Learn More: Future of AI in HR: Latest Trends and Tools
Successful Examples of AI in HR
These challenges are not holding back AI progression, however, and many companies have figured out how to use AI in HR successfully. As illustrated in these AI in HRM examples, with the right effort, investment, and strategy, you can revolutionize your people processes using artificial intelligence. So, here are four AI in HR examples to inspire you:
IBM's Watson Talent
IBM Watson Talent is a solution for talent management that powers recruiting, training and development, and various other HR functions. It seeks to locate the best applicants and eliminate bias when determining who is going to thrive within an organization. It was created on a system known as Orchestrate.
Orchestrate executes complex operations with simplicity using a mix of built-in skills, custom competencies, and application integrations. It can automate repetitive duties like posting job openings, arranging interviews, and sending follow-up communications to candidates.
HireVue's video interviewing technology
HireVue offers automated video interviews and recruiting systems. The company has carried out several million interviews and has gathered the information necessary to predict the ideal candidate for the position.
The proprietary software of HireVue helps businesses create audio recordings of candidates responding to standard interview queries. The video interview tests use artificial intelligence to collect and evaluate the candidates' recorded responses and rapidly determine if they are qualified for the position.
Textio's augmented writing platform
Textio acts as an augmented writing tool with several applications. One of these goals is to offer employers the lexicon and messaging blackbook they need to draw in candidates through language – expressions, words and phrases – exemplifying core beliefs and the broader organizational culture. Textio anticipates how your writing will fare in the race for talent and suggests tweaks to attract a more skilled and diverse applicant pool. It is an AI-powered predictive analytics engine that examines how your job posting will perform in today's labor market.
Humu's nudges for improving employee engagement
Humu is a behavioral science corporation focused on creating an artificial intelligence-based "nudge engine." It employs sophisticated nudges to improve workplace experiences. The nudge engine is an ensemble of carefully crafted guidelines, clues, tips, and recommendations that help employees make small but significant behavioral changes.
After undertaking a brief evaluation, the system gives leaders, managers, and companies a set of diagnostics that define what's working and what's not. On this basis, the push engine communicates with everybody, and not just management. The nudges are meant to go hand in hand with the leadership to holistically improve employee engagement.
To foster a sense of community at work, Humu can inspire a leader to pose a specific query about a topic that makes a worker feel valued. Employee nudges might suggest that individuals share a personal narrative in a group setting.
Learn More: 20 Examples of AI in HR You Can Learn From
Future Trends and Predictions for AI in HR
As AI in HR evolves, five key trends will shape its future. Let’s look at these in more detail:
Expansion of AI adoption in HR functions
One of the key trends shaping AI in HR is its widespread adoption across different HR functions. To begin with, most companies targeted recruitment and talent screening as one of the lowest-hanging fruits for AI in HR management. Now, it’s fast becoming clear that artificial intelligence can play a role in nearly every process that generates and consumes data.
In the future, AI will be used across the end-to-end employee lifecycle, from sourcing the best-fit passive candidates to conducting exit interviews. Just like digitization has become table stakes for HR operations worldwide, similarly AI capabilities will become ubiquitous across HR tasks in the near future.
Integration of AI with other emerging technologies
AI integration with emerging technologies like blockchain, Web3, and IoT has the potential to revolutionize HR processes in the future. Here's a breakdown of how these technologies can work together to improve HR processes:
By combining AI and blockchain, HR processes can become more efficient, secure, and transparent. AI algorithms can analyze large volumes of HR data, such as employee performance, skills, and engagement levels, to provide valuable insights for decision-making.
Blockchain can ensure the security and integrity of this data by creating an immutable and transparent HR ledger.
This can help prevent data tampering and fraud and improve data privacy. Additionally, blockchain can enable smart contracts, which automate HR processes like payroll management, benefits administration, and performance management, making them more accurate and streamlined.
Web3 technology focuses on decentralization, user privacy, and control over personal data. When integrated with AI, it can enhance HR processes in several ways. Moreover, the two technologies together can enhance security by detecting and responding to potential threats in real-time. It can identify suspicious activities, such as unauthorized access to sensitive HR data, and trigger appropriate actions to mitigate risks.
- Internet of Things (IoT)
IoT devices can collect vast amounts of data related to employee well-being, productivity, and workplace environment. AI integrations with IoT can enable HR departments to leverage this data for better decision-making.
AI algorithms can analyze IoT data to identify patterns and correlations between different variables. For example, they can determine how environmental factors (temperature, lighting, air quality) affect employee productivity and well-being. This information can help HR managers optimize the workplace environment to improve employee satisfaction and performance.
Additionally, AI-powered chatbots can interact with employees through IoT devices, providing real-time support and answering HR-related queries.
Personalization and customization of HR experiences
AI is already making employee experiences richer and more closely aligned with individual preferences and needs. In the future, the same benefits will apply to HR professionals as well, as AI-based virtual assistants make the lives of HR professionals easier at every step. For example, AI could adapt workflows based on your references. It could dynamically update dashboards based on the data you need on a particular day and the type of visualizations you find easy to understand.
Enhanced employee wellbeing and work-life balance
This particular AI trend is already in action in many workplaces. AI can play an important role in improving wellbeing by detecting red flags about employee health. For example, it can spot signals of burnout before it happens, it can detect performance anomalies, and it can alert employees when they are pulling away from social interactions too often.
AI can also enable better work-life balance by reducing employee work hours through automation. It can nudge employees to clock out after a stipulated number of hours, and, in the future, it may even be able to predict when an overwhelming workload threatens to get in the way of work-life balance.
Ethical guidelines and regulations for AI in HR
As AI continues to play an increasingly significant role in HR processes, there will be a growing need for clear ethical standards to ensure responsible and fair use.
To address concerns related to algorithmic bias and accountability, regulatory bodies and industry organizations are expected to develop specific guidelines for AI adoption in HR. These guidelines will emphasize transparency, fairness, and the mitigation of biases in AI algorithms. They may require organizations to regularly audit and monitor AI systems to ensure compliance with ethical standards.
Furthermore, regulations may focus on data privacy and security, as AI-driven HR processes often involve handling sensitive employee information. Stricter rules regarding data protection and consent are likely to be implemented to protect employees' rights and prevent misuse of personal information.
Collaboration between industry stakeholders, policymakers, and ethics bodies will be vital in shaping these guidelines and regulations. Public discussions and consultations will help establish consensus and address the challenges associated with ethical AI deployment in HR.
Bear in mind that, in the future, an AI ethics manager could become an essential role, just like a recruitment manager today.
Learn More: What Is the Impact of AI on HR?
The use of AI in HR has revolutionized the way human resources functions and benefits employees. With increased efficiency in the recruitment lifecycle, improved employee engagement and satisfaction, enhanced data analysis for better decision-making, streamlined onboarding and training processes, and reduction in bias and discrimination, AI has made a significant impact on the future of human resources.
However, it is important to consider challenges such as data privacy concerns, potential biases in algorithms, integration with existing systems, and employee resistance.
By addressing these challenges proactively through proper training and support for employees along with ethical considerations while implementing AI tools, organizations can unlock the full potential of artificial intelligence in transforming their HR practices.
It is safe to say that AI will continue to play a crucial role in shaping the future of human resources by optimizing talent management strategies and creating a more efficient workplace for all individuals involved.
Schedule a demo with Darwinbox to learn how we are using AI in HR to streamline processes and unlock value for organizations.