AI in HR: Streamlining Recruitment, Employee Engagement, and Performance Management

The rapid development of Artificial Intelligence is opening up completely new possibilities in the Human Resources sector. Recent Gartner research on HR Technology shows that 76% of HR leaders agree they will be lagging in organizational success if they don’t adopt and implement generative AI in the next 12 to 24 months.

The possibilities of AI technology to optimize HR systems are limitless in making HR management easier, faster, and more objective. Algorithms are already used in applicant selection, personnel engagement, and performance management.

According to SHRM (the Society for Human Resource Management):

• Approximately 25% of organizations utilize automation or AI to assist with HR-related tasks.
• 85% of employers using automation or AI say it saves time and/or increases efficiency.
• 64% of HR professionals say their organization's automation or AI tools automatically filter out unqualified applicants.
• Over 2 in 3 HR professionals say the number of applications they must manually review is somewhat (44%) or much better (24%) due to their use of automation or AI.
• 92% of organizations that use automation or AI source some or all of these tools directly from a vendor.
• 19% of organizations that use automation or AI have experienced those tools accidentally overlooking or excluding qualified applicants or employees.

From acquiring talent to employee development, machine intelligence delivers productive processes, precise decisions, and a better staff experience.

Transforming Recruitment

Let's take a closer look at how AI transforms critical areas in HR Management.

AUTOMATED RESUME SCREENING (ARS)

AI-backed tools can smoothly go back and forth through thousands of CVs, thus identifying the most suitable candidates using predefined criteria. This not only saves time but also reduces human bias, which ensures a fairer selection process.

Major players in the ARS market:

• Lever — uses AI to streamline the recruitment process, from sourcing to hiring. Its AI capabilities can automate manual tasks, improve candidate matching, and provide predictive analytics to enhance hiring decisions.
• Daxtra — leverages semantic searching techniques for quick and easy sourcing through databases. This parsing tool can provide data-driven insights from acquired resumes and help in hiring candidates easily.
• SmartRecruiters — an AI-powered resume tool ideal for enterprises. Its detailed resume-screening features work well for specific organizational needs. It also offers CRM functions to help HR professionals focus on building brands and sourcing candidates.
• CVViz — AI-driven platform used for contextual tracking and selection of the most suitable applicants. It goes a step further from keyword matching and chooses resumes based on contexts.
• SkillPool — offers a commendable AI resume tool for recruiters, matching applications with job descriptions and screening acquired resumes in no time. The automation features make repetitive HR jobs easier.

PREDICTIVE ANALYTICS

Advanced algorithms can predict which candidate succeeds in a given vacancy by analyzing data from previous hiring cycles. This predictive ability can help HR professionals make more informed decisions, increasing the match between applicant and employer.

IBM Watson Recruitment (IWR), uses AI to leverage information about the job market and experiences of hiring candidates. Then, it predicts time to fill and identify the candidates most likely to be successful.

CANDIDATE ASSESSMENT

AI-based assessment solutions use gamification, skills testing, and behavioral evaluations to efficiently measure candidate competency and personality traits. Progressive algorithms analyze the data generated by these comprehensive assessments to provide an in-depth report on a candidate’s strengths, weaknesses, personality traits, social skills, and cultural fit.

A global leader in consumer goods, Unilever began its recruitment transformation with its Future Leaders Program, a highly selective testing for recent university graduates that selects 800 individuals from a pool of 250,000 applicants.

The team at Unilever partnered with multiple solutions to create an end-to-end engaging and digital candidate experience, including HireVue to initiate mobile-phone-based recorded video interviews and interview assessment technology.

Through HireVue Assessments, AI filtered up to 80% of the candidate pool using data points, ultimately surfacing those candidates that are most likely to be successful at Unilever.

CHATBOTS AND VIRTUAL ASSISTANTS FOR CANDIDATE INTERACTION

Chatbots and Virtual Assistants play a crucial role in enhancing candidate engagement right from the initial stages of the recruitment process. By providing a responsive and interactive platform, candidates can have their questions addressed promptly, regardless of the time of day. This immediate feedback helps candidates feel valued and supported throughout the application process, improving candidate experience.

Probably your next job interview may be with ‘Alex,’ the smart Interviewer. Apriora’s key product is a two-way AI avatar, that conducts live video interviews with job candidates.

Alex can manage interviews at a pace far exceeding what a human can do. It does not need coffee breaks, vacation days, and paid time off, which reduces a company’s recruiting overhead and allows it to keep interviewing through rain, heat, and snow days.

The following are some of the top AI chatbots for recruitment and HR based on their features, ease of use, and compatibility with other HR tools.

• Talentsoft (acq. by Cegid) — useful in internal recruitment and employee engagement. TalentSoft is proficient in finding potential internal candidates for vacant positions and assists in the career progression within companies.
• Talkpush — engages with candidates across various messaging platforms, helping with screening, interview scheduling, and answering FAQs.
• Olivia — Paradox’s AI recruitment chatbot with a complete recruitment management system. From sourcing candidates to onboarding, Olivia has proved to be very effective enhancing candidate experience and ensuring seamless integration with the company’s HR systems.
• XOR — helps streamline the hiring process by automating candidate screening, scheduling interviews, and conducting initial interviews via chat.
• JobPal (acq. by SmartRecruiters) — focuses on improving the candidate experience by providing instant responses to inquiries and automating repetitive tasks.

Enhancing Employee Engagement

SENTIMENT ANALYSIS

A satisfied employee is a productive worker. It's a basic truth, but keeping your workforce happy and engaged in today's competitive job market can be challenging.

This is where employee sentiment analysis comes in. By understanding how your employees feel about you, their work, their colleagues, and the company, you can proactively address concerns and create a more positive work environment.

The type of tool you use will depend on the size of your organization and the insights you’d like to collect and track. Here are a few examples of sentiment analysis software tested in 2024 to look into:

• Qualtrics — a platform that helps you understand people’s experiences with your brand. It uses a sentiment analysis model called Text iQ. It analyzes written feedback from survey answers and comments on various social media platforms to check if it’s positive, negative, or neutral.
• Medallia — a comprehensive customer and employee experience platform (CX/EX platform). It helps capture the sentiment through surveys and pulse checks.
• Lattice — employee survey tool for multiple survey types using science-backed templates.
• Sogolytics — best for facilitating comprehensive analysis of employee feedback for improved engagement.
• Eletive — a People Success Platform designed for human resources teams aiming to increase employee engagement and improve the employee experience.

PERSONALIZED LEARNING & DEVELOPMENT

⁤Artificial Intelligence can adapt programs for development and training according to the individual needs and career goals of employees. ⁤⁤By recommending necessary courses, training courses, or mentoring opportunities, AI ensures that employees receive appropriate and effective development opportunities. ⁤

Training solutions, known as personalized learning platforms, dynamically adjust the content, pace, and feedback to precisely match and accommodate each learner's unique learning style, preferences, and abilities, ensuring an optimized and personalized experience.

Top e-learning platforms enhanced with AI:

• 360Learning is an AI-powered collaborative learning platform that incorporates the features of an LMS, LXP, and Academies to power upskilling and reskilling from within your organization.
• Docebo is a user-friendly cloud-based platform for training employees, partners, and customers that includes built-in AI-driven features.
• Sana Labs enables organizations to discover, share, and apply knowledge to achieve their business goals.
• Absorb LMS is a cloud-based LMS that aims to deliver engaging and effective employee and customer training.
• SC Training (prev. EdApp) is a mobile-first learning platform designed to ramp up mobile learning for employees anywhere, anytime, and on all devices.
• Zavvy is designed with a focus on helping you and your team design, curate, and manage your training programs.
• Cornerstone is an AI-powered platform designed to offer employees a seamless learning and growth experience.
• CYPHER Learning is a comprehensive learning platform for organizations ranging from tertiary providers to enterprises.
• WorkRamp offers a platform to centralize all your learning needs for employees and customers.
• LearnUpon is a cloud-based LMS that includes course creation, training delivery, and user management features.

PERFORMANCE FEEDBACK SYSTEMS

⁤Preparing performance reviews can be a difficult task for managers, often requiring a significant investment of time and effort. ⁤⁤A 2017 Adobe survey of 1,500 US office workers found that, on average, managers spend 17 hours per employee just preparing for the performance review itself. ⁤⁤However, with the advent of AI, many tools have emerged to streamline this process. ⁤⁤They empower managers to create comprehensive and personalized performance reviews efficiently, providing valuable feedback to their employees. ⁤

Deloitte, a global consultancy, recognized that traditional performance reviews were leaving employees feeling disconnected. They introduced an AI tool named "Performance Management", which delivers personalized real-time feedback and development prompts based on an employee's unique workflow and contributions. By leveraging employee data, they fostered a continuous feedback loop that allowed employees to feel more in control of their development. As a result, Deloitte saw a significant increase in employee retention rates — a crucial metric in the competitive consulting industry.

Optimizing Performance Management

OBJECTIVE PERFORMANCE METRICS

Effective performance management involves measuring performance by considering more factors than a simple rating or score. This allows for better identification of areas where an employee might need improvement and uncovering strengths. With advanced technology, you can track and analyze various performance metrics, providing an objective basis for appraisals.

One of the standard performance metrics is KPI (specific, quantifiable measures for tracking progress toward strategic goals and objectives). KPIs help focus on the most critical aspects of performance and drive improvement efforts. By now, Artificial Intelligence has reached a stage where it can analyze past data to give you recommendations for KPIs worth tracking.

On top of this, they assist you with real-time analysis in measuring employee progress to see if you're set to hit your KPIs on time.

EMPLOYEE RETENTION

AI-powered predictive analytics can play a focal role in identifying employees at risk of leaving the organization. By analyzing large amounts of data from various sources, such as payroll, HR records, and employee surveys, advanced algorithms can uncover patterns and indicators that may signal potential turnover.

IBM’s AI-powered predictive attrition model is a notable example of how predictive analytics can revolutionize retention strategies.

With a reported accuracy of 95% in identifying employees at risk of leaving, this tool helps HR departments design personalized retention plans tailored to individual employee needs. This can ultimately reduce turnover rates and boost engagement.

CAREER PATHING & SUCCESSION PLANNING

Machine intelligence has immense potential to transform career development strategies in large organizations. By leveraging predictive analytics and providing personalized guidance at scale, AI-powered career tools can revolutionize how employees navigate their career journeys.

Leading HR tech providers now integrate AI into career development capabilities:

• HRbrain offers an AI-powered Career Coach that creates personalized career plans and matches employees to growth opportunities.
• Eightfold leverages computer intelligence to map employee skills to open positions and generate predictive insights around retention risk.
• SAP SuccessFactors uses machine learning to recommend relevant learning content that bridges individual skills gaps.

As AI algorithms grow more sophisticated with expanding datasets, expect AI-enabled career development tools to become a competitive necessity for attracting and retaining top talent. The future of work depends on a holistic approach to nurturing employee growth and providing clarity amid constant change.

Challenges & Considerations

While intelligent systems offer numerous benefits for HR, it also presents challenges and considerations that organizations must carefully navigate. Here are some key challenges associated with implementing AI in HR and strategies to address them.

DATA PRIVACY & SECURITY

Challenge: AI systems rely heavily on data, including sensitive employee information, to function effectively. This creates significant concerns about data privacy and security. Unauthorized access, data breaches, and misuse of personal information can lead to serious legal and reputation consequences for organizations.

In the 2010s, personal data belonging to millions of Facebook users was collected without their consent by British consulting firm Cambridge Analytica, predominantly to be used for political advertising. The public reacted to the data privacy breach by initiating the campaign #DeleteFacebook to start a movement to boycott Facebook.

Considerations:

• Data Protection: Organizations must implement robust data protection measures, such as encryption, access controls, and regular security audits, to safeguard employee data.
• Compliance with Regulations: Compliance with data privacy laws, such as the General Data Protection Regulation (GDPR) in Europe or the California Consumer Privacy Act (CCPA) in the U.S., is crucial. Organizations should ensure that their AI systems meet these legal requirements and provide transparency about how data is collected, stored, and used.
• Employee Consent: Clear communication with employees about the data being collected, how it will be used, and obtaining their consent is essential for maintaining trust.

Microsoft provides data protection by implementing Personal Data Encryption (PDE), Multi-Factor Authentication (MFA), and continuous monitoring of AI-powered HR platforms. The company also meets global data privacy regulations by providing visibility about data usage and obtaining the employee's clear consent for data collection.

BIAS IN AI ALGORITHMS

Challenge: AI algorithms can inadvertently perpetuate or even exacerbate existing biases present in the data they are trained on. This can lead to unfair outcomes, such as biased hiring decisions or skewed performance evaluations, which can harm diversity and inclusion efforts.

Amazon launched its AI recruiting tool way back in 2014 with hopes that it could potentially help its HR team revolutionize hiring practices and reach hiring verdicts more efficiently.

But sadly, that wasn’t meant to be. The tool quickly developed a clear gender bias which automatically limited the number of female candidates selected for the next stage — all due to a lack of strong female candidates in the training data provided to the AI model.

Consideration:

• Bias Detection and Mitigation: Regular audits of advanced algorithms should be conducted to identify and mitigate any biases. Organizations should use diverse and representative datasets to train AI models and employ techniques like algorithmic fairness to reduce bias.
• Human Oversight: While digital intelligence can automate many HR processes, human oversight remains critical. HR professionals should be involved in reviewing AI-driven decisions to ensure they align with ethical standards and do not unfairly disadvantage any group.
• Continuous Improvement: AI systems should be regularly updated and refined to address new types of bias and to reflect changes in organizational values and goals.

IBM actively works on reducing bias in its intelligent systems by directing regular bias audits and involving diverse training datasets. IBM has also developed tools like AI Fairness 360, an open-source toolkit that helps detect and reduce bias in AI models, which ensures fair HR decisions.

CHANGE MANAGEMENT

Challenge: The integration of AI into HR processes requires significant changes in how HR professionals work. This can lead to resistance, particularly if employees fear that AI will replace their jobs or if they lack the necessary skills to work with new technology.

Hewlett-Packard (HP) experienced challenges in change management when it deployed an AI-backed performance management system. Employees were initially skeptical regarding newly implemented technology, fearing that AI-driven appraisals would lack the personal touch and nuance that managers provide.

Considerations:

• Training and Upskilling: Providing comprehensive training and upskilling opportunities is crucial for helping HR teams adapt to AI. This includes not only technical skills but also understanding how to interpret AI insights and make data-driven decisions.
• Communication and Transparency: Clear communication about the role of artificial intelligence in HR, its benefits, and its limitations can help alleviate fears and build trust among employees. Emphasizing that AI is a tool to enhance, not replace, human judgment is key.
• Leadership and Support: Strong leadership is essential for guiding the organization through the transition to AI-powered HR. This includes fostering a culture of innovation, encouraging collaboration between HR and IT teams, and providing ongoing support as new systems are implemented.

AT&T successfully managed the integration of AI by investing heavily in upskilling and reskilling its workforce. The company launched a Future Ready initiative, offering training programs to help HR professionals and other employees adapt to AI-driven processes. This effort not only mitigated resistance but also empowered employees to leverage machine intelligence” to enhance their work.

Conclusion

By involving AI, not only companies can improve efficiency and effectiveness but also create a more engaging and supportive environment for their employees.

As AI technology continues to expand, its impact on HR will undoubtedly grow, offering even more innovative solutions to meet the dynamic needs of the modern workforce.