This is an expert guest post written by Eleanor Hecks from Designerly.
Artificial intelligence has become more accessible, popular, and advanced in recent years. You may have already noticed how it has improved workflows in modern organizations. For HR leaders, there’s optimism that AI can accelerate solutions to common issues in workforce management. However, there’s also a looming anxiety, as these advancements also mean bots could replace a significant number of human workers, even HR personnel. But how exactly is AI used in human resources, and what have companies achieved with it so far?
This article will discuss the positive and negative consequences of AI use, as well as the ethical concerns HR leaders must consider. Understanding these areas will help facilitate your decision-making process when it comes to using AI technology without compromising the “human” aspect of the HR role. Broadening your use of HR technology could also advance your career by giving you more time to spend on high-value tasks, which will also help you prepare and stay ahead as companies begin to use AI more extensively.
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AI adoption in HR this 2025
A 2025 study of AI implementation in HR found that 59% of HR directors use little to no artificial intelligence in their organizations. However, 45% have started implementing it gradually, while 3% are completing their rollouts. Nearly a quarter said their HR departments lack clear strategies for integrating AI into their workflows.
Another potentially surprising takeaway is that regulatory and ethical concerns did not pose significant challenges to adoption. Instead, the largest obstacles were the lack of expertise, time, budget, and high-quality data.
Learning about examples of AI in HR can help you find the most appropriate use cases to save time, increase productivity, and anticipate potential needs and issues.
The impact of using AI in HR
Artificial intelligence is like most other technologies in that it has positive and negative impacts. You may notice both in specific applications.
Talent acquisition
HR professionals use artificial intelligence to screen potential applicants, reducing the time it takes to find the most suitable candidates. But while doing so also increases the chances of optimized outcomes, some hiring managers can become too dependent on the technology and overlook qualified individuals. This is because AI tools detect specific keywords and may potentially eliminate highly qualified individuals whose résumés contain slight keyword variations.
In a case reported by The Guardian, a candidate who attended an AI phone interview said the creepy robotic voice kept cutting him off, so he couldn’t finish answering the questions. Surprisingly, the AI prompted that the interview was completed even after a series of questions with incomplete answers.
Technology helps busy HR professionals weed out unsuitable applicants, but efficient applications of AI in recruitment require creating channels to address potential issues that may compromise a qualified candidate’s application.
Employee engagement
Engagement is one of the biggest factors that affect employee productivity and retention. In many organizations, AI is used to optimize schedules, personalize training, track performance, and analyze feedback faster.
However, this may also mean less interaction with leaders, and employees who could use empathy in scenarios that require sensitivity may feel misunderstood and subsequently disengage when dealing with a bot that lacks emotional intelligence. Aside from this, the use of AI may also raise privacy concerns and issues about algorithmic bias.
HR automation
AI automates repetitive and time-consuming tasks for HR departments, giving staff more time to focus on more mentally demanding, complex duties. However, professionals who trust the tools too much may not notice the occasional errors made by even the most advanced AI systems.
Ideally, AI should be treated as a supplement to one’s expertise rather than using the technology to replace it. An AI-powered automation software can reduce manual work significantly, which can free up your time for other bigger, more important tasks.
Performance management
Artificial intelligence can also be used to keep the workforce motivated and accountable. Many time-tracking tools feature the technology to optimize user productivity when confirming the type and duration of their activities, streamlining client-billing procedures or other administrative tasks that require documentation of time spent in tasks. Some also reveal excessive idle time or inefficient processes. AI is also useful in generating performance reviews customized to specific individuals.
Alternatively, manufacturing companies, construction sites, and trucking businesses install AI-enabled cameras to monitor performance and identify risks. The footage highlights relevant areas for improvement, but some employees dislike the use of AI to oversee their work and feel upset by the belief that their employers don’t trust them to manage their time and follow procedures.
Chatbots
The use of chatbots is among the most recognized AI examples in many businesses. In the workforce, employees simply need to input tailored prompts to get nearly instantaneous answers to their questions anytime. There are also recruitment tools that provide multilingual jobseeker support, aiding users in submitting applications smoothly.
However, HR professionals can only achieve the best results by striking a practical balance when using chatbots in their organizations. Some teams may resist the changes, and those unfamiliar with new technology may not even want to try them. Demonstrating how the tools save time and improve quality of work can encourage employees to incorporate them into their work.
Moreover, offering users technical support channels or other resources will ease anxiety as it will enable them to seek help easily if chatbots malfunction. HR teams should consider explaining how advanced versions of these tools work, including scenarios where AI is likely to dispense incorrect information that seems accurate, which necessitates fact-checking instead of immediately accepting the answers given.
Predictive analytics
Employees who quit without warning or exhibit sudden decline in performance cause far-reaching impacts on the HR department and organization. However, there are vendors that offer AI tools which they claim to be capable of predicting dissatisfaction, allowing managers to intervene before disengaged or unsatisfied workers decide to leave. Similarly, systems with predictive analytics include features that determine which candidates will stay in their roles the longest.
Unfortunately, many vendors do not publish specific back-end functionality details about their products, reducing transparency and trust. Additionally, staff awareness of workplace monitoring may elevate anxiety and lower retention rates among formerly satisfied parties, especially if people worry about their superiors misinterpreting what the data supposedly indicates about them.
Workforce planning
AI can strengthen talent management processes for human resources departments, equipping organizations for both their current and future needs. Besides offering candidate-screening solutions that fill new roles, these systems can enhance training programs to prepare learners for career advancement and mentoring opportunities.
AI technology can also identify high-potential employees, so you can narrow down the best candidates for promotions or growth opportunities. It can highlight urgent hiring needs, enabling organizations to close workforce gaps and prevent labor shortage issues from escalating. You should remain cautious though, since AI tools are only as reliable as the amount and quality of information they receive. To reduce unwanted outcomes, robust quality control and data governance efforts at all organizational levels are a must.
The ethical issues of using AI in the workplace
The rise of AI in the workplace has revealed ethical considerations that could affect the ways this technology is used. Many professionals have experienced or witnessed how applications that seem advanced can make dangerous errors or introduce workflow complications.
Incorrect information
Generative AI use cases in human resources center on large language models that allow products to have human-like conversations with users via chatbot interfaces. However, these tools may provide wrong information that seems correct. This tendency poses a liability risk, especially if it results in team members receiving inaccurate information about their rights or benefits, or applicants getting misleading answers to questions about open positions.
Skill erosion
Professionals in human resources and other demanding industries often face many distractions and burdensome workloads, which can make workers more impulsive. Crucially, impulsive behavior is an undesirable characteristic for those involved in decision-making roles that can impact people’s lives and careers.
AI relieves HR workloads by handling repetitive or low-value tasks, leaving professionals more prepared to act more thoughtfully and stay level-headed under pressure. However, parties who become too dependent on it could eventually forget how to do tasks previously within their skill sets. Automation can erode human skills, and this lack of practice can lead to a decline in proficiency. They may also trust AI technology too much instead of relying on analytical judgment and firsthand experience.
Harmful biases
AI accuracy depends on the completeness of the training data and how well that information reflects real-world conditions. Tools are only as good as the humans who make them, but uninformed users may overlook flaws, which can cause unintended and damaging results.
Imagine if a tool disadvantages female applicants or those of a particular race because of underrepresentation in training data. Such bias could cause affected parties to lose significant career advancement opportunities even if they are well-qualified. Tools that detect AI-generated writing may wrongly flag individuals with communication patterns not prominently apparent within the tool’s initial dataset, including non-native speakers or people with disabilities.
Labor shortage has been at an all-time high in the last decade, presenting challenges that convince many HR professionals to consider addressing them with artificial intelligence. While AI can indeed help tackle common workforce issues, remember that user skill is just as important as data quality for AI systems to be efficient.
How is AI used in human resources?
HR departments naturally expect outstanding results from artificial intelligence when used to address workforce issues. However, clear expectations must be set when it comes to solving identified problems, and timelines must be adapted to account for anticipated obstacles.
IBM’s benefits assistant chatbot
IBM was an early adopter of AI in HR when it introduced a benefits chatbot in 2017. Executives wanted to reduce time-consuming tasks where front-line managers had to flip through long corporate manuals to find answers to workers’ queries. They implemented a new rule that required leaders to use the chatbot instead, but worker satisfaction plummeted because executives forced the change.
The HR department reacted to the discontent by introducing a new strategy of asking employees to find workday optimization opportunities with the chatbot instead. Now, users are happier than they were before the introduction of AI. The chatbot handles 94% of queries, accounting for over 10 million HR-related interactions each year. This tool also detects potentially sensitive subjects like misconduct or low performance, instructing people to discuss them with HR leaders instead.
This example emphasizes why executives must be willing to adjust their plans when necessary. Many workers don’t like it when their managers force them to use new technology, especially with little or no notice. Such situations lead them to conclude that their workplace’s executives make major, process-altering decisions without their input. However, since HR professionals listened to the dissatisfaction and adjusted their strategy, it still succeeded. Encouraging staff to fit AI into their daily workflows also brings to light better ways for the technology to truly help them.
Conagra Brands’ centralized succession planning
Workforce optimization isn’t easy but talent managers can influence its success by identifying the best candidates for career progression and those suitable for leadership roles. Conagra Brands deployed an HR-focused generative AI tool to replace a decentralized Excel spreadsheet system for succession planning.
Capturing the data in separate spreadsheets didn’t give the HR team sufficient visibility into the skills and experience of its current workforce. However, Generative AI assisted them in developing a new talent succession framework. It displays all the information in one place and keeps it accessible to HR business partners. Thanks to this high-tech update, HR experts make more data-driven decisions and minimize bias while improving their talent management process.
In Conagra’s Gen AI process, an associated skills framework defines the 12 competencies within the roles of its 720 workers added to the system after eight months. It prompts HR professionals to discuss advancement and development opportunities with workers who reach the desired proficiency levels. These interactions also allow participants to discover gaps and set goals to plan their progression paths. HR leaders expect that this strategy will encourage the organization to invest in its talent and enhance future competitiveness.
Unilever’s improvements to outdated hiring processes
Many HR professionals find that traditional approaches to hiring no longer serve the needs of the modern workforce. Not surprisingly, applicants dislike many of these enduring best practices, too. Tailoring a résumé and cover letter to a specific role takes time, and catching HR professionals’ attention within the first page or paragraph isn’t easy either.
How is AI used in human resources to address these challenges? It streamlines processes and gives candidates more opportunities to showcase their skills and experience. It may also help organizations to hire virtual teams more effectively by broadening the applicant pool to attract people from specific states or countries. Such possibilities are especially appealing if you need to fill highly specialized positions or those not well-represented within the local job market.
Executives at Unilever had extremely ambitious goals to hire 30,000 people in a year without using résumés. Equally important, they sought to overcome the issues associated with conventional recruitment methods. These forward-thinking HR professionals thought outside the box by not using résumés to find candidates. Instead, applicants underwent AI-enabled assessments, real-world problem-solving challenges, and video interviews to prove their suitability.
When AI analyzed each candidate’s recorded video interview, it revealed valuable details about their personalities and communication styles. Since this assessment examined soft skills, cognitive abilities, and other traits, the results indicated candidates’ suitability for roles and the organization’s culture. Their data-driven decision-making process also used AI to match applicants’ skills and characteristics to specific job roles.
These tech-driven methods can shorten hiring timelines and boost new-hire diversity. Such outcomes eliminate preventable delays while meeting the organization’s workforce needs. The selection process became fairer and more objective because AI handled its early stages. However, HR professionals interested in replicating these results should investigate training data quality and learn about development efforts to reduce unconscious bias.
Final thoughts
Using AI in human resources can help you predict and even improve workers’ performance, identify advancement opportunities, save time, and replace irrelevant processes. Many organizations have tackled these problems and others with artificial intelligence, elevating workforce efficiency, satisfaction, and productivity.
However, AI technology has ethical issues and downsides, including producing biased results that can disadvantage specific groups. Generative AI chatbots also have a well-documented shortcoming—providing inaccurate answers that sound correct, creating risks for those who do not fact-check the output. Such outcomes could pose legal or reputation issues, mainly if the output is considered for critical decision-making.
If you’re considering using AI as an HR professional, take the time to research all relevant options to learn about the system’s reliability, functionality, and best use cases. It’s also valuable to ask vendor representatives to show examples of enterprises similar to yours that have achieved desirable results. Finally, remaining open and responsive to employee feedback after deployment will help enhance the technology’s outcomes.