A strong hiring process can help you identify the best candidates for any role. But even the best recruiters can't predict with 100% accuracy how a new hire will perform in your team. Sometimes, a very promising candidate might turn out to be disappointing. Other times, the person with the patchy resume might evolve to become your star player.

Data-driven HR teams can leverage artificial intelligence to enhance strategic decision-making through five key applications: combining multiple data sources into unified reports, performing sentiment analysis on employee feedback, identifying retention risks through pattern recognition, analyzing skills gaps for workforce planning, and designing tailored benefits packages based on employee demographics and preferences. In recent years, Human Resources leaders have played an increasingly strategic role within their companies. CHROs are to be found in most C-Suites, and their insight helps to shape long-term strategy. This change is happening mostly because HR teams can provide invaluable insight into the current state of play. This insight is supported by the rich people data gathered on HRIS platforms, plus related systems like ERPs (Enterprise Resource Planning). As a result, companies that use people metrics enjoy consistently higher profits than other businesses. Now that Artificial Intelligence (AI) is on the rise, HR professionals have a chance to become even more impactful. In this blog, we’ll examine some strategies for using AI in the HR function. But first, let’s look at how HR data influences decisions. Data-driven decisions in the HR department Human Resources is one of the most data-rich departments in any business. HR teams have access to vital information, such as: Labor costs: Including salaries, benefit expenditure, and other associated costs Operational capabilities: Available skills within the current team (as well as any skills gaps) Resource allocation: Performance and scheduling data, which helps avoid over- and under-staffing Culture and DEI metrics: Measurements of the organization’s progress against inclusivity goals Engagement and retention metrics: The organization’s ability to get the most from staff and retain the most valuable people This information is hugely important at a leadership level, as it allows them to game out strategic decisions. For example, a business might want to expand into a new product line. Does the current team have the operational capabilities to support that product line? What are the costs of hiring more people to support this project? HR data provides answers to all of those questions. Data-driven decision-making also helps the HR team perform their responsibilities. Data insights can tell if your hiring strategy is working, if employees are engaging with professional development, and if your team structure is evenly balanced. The biggest challenge for HR teams is analyzing and acting on all of this data. In fact, many HR leaders now find themselves overwhelmed by the sheer volume of data—only 12% of companies conduct regular reviews of contingent workforce data. And that’s where AI can help. How Artificial Intelligence can help HR AI is still an emerging technology with dozens of new tools appearing each week. On top of that, you might find AI capabilities appearing in your existing software. The ideas below are based on the capabilities found in some of these AI tools, as well as general AI platforms like ChatGPT. It’s worth shopping around to find an AI tool that allows you to do what you need. If you need help, speak to an HRIS consultant for advice. (A word of caution: Do not input sensitive information such as employee records to an AI tool unless you have verified that the tool is secure. Speak to the software vendor or consult a HR IT expert.) 1. Combine multiple sources of HR data One of the strengths of AI is that it can work with data from lots of different sources, even if it’s in a different format. For example, say your HR team wants to perform a detailed analysis of employee engagement data. This data might include a range of different sources, such as: Productivity data exported from your HRIS Resource allocation data from your ERP An Excel spreadsheet that records sick leave and other unexplained absences. Written notes from an employee satisfaction focus group One of AI’s strongest features is its ability to combine different sources. With the right AI tool, you could potentially upload a number of different sources, then ask the AI to combine them into a single report. 2. Perform sentiment analysis Engagement analysis is one of HR’s most important responsibilities. Engagement data can reveal a lot about your current state. For example, poor engagement could mean that you have issues with organizational culture, Total Rewards, or employee wellbeing. AI can help collate engagement data into a single report, but it can also go one step further. “Sentiment analysis” looks at the language that employees use, categorizing phrases according to sentiment: Positive sentiment words: Empowered, encouraged, valued, appreciated. Negative sentiment words: Unclear, frustrating, difficult, disappointing AI is also capable of analyzing context, so it can tell the difference between “My boss makes me feel empowered” and “I wish my boss made me feel more empowered”. This allows for fast, accurate analysis of large quantities of data. With AI tools, you can perform sentiment analysis on a large body of engagement data, such as survey results, exit interview notes, or feedback forms. You can also ask the AI to analyze historical data, showing how engagement trends over time. 3. Identify retention risks AI is also great at identifying complex patterns within your HR data. This makes it an excellent tool for forecasting and pattern-based predictions. One common HR data pattern is the retention risk. An employee might be a retention risk if they meet any of the following criteria: Unusual number of sick days or leave requests Declining logged-in hours Negative feedback from managers, customers or colleagues Salary is below market average or less than their peers A HR professional might not spot any of these red flags by themselves, but an AI can be trained to look out for telltale patterns. When an employee is deemed to be a retention risk, the AI can suggest appropriate next steps to prevent turnover. 4. Analyze skills gaps Every team has certain available skillsets, and certain skills gaps. For example, you might have a Java developer but not a C++ developer, or Spanish speakers but no Mandarin speakers. Data-driven HR teams can gather skills information and create a picture of the current team. An AI tool can go one step further by: Collating public information about required skills for specific roles Creating a skills matrix for a specific project type Identifying gaps between available skills and skills needed Again, AI’s biggest advantage is size and speed. With the right AI tool, you can analyze enormous quantities of data and create detailed job profiles for every position. This gives you a clear, up-to-date picture of the skills your team requires. With this information, you can fine-tune your recruitment strategy and your professional development program to meet strategic requirements. 5. Design effective benefits offerings Creating a compelling benefits package is key to attracting and retaining top talent. However, with so many options available, it can be challenging for HR teams to determine which benefits will be most valuable to their employees. AI can help by analyzing employee data, such as demographic information and survey feedback, to identify employee preference trends. For example, if a significant portion of the workforce consists of young parents, AI may suggest offering more robust parental leave policies or childcare benefits. By leveraging AI insights, HR teams can design benefits packages tailored to their workforce's specific needs and preferences, ultimately leading to higher employee satisfaction and retention. The future of AI in HR As AI technology continues to advance, its potential applications in HR will only expand. From automating routine tasks to providing predictive insights, AI has the power to transform the way HR teams operate. However, it's important to remember that AI is not a replacement for human judgment and expertise. Rather, it is a tool that can help HR professionals make more informed, data-driven decisions and focus on strategic initiatives that drive business success. By embracing AI and leveraging its capabilities, HR teams can position themselves as key strategic partners within their organizations, driving innovation and contributing to overall business success. Need help with HRIS or other HR technology? Speak to a Helios HR consultant today! FAQ How Can AI Help HR Teams Analyze Employee Data More Effectively? AI excels at combining data from multiple sources—HRIS platforms, ERP systems, spreadsheets, and qualitative feedback—into unified reports. This capability allows HR teams to analyze complex datasets quickly, identifying patterns and trends that would be time-consuming or impossible to detect manually, leading to more informed strategic decisions about workforce planning and talent management. What Is Sentiment Analysis and How Does It Benefit HR? Sentiment analysis uses AI to categorize language in employee feedback as positive, negative, or neutral while understanding context. This enables HR teams to rapidly analyze large volumes of engagement data from surveys, exit interviews, and feedback forms, tracking sentiment trends over time to identify culture issues, engagement problems, or areas requiring immediate attention. Can AI Predict Which Employees Are at Risk of Leaving? AI identifies retention risks by analyzing patterns such as increased sick days, declining logged hours, negative feedback, and below-market compensation. By detecting these warning signals early, AI enables HR teams to proactively intervene with at-risk employees through targeted retention strategies, potentially preventing costly turnover before it occurs. What Role Does AI Play in Identifying Skills Gaps? AI analyzes job requirements, current employee skills data, and industry standards to create comprehensive skills matrices for specific projects or roles. This analysis reveals gaps between available capabilities and needed competencies, enabling HR teams to develop targeted recruitment strategies and professional development programs aligned with strategic business objectives and future workforce needs. Additional Resources SHRM, What HR Professionals Must Know About AI-Powered Analytics Harvard Business Review, Is HR the Most Analytics-Driven Function? SHRM, The Role of AI in HR Continues to Expand

Finance companies face complex HR compliance requirements alongside daily administrative tasks like payroll, benefits, and employee relations. Foundational HR outsourcing provides access to experienced professionals who handle staffing, training, documentation, and regulatory compliance, allowing internal teams to focus on strategic initiatives while ensuring adherence to financial industry regulations like SOX and FINRA.

As I-9 audits and penalties increase in 2025, businesses must stay ahead of compliance risks. Errors in Form I-9 can lead to significant fines, even if they are unintentional. Ensuring compliance requires accurate documentation, timely verification, and a proactive compliance strategy.

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Internships are a vital stepping stone in the career paths of many young professionals. They give recent graduates a chance to gain real-world experience, which is a vital part of any resume.