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!
