HR teams are sitting on a goldmine of data, but most of it goes untapped. While organizations collect vast amounts of information on workforce trends, only a few use this data to shape the future. AI-powered analytics is changing that, transforming HR from a reactive function into a predictive powerhouse.
Advanced analytics solutions could help HR move from reacting to predicting, reporting to influencing. HR leaders can use these tools to predict turnover, identify skill gaps before they become crises, test drive decisions, and pinpoint what (and who) influences workplace culture.
Yet, as analytics has advanced, most HR skill sets have not. HR professionals who want to keep ahead of the curvemust transition from data collectors to data-driven decision-makers. That means embracing AI-powered analytics and improving data literacy to maximize HR’s influence.
The future of HR isn’t just about managing people—it’s about making data-driven decisions that drive business impact. HR professionals can lead this shift by harnessing AI-powered analytics to anticipate challenges, optimize talent strategies, and shape a thriving workplace culture.
SHRM
The Difference Advanced Analytics Makes
Most HR teams already track workforce trends. Advanced analytics highlight trends and shows why they happen, how they’re connected, and what to do next.
In the modern era of data sciences, AI-driven tools take this further, uncovering hidden patterns and connections traditional analysis might miss.
One of the most valuable applications of these tools in HR is to define or quantify the value of your workforce investment. I advocate for tracking retention, engagement, workforce health, and success factors (e.g., promotability). AI-powered data analytics can help you connect these metrics to business outcomes and uncover areas of opportunity.
Anticipating Workforce Shifts to Stay Ahead
Recruiting was a challenge for some organizations in 2024, with 43% of organizations identifying it as a top priority in 2024, however only 56% of HR professionals rated their organization's recruiting efforts as effective or very effective, according to the 2025 SHRM State of the Workplace report.
Advanced analytics can help close this gap by predicting workforce trends—such as turnover and skill obsolescence—allowing HR leaders to shift from reacting to problems to preventing them. (Some organizations are so sophisticated they can analyze interview data and predict—down to the day—when an employee might leave.)
One of the most powerful applications of these tools is forecasting skill needs, be it skill shortages or the skills that will become obsolete. By analyzing internal workforce data alongside external labor trends, HR can anticipate gaps and take action to improve future business operations.
Analyzing potential labor market shifts is another example most HR professionals would benefit from. Projecting talent needs 5 or 10 years ahead allows organizations to simulate workforce scenarios—best case, worst case, and more realistic cases in the middle—keeping HR prepared for what's next.
Shaping a Stronger Workplace Culture
SHRM’s 2024 State of the Global Workplace culture global research shows 83% of employees in good or excellent workplace cultures feel deeply motivated to deliver high-quality work, compared to 45% in poor or terrible workplace cultures. AI-powered data analytics can help HR teams assess workplace culture and make informed decisions to strengthen it.
Using advanced analytics, HR teams can evaluate factors like employee sentiment, workload patterns, and organizational communications to get a real-time view of engagement and cultural influencers. Rather than depending on traditional surveys to find trends, AI-driven tools provide insights to help influence trends.
For example, one organization in the health care industry used organizational network analysis to identify individual nurses who influenced the safety practices of their peers across all disciplines during emergency medical treatment situations. Once identified, they turned their influencer into an uber influencer, modeling an AI agent based on their communication style and approach to train and guide others.
Conversely, these tools can also identify negative influencers or influences on the culture, enabling HR to address potential challenges before they impact business performance.
Building Models That Sharpen Decision-Making
The influencer example presents a key opportunity many HR organizations haven’t tapped into yet: using AI to replicate leadership styles. While deepfakes have a terrible connotation, I find there's value in modeling AI agents after leaders—whether it’s the CEO, CHRO, or even yourself.
A digital twin can think like you and ask questions like you but then focus on objective data sources you define, helping you make more strategic, data-driven decisions. A digital twin can help workshop situations, test choices, and challenge assumptions.
It’s worth noting that AI models are a tool, not a replacement for an individual. JohnnyGPT will never be better than Johnny (and they certainly shouldn’t make compensation decisions), but JohnnyGPT could push you beyond your blind spots.
Break Barriers to Adopting Advanced Analytics
Adopting AI-driven data analytics comes with barriers, and our research points to two: data literacy and data infrastructure. Fifty-eight percent of HR executives whose organization uses people analytics say their organizations don’t provide enough resources to upskill HR professionals in data literacy, and 56% say they lack adequate data infrastructure, according to SHRM’s People Analytics in Human Resources report.
Education and reinforcement matter more than anything in improving data literacy, and mandatory training is the most effective approach I’ve seen. But not compulsory training for the sake of compliance. Instead, make it mandatory to demonstrate skill application. Some organizations even incentivize training with cash prizes for the best AI-driven solutions based on actual use cases.
As for data infrastructure, it starts with working closely with your tech partners. HR must ensure data integrity and security in how data is stored. It’s also essential to have transparency in the AI system's decision-making process—something HR professionals whose organizations use people analytics are nearly unanimous on according to SHRM’s People Analytics in Human Resources report. Find a system that meets your security needs and provides insight into how AI makes decisions.
From there, HR needs a collaborative approach to AI policy. Legal and tech should always be involved. Once a policy is in place, consider running it past a vendor specializing in cybersecurity risk and an organization focused on responsible AI use.
Preparing for an AI-Driven Future in HR
The future of HR isn’t just about managing people—it’s about making data-driven decisions that drive business impact. HR professionals can lead this shift by harnessing AI-powered analytics to anticipate challenges, optimize talent strategies, and shape a thriving workplace culture.
HR's future belongs to those who embrace AI and data driven decision making. Those who do will not just manage change, they will definte the future of work.
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