By Jennifer Schaefer, MBA, ChFC, CLU, RHU, REBC, SHRM-SCP
Founder & CEO, JS Benefits Group | Forbes Business Council Contributor | Co-Host, Executive Leaders Radio

For years, employers have made many workforce decisions using a familiar formula: review what happened last year, look at current trends, compare available options, and make a decision before a deadline.

That approach is becoming increasingly difficult to justify in a data-driven business environment.

Employees have different priorities, organizations are managing increasingly diverse workforces, and employers have access to more information than ever before.

The opportunity is not simply to collect more data. It is to use that data more intelligently.

Artificial intelligence is beginning to change how employers can evaluate workforce needs, identify patterns, understand employee preferences and make better-informed decisions.

Moving Beyond Traditional Workforce Decisions

Many workforce decisions have historically been based on limited information.

Leaders may review employee surveys, participation numbers, turnover reports and other information before determining whether changes are necessary.

The problem is that a single snapshot may not tell the entire story.

A company’s workforce changes throughout the year. Employee demographics change. Preferences change. Hiring changes the composition of the organization. Different groups of employees may have very different priorities.

AI and advanced analytics create the possibility of moving from occasional analysis toward a more continuous approach to employee benefits strategy.

Instead of asking only what changed, employers can begin asking better questions.

What patterns are appearing across the workforce?

Which programs are employees actually using?

Are employee preferences changing?

Are certain groups experiencing different challenges?

What factors appear to influence engagement and retention?

The answers require more than a spreadsheet. They require meaningful analysis.

The Growing Role of Workforce Data

Organizations generate enormous amounts of workforce information.

Employers may have access to information involving employee demographics, participation, engagement, preferences, retention and other workforce characteristics.

The challenge is turning that information into something useful.

AI can help identify relationships and patterns that may be difficult to see through manual analysis alone.

For example, an employer might discover that participation differs substantially between employee groups, that certain programs have very low engagement, or that employee preferences are changing over time.

These observations do not automatically tell an employer what to change.

They do, however, provide a better starting point for asking the right questions.

The goal should not be to replace human judgment with an algorithm. The goal is to give leaders better information with which to make decisions.

AI Can Help Employers Better Understand Employees

One of the biggest limitations of traditional workforce strategy is the assumption that employees have relatively uniform needs.

They don’t.

A younger employee may have very different priorities from an employee approaching retirement. An employee with a family may evaluate workplace programs differently from a single employee. Employees in different geographic areas may have different expectations and priorities.

A single strategy must often serve all of them.

Data-driven analysis can help employers understand those differences.

AI can potentially identify workforce patterns and help employers evaluate whether their overall employee strategy is aligned with the people they are actually trying to attract and retain.

This does not mean creating a completely different experience for every employee.

Instead, it can mean using workforce data to make better decisions about employee programs, communication, workplace resources, wellness initiatives and other areas that influence employee experience.

The Connection Between Employee Experience and Retention

Employee experience has become increasingly connected to recruiting and retention.

Compensation is important, but employees evaluate the overall employment experience.

Workplace flexibility, professional development, recognition, wellness resources and employee programs can all influence how employees perceive the value of working for an organization.

AI can potentially help employers understand which programs matter most to different segments of their workforce.

That creates an opportunity to move away from the idea that more programs automatically mean a better employee experience.

An organization could offer numerous programs and still provide an experience that employees do not value.

The better question is whether the organization is investing in the areas that produce meaningful value for employees while supporting broader business objectives.

Better Decisions Require Better Data

Data can help determine where an organization should focus its attention.

Instead of relying exclusively on assumptions, leaders can examine patterns across their workforce and identify areas that deserve additional attention.

For example, participation data might reveal differences between employee groups. Engagement data might identify programs that are underused. Workforce trends might reveal changes in employee preferences that leadership had not previously recognized.

Technology can make analysis faster, but the quality of the decision still depends on the quality of the underlying data and the expertise interpreting it.

Data is valuable because it can help organizations ask better questions.

AI Does Not Replace Human Expertise

The rise of AI does not mean employers no longer need experienced professionals.

In many ways, it makes human expertise more important.

AI can identify patterns, organize information and assist with analysis. It cannot independently understand every business objective, employee population, organizational culture or strategic priority.

Workforce decisions can also have significant consequences for employees.

An experienced advisor can take data-driven findings and put them into context.

That may mean comparing different strategies, evaluating potential outcomes, explaining tradeoffs or helping leadership understand how a proposed change could affect employees.

The most effective model is therefore not humans versus AI.

It is humans using AI to make better-informed decisions.

The Future of Workforce Strategy Is More Data-Driven

The workplace is moving toward a more analytical model.

Employers have more data available to them, technology continues to advance, and sophisticated analysis is becoming increasingly accessible.

The organizations that benefit most will not necessarily be the ones using the most technology.

They will be the ones asking better questions.

Instead of simply asking what employees want, organizations can look for evidence.

Instead of assuming every employee has the same priorities, leaders can examine differences across their workforce.

Instead of waiting for an annual review, organizations can evaluate trends throughout the year.

AI can help make that possible.

But the ultimate objective remains the same: build a workplace strategy that works for both employees and the organization.

The future of workforce strategy will not simply be about having more data.

It will be about knowing what to do with it.

About the Author

Jennifer Schaefer, MBA, ChFC, CLU, RHU, REBC, SHRM-SCP, is Founder & CEO of JS Benefits Group, an employee benefits consulting firm. She is also a Forbes Business Council Contributor and Co-Host of Executive Leaders Radio.