The Future of Public Sector Workforce: 6 Ways AI Can Improve Employee Wellness and Performance

Data and AI are transforming every aspect of our lives, from home deliveries to work calendar management to curing cancer. Public-sector organizations are no exception in the AI revolution. In fact, the adoption of data and AI technologies can be a game-changer for public-sector organizations that want to maintain excellent employee performance and retention in a tumultuous employment market.

Here are six ways that public-sector organizations can leverage data and AI to improve employee wellness and, by extension, increase productivity and reduce turnover:

An AI-generated government building in a swirl of AI activity

1. Predictive analytics to identify high-risk employees

Predictive analytics can help government organizations find employees who are at risk of leaving or underperforming. By analyzing data on employee engagement, job satisfaction, and turnover rates, predictive analytics algorithms can identify patterns and make accurate predictions about employee behavior. This enables leaders to take proactive measures to retain high-risk employees and prevent underperformance. According to a study by McKinsey, predictive analytics can reduce employee turnover by up to 35%.

One great example of a government agency that has implemented predictive analytics is the U.S. Department of Veterans Affairs (VA). The VA uses predictive analytics to identify high-risk veterans who are at risk of suicide. By analyzing data from various sources, including electronic health records (EHR), the VA can identify veterans who are at high risk of suicide and intervene before it's too late.

2. AI-powered chatbots to improve employee wellness

For public-sector orgs struggling with employee burnout or lack of engagement, AI-powered chatbots may be a game-changer. The World Health Organization wrote that “for every $1 put into scaled up treatment for common mental [challenges], there is a return of $4 in improved health and productivity.”

Chatbots are a relatively cost-efficient way to provide employees with instant access to mental health support and resources. By using natural language processing (NLP) and machine learning (ML), chatbots can provide personalized support, tailoring responses to employees' specific needs. Some 64% of employees would be willing to use a chatbot for mental health support—possibly because it feels less workplace-connected and less stigmatizing.

For a working example of chatbots used for government workers and citizens alike, look at the Canadian Federal Government. The government has developed an AI-powered chatbot named Wellness Together Canada that provides free mental health support to Canadians.

A cheerful chatbot waiting to engage with public-sector employees

3. Data-driven performance management

Public agencies can improve employee performance by providing managers access to data-driven insights into their employees' work. By using data on employee productivity, job satisfaction, and feedback, leaders can identify areas for improvement and provide targeted training and development opportunities to employees. The New Zealand Police, for example, uses data analytics for this purpose, and has measured significant improvement in officer performance and a reduction in complaints.

AI can also help drive continuous performance management with tools such as Microsoft Viva, which can nudge managers to schedule check-ins and reviews. 85% of surveyed workers who have weekly check-ins with their manager reported that they experience higher levels of employee engagement as compared to their counterparts who have annual reviews.

4. AI-powered recruiting

AI-powered recruiting can help public-sector organizations attract and retain top talent by streamlining the recruitment process and reducing bias. For one thing, AI can help candidates find the right jobs for them by providing recommendations for qualified opportunities based on past interest and the candidates’ skills. Since government jobs often require specific credentialing, this is a helpful bonus.

On the employer side, by using AI-powered algorithms to screen candidates, public-sector organizations can identify the most qualified candidates and reduce the time and resources required for recruitment. One example of a government agency that has implemented AI-powered recruiting is the United States Intelligence Community (IC), which uses AI-powered algorithms to screen candidates for security clearances, reducing the time and resources required for the clearance process.

5. Predictive maintenance to improve employee experience

This might be a surprising item on this list, but everyone can identify with feeling frustrated and thwarted at work because a tool isn’t working. Smooth workflow yields productive work. That’s why predictive maintenance helps improve employee experience and productivity—by reducing downtime and ensuring that equipment is always available when needed.

By using data on equipment performance and maintenance history, predictive maintenance algorithms can predict when equipment is likely to fail and schedule maintenance before it impacts operations. The New York City Department of Transportation (NYCDOT), for instance, uses a predictive maintenance system to monitor the condition of its fleet of trucks and predict when maintenance is required. This has resulted in a significant reduction in vehicle breakdowns and improved employee experience.

Predictive maintenance for both virtual and physical worktools is especially crucial for large, complex, and customer-facing public organizations like NYCDOT. Downtime can impact not only large chunks of operations, but also customer experience. When customers are frustrated, that creates more pressure on the agency’s employees.

6. AI-powered training and development

Retention rates are 34% higher among organizations that offer employee development opportunities. And 91% of employees want personalized, relevant training. These are two excellent reasons for public-sector organizations to implement AI-powered training and development.

Well-trained and engaged employees are the most valuable assets in any organization. Leaders can use AI-powered algorithms to not only analyze employee performance and identify areas for improvement, but to use data from surveys and reviews to offer personalized upskilling and cross-skilling opportunities. This is key right now given the dearth of available candidates for mission-critical areas like cybersecurity and, yes, AI. Finding people with the right skillset and interest to cross-skill into those understaffed departments can be an enormous cost-saver.

Many government organizations are already using AI-enabled training, but one example that stands out in terms of mission-critical training is the UK’s Royal Air Force (RAF), which uses an AI-powered training system that provides personalized training and development opportunities to pilots. The system analyzes pilot performance data and identifies areas for improvement, then recommends targeted training and development opportunities to each pilot to maximize their individual skills.


Looking at all these, it may seem like the future of human resource management isn’t human at all. In fact, using AI to improve employee wellness and productivity makes work more human-focused than ever. People prefer and expect personalization in all aspects of life, and often, the workplace can feel anonymizing, or targeted at a theoretical baseline employee that not everyone relates to.

Data and AI have the potential to transform employee experience, wellness, and performance. By leveraging the technologies above, public-sector organizations can improve employee retention, reduce underperformance, and provide personalized support without additional overhead. The examples used within this article demonstrate that all types of government entities, from military to street sweeping, can successfully implement AI-powered programs. Embracing data and AI today means embracing a more engaged, more productive workforce for many years to come.

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