AI in Employee Engagement: 7 Applications to Try Yourself

15% of employees are actively disengaged in the workplace. Such low engagement results in a global GDP loss of over $8.9 trillion.

You don’t want this to be the case for your company. Yet, from managing repetitive administrative tasks to ensuring personalized growth opportunities, leaders are stretched thin.

At Deel, our global experience shows that leveraging AI can empower organizations to tackle engagement barriers. Whether you’re an HR manager or a team leader, AI-powered solutions provide actionable insights and save precious time.

In this guide, we’ll walk you through seven popular applications of AI in employee engagement so you can learn how to use AI coaches, bots, and other processes.

What are the potential benefits of incorporating AI in employee engagement strategies?

Artificial intelligence is already used in HR for various use cases, including recruiting, onboarding, training and development, performance assessment, and more. One of the core use cases, though, remains employee engagement.

Not only can using AI improve employee satisfaction and productivity, but it also helps you ensure that you meet your people’s requirements (remote and onsite).

You can use AI-based HR tools to:

• Automate day-to-day processes such as feedback sharing or facilitating team member connections
• Automatic event scheduling reduces the burden on your HR team. This way, they can focus on the tasks that require human involvement, like one-on-one meetings or live coaching
• Streamline conflict resolution by providing objective third-party insights and improving learning and development initiatives. Specifically, these AI tools use existing employee data to make better employee training recommendations and connect specific employees to growth opportunities (like new roles or departments)
• Gain deeper insights into employee preferences and proactively address any discontent across the organization

Ultimately, AI can foster organizational alignment, help you retain employees, and improve future performance. That’s simply because you’ll have more time to dedicate to every person on your team.

Applications of AI in employee engagement

To start using AI solutions to improve employee engagement levels for good, let’s consider seven typical applications.

How to use them: Each artificial intelligence application and solution caters to a different need or challenge you’re dealing with or might bump into in the future.

Most AI-powered tools won’t be able to help you with all scenarios. So take the time to prioritize your immediate needs and gradually test these applications with your employees.

Chatbots and virtual assistants for employee support

Your HR team is asked the same questions dozens of times each week. “When’s open enrollment?” “How do I request time off?” “Who handles equipment requests?” Meanwhile, employees wait hours or days for answers to simple questions that could be resolved instantly.

AI-powered chatbots, like Leena AI, Happyfox, and Deel AI (although Deel AI is much more than a chatbot), completely change this dynamic. They’re available 24/7, never get frustrated with repetitive questions, and can handle multiple conversations simultaneously. Think of them as your always-on HR assistant that scales infinitely without burning out.

How to use AI chatbots and virtual assistants for employee support:

• Answer frequently asked questions
• Provide on-demand training and guidance
• Automate repetitive and administrative tasks
• Speed up communication between employees and HR

When to avoid using AI chatbots and virtual assistants for employee support:

• When an issue requires a personal touch or human empathy
• When a topic is highly complex and requires a high level of expertise or knowledge that cannot be provided by AI
• When an issue requires people to be physically present (like technical support)
• If you didn’t have the time or resources to train the bot properly

Sentiment analysis for monitoring employee satisfaction

Many times, the insights from traditional employee surveys get stale before you can apply them. That is where tools like Leapsome and Lattice, that monitor employee satisfaction, could help.

AI sentiment analysis monitors the pulse of your workforce in real-time. It analyzes communication patterns, email tone, chat messages, and feedback to spot satisfaction trends as they develop. You’ll catch problems while they’re still fixable, not after half your team has mentally checked out.

How to use AI for sentiment analysis:

• Collect data from employee feedback surveys, social media, and other sources
• Help managers find areas where employees are satisfied or dissatisfied

When to avoid using AI for sentiment analysis:

• If you’re unable to gather consent before collecting and analyzing employee feedback
• If biased results are likely to occur

Use case spotlight: AI-based sentiment analysis tools offer data-driven insights into employee sentiment and behaviors. Managers can use this data to examine their team’s preferences, motivations, and performance drivers.

Gamification to ultimately boost engagement

Most workplace motivation systems feel forced. Badges for attending meetings, points for submitting reports on time, and leaderboards that pit colleagues against each other. They create temporary excitement but don’t drive lasting engagement because they’re not connected to what actually matters to each person.

AI-powered gamification works differently. It learns what motivates each employee individually and creates personalized challenges that align with their goals and interests. The result? Game mechanics that feel natural and meaningful rather than gimmicky.

How to use AI for gamification:

• To create and maintain a rewards system
• To incentivize employees to complete tasks (e.g., by sending notifications when peers complete their tasks for a dose of healthy competition)
• To gather new (sometimes unique) data on employee behavior and preferences

When to avoid using AI for gamification:

• If gamification practices do not align with your company’s culture or values
• If the company or department is facing significant financial challenges

‍Personalized learning and development programs

Standard training programs treat all employees as if they learn at the same pace. As a result, some people get bored while others feel overwhelmed. At the end of the day, most learning content remains unused due to a mismatch between individual goals and learning methods.

AI personalizes the entire learning experience. It assesses each person’s current skills, identifies knowledge gaps, and creates custom learning paths. The system adapts as people progress, suggesting relevant content when they need it most. It’s like having a personal career coach who knows exactly what each employee should learn next.

How to use AI for personalized learning:

• Create individualized programs for each employee
• Gather data on employees’ skills and interests
• Find and recommend the best materials or activities to match the skills and interests of each employee
• Keep track of the employee development progress

When to avoid using AI for personalized learning:

• When the content of a learning program is sensitive or confidential and requires human discretion and judgment
• If the learning and development program is meant to build interpersonal skills or emotional intelligence (since human interaction is more effective in these cases)

AI-driven communication and collaboration tools

AI-enhanced communication tools actively facilitate better collaboration. They surface relevant information when you need it, connect you with the right people for specific questions, and help teams coordinate more effectively. The technology works behind the scenes to make communication smoother and more purposeful.

How to use AI-driven communication and collaboration tools:

• Improve communication efficiency and collaboration
• Automate repetitive or time-consuming tasks
• Analyze data and gain insights into employee engagement
• Provide customized feedback to your employees faster

When to avoid using AI-driven communication and collaboration tools:

• If you want to build a stronger sense of community among your employees, relying solely on AI-driven tools may not be effective
• If you can’t provide transparency in the communication process, your employees might not trust your AI tools

Use case spotlight: Set up communication training as your priority, and let AI record and track your team’s performance. An impactful communication training program will help your employees learn how to communicate effectively through methods like active listening or empathetic understanding.

Building an engaging onboarding experience

New hire onboarding typically follows a standard checklist for all employees. Read the handbook, watch training videos, attend orientation sessions, and hope for the best. By week three, most new employees still don’t understand their role clearly or feel connected to their team.

AI creates personalized onboarding journeys that adapt to each person’s background, role, and learning style. It delivers relevant information at the right pace, connects new hires with appropriate mentors, and tracks progress to ensure nothing falls through the cracks.

How to use AI for onboarding:

• To create highly personalized content in your onboarding checklist
• Provide real-time feedback
• When there are large amounts of data to handle, curate, and summarize
• If you need to automate repetitive tasks (e.g., sending new hires resources, setting up accounts)
• When automatically connecting employees to onboarding buddies
• For running a self-service center for new hire issues

When to avoid using AI for onboarding:

• If you need a human connection at every single step of the employee onboarding process
• If you haven’t had the time to test the AI-generated onboarding flow
• If your onboarding process involves highly technical or complex information

Recognition and rewards systems

AI-powered recognition systems spot patterns human managers might miss. They track contributions across different projects, identify when someone goes above and beyond, and suggest appropriate recognition opportunities. The result is more frequent, fair, and meaningful acknowledgment of good work.

Implementing AI in your recognition and rewards system will enable you to:

• Accurately track employee performance
• Send regular rewards or recognition cues to your employees
• Interpret performance data and offer recommendations for improvement (especially relevant when you’ve got large teams where manually keeping up with employee performance is impossible)

When to avoid using AI for recognition:

• If your team is generally hesitant to rely on artificial intelligence for decisions like these because they believe it’s not transparent or inclusive
• If you don’t have a person in charge of monitoring this system to ensure fairness

Use case spotlight: AI recommendations for growth based on past feedback results. For example, their last mid-year review highlighted a gap in presentation skills. In that case, they can get an automatic recommendation to sign up for a public speaking course.

The challenges and risks of AI in engagement

While AI offers tremendous potential for improving employee engagement, you must navigate several significant challenges to use it successfully.

Understanding the risks upfront can help you make informed decisions and develop mitigation strategies.

Employee skepticism about monitoring

Many employees worry that AI engagement tools are actually sophisticated surveillance systems designed to monitor their productivity and behavior. This skepticism isn’t unfounded: some AI tools do track employee activity in ways that can feel invasive.

Employees who don’t trust AI engagement tools will either avoid using them entirely or provide sanitized, inauthentic responses that defeat the purpose of gathering genuine feedback. The result is skewed data that does not accurately reflect actual employee sentiment.

Risk of bias in recommendations

AI systems learn from historical data, which means they can perpetuate existing biases in the work environment. For example, an AI system analyzing recognition patterns might learn that technical contributions get more praise than collaborative work. As such, it might recommend recognition for similar technical achievements while overlooking essential teamwork.

The bias risk extends to personalization features. AI might recommend different development opportunities to different employees based on biased assumptions about their capabilities or interests. These algorithmic decisions can reinforce inequalities even when human managers are trying to be more inclusive.

Over-reliance on automation vs. human connection

There’s a risk that managers might lean too heavily on AI insights instead of having direct conversations with their team members. An AI system might flag that someone seems disengaged based on their survey response. Still, only a human conversation can uncover the underlying issues and build the trust needed to address them.

Factors you should consider before investing in an AI engagement solution

Before you choose an AI engagement solution, take the time to test them all while keeping an eye on these seven core factors:

1. The return on investment (ROI): Will the AI tool you’ve picked save you money and time? How scalable is it? For instance, will it keep up with your needs as your business grows, or as your team’s size doubles?
2. Ease of use: Your team comes first. So you’ll want to ensure the platform and its integrations are easy to get accustomed to and use daily (if needed)
3. Analytics: Insights provide the capacity to measure success and identify areas for improvement. Some of the best AI and machine learning solutions offer real-time analytics that use past trends and data to predict future business outcomes
4. Key stakeholders: Think about everyone involved in using this app. Consider who will own it, who is in charge of managing day-to-day operations using the tool, and if any stakeholders should be informed, onboarded, and invested in this new addition to your tech stack
5. Ethical implications and bias: Make sure to take into account any ethical or legal consequences of using these AI tools
6. Building internal trust: This new tool is yet another addition to the various solutions that already occupy employees’ days. Hence, your team should understand the power of this app and how they can use it without wasting time or being distracted
7. Maintenance and support: Simply put, someone will have to manage all this. Prepare accordingly and ensure the solution you pick has a support team always available to help you fix issues or find new use cases

Engage your workforce with Deel Engage

AI solutions are here to help you keep your people engaged and enable HR professionals. Whether we’re talking about helping them gain new skills or just staying motivated, you can turn to a tool like Deel Engage to do it all. Our suite of tools lets you engage and grow your organization’s talent by:

• Getting people insights to help you engage meaningfully, spot and facilitate better development opportunities, and create stronger remote relationships
• Running training, one-on-ones, onboarding, and training faster with the AI assistant

Additionally, Deel AI is included with every Deel product, so you can get the answers you need faster than ever. Whether you’re stumped about local laws, want to generate a report, or need tech support, Deel AI is always ready to help.

Schedule a free demo to learn more about all AI functionalities of the Deel platform, and how they will help you manage and engage a modern global workforce.