Should you use AI in learning and development?

According to research, companies that invest in an employee development strategy are twice as likely to retain team members. These businesses also report 218% more income per employee than those without.

At the same time, 84% of employees expect their organizations to provide them with education and training to stay current with changing skill requirements in their sectors. What’s even more telling is that three out of four employees believe they aren’t reaching their full potential. According to Lorman, only one-third of employees are “very satisfied” with the job-specific training they receive. 

Clearly, modern employees value learning and development opportunities. However, there is a considerable disconnect between what employers are offering and what employees want and expect.

Enter artificial intelligence (AI), which has emerged as a powerful tool for cost-efficient training and employee retention through L&D. Our guide outlines the pros and cons of AI in learning and development so you can identify when and how to integrate it into your talent management strategy.
 

What Is AI in Learning & Development?

AI in L&D encompasses the use of artificial intelligence, machine learning, natural language processing, and data analytics to facilitate learning automation at scale. 

By adopting AI-driven learning tools, leaders can analyze large volumes of employee data and create personalized learning path recommendations based on each person’s needs and professional goals.

Some of the most exciting applications for AI for employee training include the following:

• Personalized learning experiences
• Content creation and curation
• Skills assessment and gap analysis
• Learning path recommendations
• Progress tracking and analytics

When you use AI in learning and development, you can offer personalized learning experiences that empower employees and enhance overall business performance. AI tools allow you to align your training and development efforts with long-term business goals while promoting retention and productivity.

Pros of Using AI in Employee Learning & Development

Adaptive learning technology powered by artificial intelligence offers the following advantages.

Pro #1: Personalized Learning Experiences

Employees don’t want generic training sessions; they want content that is curated to their current roles and to their personal strengths, weaknesses, and long-term career goals. Personalized learning with AI ensures that every training session is relevant and engaging for participants. 

Suppose that one of your team members is struggling with a new project management role. An AI skills development platform could create a personalized learning path with micro-courses that address the team member’s specific weaknesses. The content would focus on areas where the person needs to improve rather than presenting them with generalized project management content. 

This tailored approach helps employees feel more engaged and supported in their professional growth. Managers benefit from having teams better equipped to handle their roles effectively. At an organizational level, personalized learning with AI leads to improved productivity and higher retention rates because employees see clear value in their training experiences.

Pro #2: Faster Content Creation and Curation 

Creating quality content is one of the biggest barriers to training and development. Traditional content creation processes are tedious and time-consuming, but 70% of business owners believe that artificial intelligence will speed up content creation. 

AI-driven content creation streamlines training development by automating many initial steps, reducing overall costs, and enabling organizations to quickly build extensive libraries of educational resources for their teams.

Using generative AI models trained on industry-specific data, modern L&D platforms can rapidly produce accurate drafts of training materials such as course outlines, instructional video scripts, tests and quizzes, skill assessments, and even interactive simulations. Subject matter experts then review these drafts for accuracy rather than starting from scratch, dramatically reducing turnaround times.

For instance, if your organization needs rapid deployment of compliance training due to new regulatory requirements or industry standards updates, AI can quickly generate initial drafts based on existing regulations and best practices. This faster content creation benefits HR teams by freeing up valuable time previously spent on manual tasks so they can focus more strategically on planning employee development initiatives. Employees benefit from timely access to relevant information without delays caused by slow manual processes.

Pro #3: Accurate Skill Gap Identification

Identifying skill gaps accurately across an entire workforce has traditionally been challenging due to limited visibility into individual competencies beyond basic performance metrics or subjective manager evaluations alone. Without precise insights into where each employee stands regarding critical skills required for success in their roles, or future roles, it becomes difficult for HR leaders to design effective development programs aligned with strategic business objectives.

An AI skills gap analysis reveals each person’s specific strengths and weaknesses. You can also use analytics tools to identify organizational talent gaps. To optimize the value of these insights, combine quantifiable performance data with other sources, including employee survey results and manager feedback. 

For example, Macorva Radiant AI aggregates manager notes, survey data, and employee feedback into a centralized platform. Our solution provides a real-time look into individual, department-wide, and organizational performance. For instance, if Macorva identifies that a sales team consistently struggles with customer communication skills based on customer feedback surveys and internal reviews, HR leaders can proactively implement targeted communication training programs specifically addressing these identified gaps.

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Use this information to guide your AI training implementation and curate each employee's learning journey.
 

Pro #4: Real-Time Feedback and Adaptive Learning

One of the most valuable advantages of AI for skills assessment is the ability to create adaptive learning paths. Employees will receive real-time feedback during training sessions, allowing them to better understand what information they are retaining. 

For example, imagine an employee completing a technical skills training module. With adaptive learning technology powered by AI, the system continuously assesses their responses during each session. If an employee struggles with a particular concept or skill, the AI automatically identifies this gap and adjusts future lessons accordingly, reinforcing challenging topics until mastery is achieved.

This real-time adaptability benefits employees by clearly showing them where they stand at any given moment in their training journey. Managers also benefit from having immediate visibility into each team member’s progress without waiting for scheduled assessments or reviews.

Pro #5: Cost and Time Efficiency

According to researchers, artificial intelligence can reduce training costs by up to 35%.  Research also reveals that AI learning programs improve training outcomes. AI-driven learning programs significantly reduce these costs by automating many of the repetitive tasks involved in content creation, curation, and delivery. 

For example, instead of manually developing onboarding materials for each new hire cohort, which can take weeks or even months, AI can automatically generate personalized onboarding plans based on each employee’s role, department, and skill level. Onboarding staff then only need to review and make minor adjustments rather than starting from scratch every time.

This streamlined approach saves HR teams considerable administrative effort, allowing them to focus more strategically on employee engagement initiatives rather than routine content creation tasks.

By cutting down on training expenses and enhancing learning outcomes, organizations free up valuable time and resources that can be reinvested into other strategic initiatives.

Pro #6: Improved Measurement and Analytics

AI learning analytics effectively measure learning programs by continuously tracking detailed metrics throughout each employee’s learning journey. These tools analyze data points such as course completion rates, quiz scores, engagement levels during sessions, time spent on specific modules, and even sentiment analysis from feedback surveys. This comprehensive data collection provides a clear picture of each employee’s strengths and weaknesses in real-time.

At an organizational level, improved measurement capabilities enable HR leaders to make informed decisions about future L&D investments based on concrete data rather than assumptions, ultimately driving better business outcomes through more effective employee development strategies.

Cons of Using AI in Employee Learning & Development 

As with any technology, there are some potential drawbacks associated with using AI in L&D.

Con #1: Potential Loss of Human Interaction

One of the most glaring concerns about AI-driven learning is the loss of human interaction. While AI excels at delivering personalized content and automating routine training tasks, it cannot fully replicate the value of human connection. Soft skills like leadership, empathy, and communication are best developed through interpersonal communication. For a comprehensive employee development program, consider a blended learning approach that combines AI with human-led training sessions. This hybrid model ensures employees receive both personalized digital content for technical skills and interactive experiences for soft skill development.

Macorva supports this blended learning approach by providing detailed analytics on employee strengths and weaknesses through Radiant AI. Managers can use these insights to identify precisely where human-led training interventions will have the greatest impact, ensuring your L&D strategy remains balanced between technology-driven efficiency and meaningful human interaction.

Con #2: Risk of Generic or Inaccurate Content 

While AI-driven learning platforms significantly speed up content creation, there is a risk that some generated materials may be overly generic or occasionally inaccurate. AI systems rely on existing datasets and patterns to produce new content automatically. Without careful oversight, this can result in training materials that lack specificity or fail to accurately reflect your organization's unique processes and standards.

Review any AI-generated materials to ensure they are relevant to your team members, and have a subject matter expert assess them for accuracy.

Con #3: Employee Privacy Concerns

Artificial intelligence platforms require an abundance of data, and AI L&D solutions need information about your employees. Some team members may be concerned about how their data is being collected, stored, and used. For instance, employees might worry that sensitive performance data could be misused or shared without their consent. These concerns can lead to decreased trust in your organization’s L&D initiatives if not proactively addressed.
Make sure to address these concerns head-on and be transparent about your data practices. Clearly communicate to employees exactly what data you collect for AI-driven learning programs and how you protect their privacy.

It's also important to select technology partners who prioritize employee privacy and data security. Macorva addresses employee privacy concerns by adhering strictly to industry-leading security standards such as SOC 2 certification and GDPR/HIPAA compliance. Additionally, Macorva’s platform ensures that sensitive employee information is securely managed within a protected environment where data is never shared externally or used beyond its intended purpose.

Con #4: Potential for Bias and Fairness Issues

Artificial intelligence systems can perpetuate underlying biases present in the data on which they are trained. Invest in bias testing to ensure any AI content or training materials don’t unfairly impact any demographics within your workforce. Be transparent about the results of your bias testing and what you are doing to fix any issues. 

It's also important to partner with a solution provider that proactively addresses potential bias. Macorva mitigates bias through built-in safeguards, including rigorous data validation processes and continuous monitoring of AI outputs to ensure fairness and accuracy. Explore our AI-generated Performance Review Workflow to see these safeguards in action.

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Con #5: Initial Investment & Implementation

Adopting advanced AI systems may require a significant upfront investment. Beyond licensing the technology, you'll also need to integrate it with your existing systems. Data silos and decentralized platforms can further increase integration costs and complexity.

Employees will also need focused training on the new system in order to make the most of your investment. While all of these costs should be considered, ROI projections should also include long-term savings in each area of implementation.

To mitigate these challenges, partner with a solution provider like Macorva that simplifies implementation through seamless integrations with existing HRIS and L&D platforms and intuitive user experiences. Macorva’s platform is designed for rapid deployment and includes built-in support resources to help employees quickly adapt, ensuring faster ROI and minimal disruption.

Con #6: Employee Resistance or Fear of Job Loss

According to recent research, about a third of workers say AI use will lead to fewer job opportunities for them in the long run, and 52% say they’re worried about the future impact of AI use in the workplace. Employees within your organization may share these sentiments, which can create change resistance and diminish the ROI of your new technology. 

Be proactive about addressing your team members’ concerns. Distribute anonymous surveys and hold town hall meetings to discuss your plans. Get line-level staff and mid-level managers involved in the decision-making process. During these meetings, emphasize that AI is meant to enhance the capabilities of your staff, not replace them.

When to Use AI in Learning & Development

Your business may benefit from artificial intelligence in L&D in the following scenarios. 

Scenario 1: Large, Distributed Workforce

The logistical barriers and costs of training a large team spread out across different locations can be formidable. Using AI makes it easy to provide your staff with high-quality, consistent training experiences. 

Scenario 2: High Volume of Training Content Needed

Do you have to frequently create and distribute training materials to update your team about regulatory changes or industry trends? AI helps you create content faster without compromising quality. 

Scenario 3: Data-Rich Environments

If your business already collects an extensive amount of employee data, it is in a prime position to implement L&D AI. Use your existing datasets to train AI tools and create better learning experiences for your team. 

Scenario 4: Technical and Procedural Training

Artificial intelligence tools excel at creating and delivering standardized technical and procedural training. A few examples include:

• Onboarding
• Compliance training
• Technical skills development

For the most common training needs, artificial intelligence platforms can automate much of the learning process while measuring each person’s progress. 

When Not to Use AI in Learning & Development

Here are some scenarios where it may not make sense to invest in L&D AI. 

Scenario 1: Highly Specialized Knowledge Transfer

Artificial intelligence is not capable of creating highly specialized training content, or at least not yet. In these scenarios, human-directed instruction is the superior choice. However, you can use AI to assist with knowledge assessment and progress tracking. 

Before investing in AI for L&D, consider the unique training needs of your workforce. You will likely find many instances where AI-directed L&D is a good fit, as well as a few areas where human-directed learning would be more practical. 

Scenario 2: Sensitive or Confidential Information

Training related to sensitive company information or confidential topics requires an extra level of trust and security. AI systems may not always provide the level of privacy required by regulatory bodies. 

Be very selective about what types of data you upload to AI platforms. It’s also important to choose reputable technology vendors whose security protocols align with your industry’s requirements. 

Scenario 3: Limited Technology Infrastructure

Implementing artificial intelligence requires a solid foundation of complementary and interconnected tools. Examine your current technology infrastructure; you may not have the supporting solutions necessary to implement an AI L&D platform. It’s also important to account for software upgrades and integration costs when planning your initiative. 

Scenario 4: Tight Budget Constraints

The initial investment for AI systems is prohibitive for some organizations. Companies operating under strict budget constraints may have a tough time justifying the upfront expenses. While AI L&D tools will deliver a strong ROI, it will take time to realize those returns.

Implementation Best Practices  

If you are ready to explore artificial intelligence for employee training, a thoughtful and strategic implementation plan is vital. Here are some best practices to guide the process. 

Start With a Pilot Program

Before rolling out AI across your entire organization, begin with a pilot program. Choose a small group of employees or a specific department to test the AI-driven learning solution. A pilot program allows you to assess the effectiveness of your initiative and address any issues before scaling up. 

Ensure Transparency 

Keeping your AI L&D program under wraps can fuel employee concerns and feed the rumor mill. Proactively mitigate these issues by being transparent about the scope and goal of your AI learning and development strategy. 

Outline how you intend to protect worker privacy and highlight the fact that AI is meant to enhance the employee experience, not replace your team. 

Maintain Human Oversight

Digital tools are meant to complement the value your team adds. Focus on solutions that provide your leadership team with direct oversight while making performance management more efficient. 

For example, Macorva MX empowers your management team with customizable dashboards and automated performance resources. Your leadership team can focus on what matters most and alleviate the burden of tedious administrative tasks with Macorva MX. 

Measure Results

Identify what key performance indicators are most relevant to your AI training initiatives. Consider focusing on these metrics:

• Course completion rates
• Performance improvements
• Employee engagement levels
• ROI

Each KPI provides a piece of the puzzle. Use them to identify the impacts of your AI L&D program at the employee, departmental, and organizational levels. 

Create a Hybrid Approach 

Rather than viewing AI as a replacement for human instructors, position it as a tool that enhances overall training processes. Combine AI’s data-driven insights with traditional learning methods to provide employees with a well-rounded foundation for success.

FAQs

As you consider these best practices for implementing AI in your learning and development strategy, you might still have some questions about how AI fits into your overall employee training approach. Here are answers to a few common questions HR leaders often ask about using AI in employee learning programs:

In the next blog in this series, we’ll take a closer look at how to successfully implement AI in your L&D programs, with practical steps to ensure a seamless rollout that maximizes impact and minimizes disruption.

Elevate Employee Learning and Development With Macorva

To incorporate artificial intelligence into a learning and development strategy, leaders must take a nuanced approach while addressing common challenges such as privacy concerns and potential bias. The key to success involves choosing the right technology partners and treating AI as a complementary tool, not a replacement for workers. 

If you are ready to explore the potential impacts and benefits of AI in L&D, connect with Macorva and book a demo today. 

Additional resources on AI in learning in development:

• Trend Report: The Latest Trends in Learning & Development
• On-demand Webinar: Leveraging AI for Personalized Learning & Development