AI Tools for Learning and Development: A Complete Guide for Businesses

AI creates pathways for every employee to learn. AI considers the skills, traits, preferences, and learning pace of each employee to support capability development and individual skills. This approach is clearly born out of a "one size fits all" approach to learning and training. Also, AI modifies the content delivered to each learner's specified learning expectations.

Interactive AI-enabled content enables employees to be engaged than with static training content. Gamification elements, engaging quizzes, and real-time feedback produce immersive learning experiences to motivate employees.

AI algorithms decide the best points for content presentation and where review sessions need to occur. By utilizing forgetting curves, AI tools will provide reinforcement when a learner is most likely to forget what they learned.

AI Tools for Learning and Development are able to deliver good rates, information about the training performance with data-driven insight, and skill gaps to help L&D managers.

Acting as a force multiplier, the cost to train employees significantly lower with automated content generation tools, automated scheduling, and less administration. AI removes the requirement of grading, content update, notifications and tracking course completion so the L&D team can focus on more strategic schools.

Major learning management systems (LMS) that allow for artificial intelligence in learning help to automate the assignments of courses, track learning progress, and pathways to potential learning based on employees performance & career ambitions. With the use of AI tools or engines, learning systems will continuously and automatically adapt to student learning styles.

These types of systems are essentially virtual coaches providing step-by-step directions and instant feedback. These systems may even find knowledge gaps & can adapt the level of difficulty in real time to maximally facilitate each employee's learning journey.

Content creation tools enable the automated generation of training, quizzes, and assessments via natural language processing (NLP). These tools can also auto-convert recent & existing documentation into interactive learning modules, & can create multilingual content at scale.

VR and AR technologies create immersive training environments for high-risk situations, and both technical skills and soft skills. These platforms allow practice in safe spaces, free of consequences.

AI chatbots support learning by providing 24/7 support to learners by answering questions, providing resources, and navigational guidance through learning pathways. They support employees in learning when there is a lack of availability of human trainers or immediate assistance is required.

Predictive models analyze employee performance data and propose forecasted learning and identify learners that are at risk of dropping out. They can suggest training or interventions to prevent performance problems from arising. Even when performance issues arise, research shows that being proactive prevents skill gaps from worsening and improves retention overall.

These tools continuously assess employee skills through OSINT and multiple other means, to then recommend the most relevant training programmes, career pathways, and other development opportunities, designed specifically for their individual learning pathway.

Docebo is a cloud-based LMS that leverages AI to personalize the learning experience for learners and automate some administrative processes. Their platform provides additional tools for creating content and an analytical platform with powerful insights into the effectiveness of workplace learning.

Coursera offers university-level courses with AI recommendations and skill assessments. The business HVAC integrates learning options to individuals based on their preferences and tracks learning progress by individuals in the same team.

EdCast is an intelligent knowledge cloud integrating AI-based opportunities to curate and deliver personalized learning content. The platform is cloud-based, integrates with existing enterprise systems, and develops social learning opportunities.

Saba Cloud provides AI-enabled talent development opportunities, including predictive analytics to identify employees with high potential and develop their talent

Skillsoft Percipio includes AI-driven content curation features and personalized learning channels that align to individual skill levels and individual learning intended outcomes.

Microsoft Viva Learning deals with Microsoft 365 to offer learning recommendations that surface right learning options right where employees are working, creating good & seamless opportunities for learning in context.

Evaluate current training obstacles, skill gaps, and learning objectives. Review existing data to evaluate where AI can have maximum impact and return on investment.

Decide on how to integrate incrementally while minimizing the disruption to on-going training programs. Ensure document/ data formats are compatible and establish migration plans for previously developed content and user records.

Intelligent systems index and organize easily-shared knowledge, and make it searchable for users. It identifies experts and resources relevant to the project and the required skills.

Begin by understanding current training pain points, the gap in skills, and the employee learning objectives. Consider using existing data to determine where AI in L&D will generate the most substantial return on investment.

Evaluate the following:

• Existing system integration
• Scalability and customizability
• User experience and ease of onboarding
• Available tech support and training resources
• Pricing structure and potential ROI

Map out a phased integration strategy that minimizes disruption to staff and existing training initiatives. Ensure data compatibility and have clear data migration processes for existing content and user data.

It will be helpful to start with simple metrics to track the implementation of the AI tool, including:

• Completion rates for learning programs.
• Skill assessments
• Employee engagement
• Time-to-competency
• Training cost per employee

As AI technologies usually require employee data from a variety of systems, it is prudent to adopt systems that perform strong security measures to protect the employee data and comply with processes such as GDPR and CCPA. Security audits and data governance will be necessary for your organization and vendors.

Companies need to weigh the skills or benefits of personalization against the need to secure employee privacy. Clear & transparent communication around data collection efforts proves crucial for building the relationship of trust with the employee.

Difficulty in getting buy-in for any sort of change to technology can be a barrier to a successful implementation of AI Tools under Learning and Development. This is where full-on Change Management is critical - be sure to have plans for the transition (i.e. training employees on the new tools, communication plans about the use of the tools, etc.).

AI systems and machine learning can easily reflect bias by virtue of how it was trained (including potential bias within the training data itself). A seemingly simple way to address these inequities is to periodically audit your algorithms, perhaps even mirroring practice from the employer and employee relationship of collective bargaining. Utilizing diverse data sources in your training data (i.e. avoiding singular identity representation) can also help ensure equitable and fair learning opportunities as well.

Implementation of AI tools may require significant initial investment, typically taking into account software development, implementation, and later, ongoing maintenance of the tools. Organizations should budget for both up front and future considerations for planning would be successful AI.

Looking forward, many AI Tools under Learning and Development will, by design, create a dynamic learning experience that will adapt as it receives real time performance data, employer retrospective learning journeys and industry trends.

Now that OpenAI has arrived and uses artificial intelligence, microlearning will be even more sophisticated with AI also developing learning modules of very short bites delivered at just the right time and right content formats.

Advanced AI Development Services will monitor emotional states, stress levels, and environmental aspects to adapt the difficulty of learning and provide appropriate help, enabling fulfilling learning experiences.

Artificial Intelligence will predict skills required in the future by market trends and will directly suggest reactive programs for precognitive training, allowing old employees to move to new roles and new technologies.