Business leaders are leveraging artificial intelligence to use ongoing employee feedback and recommend development opportunities. This helps enterprises fill skill gaps while ensuring employees continue to grow
In 2020, LinkedIn published a workplace learning report, according to which 94% of employees would stay at a company longer if it invested in their learning and development. In a work environment that becomes more competitive by the day, employees seek constant training and upskilling to remain in the race.
What does this mean for organisations? The best way to retain your employees is to offer them the learning they might be looking for in other places. But how can these programs be custom-made to suit the different minds in large teams?
Some companies have begun using artificial intelligence to offer personalised learning experiences. Walmart uses an AI-powered platform, “Axonify,” to provide personalised training to its employees. Axonify analyses employee performance data to create training plans and recommends learning content based on individual needs.
In a given workforce, once can spot varied mindsets and experiences; the learning needs will also differ for this spectrum of people. For instance, somebody with a significantly long work experience might utilise their preexisting knowledge to build further open. At the same time, the previous knowledge might even be the home to biases and assumptions. A younger employee would have a different perspective — they’ll be more open to consuming what they get. The more senior employees might exhibit resistance to new ways.
These cases support the need for personalised strategies for employee enterprise learning programs.
Align with Learning Goals
Personalisation is critical to effective learning, especially in an enterprise setting where employees have different job roles, skill levels, and learning styles. The scalability of such a programme can be challenging, but AI eases its management. An enterprise can design a course in several steps:
- Collect data: The first step is to gather data on each employee through surveys, employee feedback, and analytics tools. This could include their job role, past training history, performance data, and learning preferences.
- Analyse data: Use machine learning algorithms to analyse the collected data and identify patterns and insights related to each employee’s learning needs and preferences. This involves identifying relevant features, selecting the appropriate machine learning model, training the model, and evaluating its performance.
- Develop personalised learning plans: Based on the analysis, AI algorithms can recommend specific learning content, formats, and delivery methods for each employee’s needs. This could include recommending courses, modules, or videos aligning with their learning goals.
- Deliver personalised content: Once the learning plans have been developed, deliver the content to employees through online platforms or learning management systems. AI can help optimise content delivery by recommending the most effective method based on the employee’s learning preferences.
- Monitor and adjust: Monitor employees’ learning progress and adapt the learning plans and content as needed. AI can help identify areas where employees struggle and recommend new approaches to address these issues.
Learning analytics helps educators and learners make more informed decisions about teaching and learning, leading to improved outcomes and better experiences.
Design and Delivery
Designing a learning funnel and delivery involves a systematic process that ensures the learning experiences are effective, efficient, and engaging. A step-by-step process includes the following:
- Determining learning goals: The first step is to identify the learning goals for the training programme, for example, defining the skills, knowledge, and competencies employees must acquire.
- Developing learning objectives: Once the learning goals have been identified, develop specific learning objectives that align with the goals. These objectives should be measurable and include specific outcomes that employees should be able to demonstrate after completing the training.
- Content and delivery methods: The content should be engaging, interactive, and aligned with the learning objectives. Delivery methods could include e-learning modules, instructor-led training, videos, and simulations.
- Creating a learning funnel: A learning funnel is a process that guides learners through the training program, starting with basic knowledge and gradually building on more complex concepts. The learning funnel should be designed to support the learners and ensure they can apply what they have learned to their jobs.
- Assessing learning outcomes: Regularly evaluate the effectiveness of the training programme by measuring the learning outcomes against the learning objectives. This can be done through quizzes, assessments, and evaluations.
- Continuous improvement: Based on the assessment results, make necessary adjustments to the learning content, delivery methods, or the learning funnel to improve the programme’s effectiveness.
Help Eliminate Skill Gaps
Personalised learning programmes in the workplace create a culture of continuous learning and development. AI provides ongoing employee feedback and recommends development opportunities to help them fill skill gaps and continue to grow in their roles.
For instance, AI-powered adaptive learning platforms adjust the difficulty level of learning content and assessments in real time based on the learner’s progress and performance. This ensures that employees are challenged appropriately, allowing them to learn at their own pace and reducing the risk of skill gaps.
Similarly, AI algorithms analyse employee performance data and recommend additional training and development opportunities. Personalised feedback on performance from AI-powered chatbots and virtual assistants helps identify areas for improvement.
Towards a More Engaging Workforce
Employees feel valued and invested in their professional development with personalised learning experiences, resulting in increased motivation, productivity, and job satisfaction. Additionally, AI-powered learning programs can provide real-time feedback and progress tracking, which can help employees stay on track and feel a sense of accomplishment as they progress towards their learning goals.
Personalised learning can help employees feel more connected to their organisation’s mission and values by offering content that aligns with their career goals and the organisation’s objectives. According to research, 77% of learning and development professionals believe personalised learning is critical to employee engagement. This leads to a more engaged and committed workforce better equipped to contribute to the organisation’s success.
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