Artificial intelligence and machine learning are both being increasingly used in human resources management because of the benefits they possess. 

The reality is that AI and machine learning are tools that HR officers use for hiring, retention, and employee development.

HR leaders can leverage AI and machine learning to transform and automate the employee onboarding process.

Read: Talking with your AI: have you mastered your prompts lately?

Indeed, to ensure a streamlined and productive employee onboarding process, it's essential to harness cutting-edge technologies such as Generative AI and Conversational AI, as well as utilise translation and localisation services. 

Additionally, incorporating strategies like nudge-learning, microlearning, game-based learning, performance management, and feedback mechanisms can significantly enhance the onboarding experience.

Why using AI and machine learning are vital for a great employee onboarding experience

Based on data from the Society for Human Resource Management (SHRM), Bamboo HR, Gartner, and various research findings, here are some intriguing statistics underscoring the significance of effective employee onboarding:

Retention rates. When employees have a positive onboarding experience, 69% of them are more inclined to remain with the company for a duration of three years.

Structured onboarding. An impressive 58% of new employees exhibit a higher likelihood of staying with an organisation for over three years when they have undergone a well-structured onboarding program.

Productivity boost. Organisations witness a remarkable 50% increase in new-hire productivity when they implement a standardised onboarding process.

Early attrition. In contrast, organisations with inadequate onboarding durations or insufficient training and support experience a concerning 31% attrition rate among new hires within their first six months of employment.

Cultural connection. Demonstrating the importance of company culture, a substantial 91% of employees who receive training on company culture report feeling a strong sense of connection to their workplace.

Read: Will you need mandatory basic generative AI training in the next five years?

7 ways AI and machine learning can help you onboard new staff effectively

AI and machine learning (ML) have revolutionised the transformation of customer and employee engagement. These advanced technologies offer numerous opportunities for enhancing the employee onboarding process through automation. According to a survey conducted by Leena AI, 68% of companies are already integrating AI into their recruitment and employee onboarding practices.

Here are several examples of how AI can be used to automate and expedite employee onboarding, along with the benefits it can bring:

Sentiment analysis. Employing natural language processing, AI can analyse employee feedback and sentiment throughout the onboarding journey. By tracking employee sentiments, HR can promptly identify concerns or areas for improvement, facilitating necessary adjustments to enhance the overall onboarding experience. This can be achieved through natural language understanding and the analysis of open-text feedback, providing deeper insights into employee feelings.

Personalised onboarding plans. AI-driven algorithms can automate the creation of personalized onboarding plans for new employees. By analysing individual profiles, encompassing skills, backgrounds, and job requirements, AI can recommend tailored training modules and resources to help new hires acclimate efficiently and effectively, fostering a sense of belonging within the organization.

Virtual assistants and chatbots. AI-powered virtual assistants and chatbots offer real-time support and answers to common queries during the onboarding process. They guide new employees through paperwork, offer information on company policies and procedures, and assist with various onboarding tasks. This not only improves the onboarding experience but also lightens the workload on HR staff, as these AI solutions are available around the clock.

Predictive analytics for role fit. Predictive analytics aids in automating employee onboarding by forecasting the impact of HR policies on employee well-being and overall performance. By analysing historical employee data, including performance metrics, skills, and experience, AI algorithms can identify patterns and predict the likelihood of success in specific roles. This helps HR make informed decisions when assigning new hires to positions, increasing the chances of a successful onboarding experience and reducing turnover.

Read: How small and midsize businesses can maximise AI for growth

Performance monitoring and feedback. AI and ML can monitor employee performance during onboarding by analysing various data points such as project progress, task completion rates, and customer feedback. This enables timely feedback and support, allowing supervisors and HR teams to identify issues or areas for improvement early on.

Gamification and interactive training. Gamified and interactive training can make onboarding more engaging and efficient. AI can be employed to create gamified onboarding experiences, including interactive modules, simulations, and quizzes. These methods boost engagement, improve productivity, enhance retention, and facilitate knowledge transfer. AI algorithms can adapt training content based on individual progress and learning preferences.

Nudge-learning for key moments. AI-based nudges can assist new hires and organisations during critical moments of onboarding. These nudges might include reminders to complete specific training modules, prompts to review important policies or procedures, and suggestions for connecting with key colleagues or resources. Personalised nudges can be based on individual employee characteristics, such as role, department, skill level, and learning preferences, reinforcing learning and knowledge retention.

These examples illustrate the potential of AI and ML in automating and improving the employee onboarding process. The specific applications and techniques used will depend on an organisation's unique needs, available data, and technological capabilities.