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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Workforce planning

Workforce planning

Introduction

Workforce planning is a crucial element of human resource management, aiming to align employee skills with organizational goals. However, traditional approaches often fall short due to incomplete data, inflexibility, human bias, and resource-intensive processes. These limitations hinder organizations from adapting to dynamic environments and making accurate, timely decisions. To address these challenges, machine learning (ML) and artificial intelligence (AI) offer a transformative approach, enabling workforce planning to become more data-driven, dynamic, and predictive. AI and ML integration into workforce planning systems addresses key challenges by leveraging advanced algorithms for data-driven decision-making, real-time analysis, and bias reduction. These technologies analyze vast datasets, including employee performance and market trends, to deliver precise and equitable workforce management. Automation features enhance cost-efficiency by streamlining manual processes, freeing resources for strategic initiatives. Adopting AI and ML allows organizations to create a more proactive and responsive workforce planning process, optimizing effectiveness and maintaining competitiveness in today’s fast-evolving business landscape.

Challenges

In the field of HR, there are several challenges that are encountered in workforce planning. Some of the challenges include managing diversity in the workforce, forecasting the future requirements of talent, maintaining top talent and adhering to legal requirements. However, one of the major issues that HR professionals face is the shortage of reliable and timely information to make sound decisions. Another issue is the human bias which can affect decision making and make it less detached. Also, the conventional workforce planning models are tedious and expensive and require a lot of effort and resources such as spreadsheets and manual computations.

AI Solutions

These challenges can be solved by AI and ML. There is a large amount of data that can be collected and analysed by AI algorithms, which can help in identifying the patterns and trends which would otherwise be difficult for a human to do. They are able to forecast future talent requirements as per market conditions, company expansion and employee turnover. ML is a branch of AI that uses historical data to make future projections as accurate as possible. For instance, it can estimate the employees who are most likely to quit the company, thus allowing for preventive measures to be taken. Also, AI can assist in managing workforce diversity and identifying where the gaps are and how to bridge them for a more inclusive workforce. Some of the HR tech companies include Eightfold.ai and Pymetrics that are using artificial intelligence to assist organizations with their workforce planning.

Benefits

There are numerous advantages of incorporating AI and ML in workforce planning. The features of these technologies are that they enhance the decision-making process and make it more precise and effective therefore reducing time and resources used. They enable proactive management of talent, thus enabling organisations to keep and seek the best employees. In addition, AI and ML can also enhance diversity and inclusion, thus increasing the overall engagement and productivity of the workforce. Furthermore, these technologies can also assist organisations in meeting their compliance requirements as per the labor laws by analysing the potential violations and providing possible solutions.

Return on Investment

It is possible to get a high ROI when implementing AI and ML in workforce planning. An article by Accenture states that AI has the potential of enhancing labor productivity by 40% and hence free up people’s time. This is supported by another study by McKinsey which claimed that AI could generate up to $13 trillion to the global economy by 2030 and most of it through increased productivity and performance. In addition, AI can minimize expenses linked to turnover, recruitment and non-conformity.