Improving HR management with AI

- [Instructor] Small firms can leverage AI to optimize their HR and recruiting processes, leading to faster hiring, better candidates and lower costs. AI-powered tools can automate tasks like screening resumes, scheduling interviews, and even assessing candidate skills, freeing up HR staff and improving the candidate experience. By analyzing data and predicting candidate success, AI helps HR make more informed and efficient hiring decisions, as described in the AI Canvas. Let's start again with the first question. Who are the customers? The customers in this case are both internal and external. Internal are the hiring managers within the small firm who need to fill an open position, and externals are the job seekers and potential candidates for those positions. What are the customer benefits? Well, externally, the candidates benefit from a faster application process, a more personalized experience, increased transparency, and ultimately a better match of the candidate with the role. Internally, hiring managers benefit from reduced time to hire, improved quality of the hire, and decreased cost per hire. Also, they benefit from reduced administrative burden on HR staff. It also leads to more data-driven insights for improving the recruiting effectiveness in the long term. The third question asks what the workflow is. The AI Canvas illustrates that every single step in the recruiting process can be improved with generative AI. It is also important to notice that HR managers can gradually integrate AI, which is less risky than changing the whole process at once. For example, job posting optimization. AI can analyze job descriptions to identify language that might deter qualified candidates and suggest improvements for broader reach and appeal. Candidate sourcing. AI tools can automatically search online platforms, such as LinkedIn or other job boards, to identify and engage potential candidates who match the job requirements. Applicant screening. AI can screen resumes and applications to filter candidates based on qualifications, skills and experience, saving HR significant time. Candidate assessment. AI-powered assessments can evaluate candidate skills, personality traits and cultural fit through games, simulations and automated interviews. Interview scheduling. Chatbots can automate interview scheduling, reducing back and forth communication and saving times for both candidates and HR. Candidate communication. AI can personalize communication with candidates through the hiring process, providing updates and answering FAQs. Finally, onboarding. AI can assist with onboarding new hires by automating paperwork, providing access to resources, and answering initial questions. Let's move to the next question. What AI software and hardware is used? As in other cases, specialized vendors offer AI-based software integration and customization, and how do employees interact with AI? The AI solution will become an integral part of all communications between the HR team, the hiring managers and the job candidates. For example, HR professionals will use AI tools to manage job posting, screen candidates, schedule interviews and track progress. They will also need to train the AI systems and interpret the data provided. For the hiring managers, they will receive shortlisted candidates from the AI system, review AI-generated insights, and provide feedback to refine AI's recommendation. The data required are job descriptions, candidate data, historical hiring data, and available job market data. The next three questions we can address together. What capabilities and resource are needed and with whom can we have access to them? As with other generative AI use cases, small firms rely on their vendors to gain access to the required capabilities in terms of large language models, natural language processing and analytics. Specialized vendors offer AI-based software integration and customization that is compliant with local legislation. Potential partners include AI software vendors, HR technology consultants and recruitment agency that leverage AI and their services. Finally, what are the expected results? While the initial costs are not trivial, well-tuned AI-based recruiting processes will be more cost efficient and lead to better outcomes. In other words, the cost savings are indirect due to better hiring processes. The risks when using AI systems are data inaccuracy, biases in the recruiting decisions and when assessing candidates, and potential violations of privacy and data protection laws. HR processes are much exposed to those kind of risks and ethical violations than marketing processes, for example. There will be no direct revenue gains from optimizing the HR recruiting process. To summarize, all process that are data rich and require multiple conversations, like the HR recruiting process, can benefit tremendously from the systemic applications of generative AI. Small firms have access to these tools through specialized vendors who customize the AI use case to their specific needs. The most promising use cases for AI in every firm are related to data-rich processes. More specifically, the best use cases for generative AI are conversation-rich processes. Therefore, there should be no surprise that companies often start implementing AI to improve their HR and their marketing and sales processes.