When people say we should use generative AI to help us with uninspiring, repetitive, monotonous tasks, so we can save time for more strategic, imaginative or humane parts of our jobs, it sounds simple. So you open your favorite AI model (probably a free version) and then what? You know your job inside out, but you're pretty much clueless about what AI can and can't do and how to use it to get some real quality help? Not always easy.

If you're an HR professional, for example. As we all know, HR is about listening and communication, coaching, empathy, leadership… True. But it is just as well about procedures, administration, staring at the data, maintaining records and reporting, coordinating things, keeping an eye on policy changes… HRs could also use some help from AI, right? 

There are many products already on the market that employ AI to help HR - from scanning CVs, video interviews and talent databases, via education and training recommendation software to predictive analytics related to engagement and retention of employees, strategic planning using large datasets... Look it up. But what can you do with readily available GenAI models you most probably already use?

HR experimented. Got some ideas. Talked to engineers.

We wrote about our AI-Forward strategy, an internal tool called HAIP we developed for people to feel safe and experiment with GenAI, because they will be the ones with the best ideas on how AI can help them (here - link)... Well, it worked. 

Our HR experimented. Got some ideas. Called our engineers, talked about it. We shared the initiative with friends in the HR community. Together, we came up with some useful tips. We will show you how we, using HAIP, have started solving three examples of real problems common in HR - to demonstrate what's possible. Here they are:

1. Procedure Buddy

Never mind the naming. To ensure clarity in operations, define responsibilities, identify necessary roles, outline required tasks, etc., all to improve daily business functions, it is sometimes necessary to write procedures. The task often requires specific knowledge, focus, a bit of research, some thinking, and adaptation to the company and context. The idea is to save time with AI by asking it to generate a draft version of the procedure on a given topic, which will include predefined segments such as objectives, purpose, stakeholders, step-by-step flow, timelines, etc., which we can then customize and fine-tune. Take a look:

2. Goodbye Guru

People leaving the company can be a treasure trove of valuable information. When someone is leaving, we have an exit interview. This often includes a questionnaire, but the real value lies in the information we get in the conversation. To summarize it, analyze, and draw conclusions often involves a lot of effort and time, especially due to the qualitative nature of the data. The idea here is to use HAIP to generate a report that will contain summarized data on the reasons for leaving, the demographic structure of those leaving, employees' recommendations on what could be improved, suggestions for interventions.... Here it is:

3. Welcome Pilot

When a new employee is about to join us, since we already have all the information about the person's position (job description, seniority, team, role and responsibilities, benefits...), we asked HAIP to automate the onboarding process for us, but in a way that helps it remain customized and specific for each person and position. The idea is to get an AI-defined onboarding plan that will save us time, but still keep it humane and personalized, instead of uniform. See how it works:

Onboarding AI in HR

As we said, these are examples, hints at what you can do, ways you could think when in front of a prompt box. 

Still not sure the effort is worth it, in a profession so focused on people? AI is the major disruptor of markets, industries and skill sets. We're not saying it's time to panic, but nine out of ten information workers use generative artificial intelligence in their jobs, and the majority are satisfied with the results (according to McKinsey - link). Global adoption of AI technologies by organizations is expected to grow rapidly, with an average annual increase of 36.6% from 2024 to 2030. (Grand View - link). 

Here are just some of the reasons you should start experimenting with it right now:

Skills transformation

AI is redefining key skills for new employees. 

Actual use of AI

Employees are already using AI, regardless of company policies. 

Access to information

Everyone now has access to centralized sources of knowledge.

Empowering people

Power of AI is shifting from the IT department to the hands of every employee.

AI in daily work

AI tools can make your tasks easier. 

Understanding through practice

Use AI to better understand its impact.

There's no AI without I  

The main concerns with the use of GenAI are well known: privacy, questions of permanent storage of entered data, bias in training data reflected in the results, fake voice and video, hallucinations… But there is one we'd like to stress out: overreliance. 

Once you master AI tools, their growing power can be captivating. When your to-do list is crammed, it may appear to be an easy solution. We don't recommend using it to do your job instead of you. Use it as your assistant, not the other way around. Overreliance on AI can lead to stagnation in professional development and lack of critical thinking. It can not replace your experience, understanding of social contexts, exchange you have in your team...