What is a really useful AI project?

by bold-lichterman

Preamble: This article is not intended to enter into the debate on the ethics of the subject, for the moment. He strives to remain factual on the reflections that HR departments are currently carrying on the subject. The next articles will focus on a few players in the course of experiments (Large groups and Startups) and the last will conclude the series by questioning the very ethics of uses. Good reading !

Since artificial intelligence seems to help us in all areas of daily life – from the simplest Google search to buying a plane ticket for our next vacation, it would seem natural to make professional use of it too. , in particular to simplify HR processes within the organization.

Source profiles, identify employees likely to leave the company, automate the response to simple requests … The uses of artificial intelligence for the benefit of HR seem endless … and with more and more data integrated into HRIS, we could believe that any organization is ready to embark on a big data project and harness the power of artificial intelligence. But is this really the case?

Is all the data good to process?

Yes and no. We often talk about smart data rather than big data, it’s up to you to define which data will be really useful depending on the use you want to make of AI. If your goal is to let employees manage their leave more independently, the priority will be for the tool to have access to each person’s calendars and days of leave. If you want to find the perfect candidate internally for the position of marketing director, consider giving the tool access to the skills and qualities of each person, but also to any information that may be an indication of their success in this position. It is in the definition of utility that your most delicate task lies: you will have to both ensure the usefulness of the information taken into account (but be careful of the links that you would not have imagined and the tool will locate better than you) and the accuracy of the information entered. Be careful not to go overboard though: you don’t legally have the right to use certain data – such as the time spent by an employee on software – even if they could be very useful to you.

Are all the tools right for us?

As at all stages of the transformation, the application of artificial intelligence requires careful consideration. Everyone talks about a chatbot, but do you really need chatbots? Wouldn’t it be better to create a search engine that lets everyone access the content they need, seamlessly, in a few keywords? It’s up to you to think – depending on your objectives – on how you can simplify the lives of your employees to enrich their relationship with the HR function and how you can also simplify the work of HR. What if your tool showed you all the profiles that can evolve and be promoted when you look for “purchasing director”? We forget about plug and play and the tools that have infinite amounts of possibilities and we prefer tools whose algorithms really correspond to the needs of the organization and its employees.

We measure our results

If you have chosen a system that offers employees the training they need, your indicator of success will be the increase in the skills of the organization. But the results of the implementation are not always measurable in such a direct way. On the other hand, the level of employee satisfaction with a particular HR process or the possibility for your HR managers to have more time for in-depth reflections are very good indicators, which translate in the long term into a higher retention rate. high, more initiative and easier recruitment.

Just as you took your time to develop new training plans or change payroll software, AI takes time to think. It’s up to you to determine your needs and see how other organizations have responded to them … and don’t forget that if your employees are internal clients, it can be interesting to see how the communication and marketing departments use the artificial intelligence to meet the needs of external customers!

The contributor:

Reverse mentoring couples of a few months that influence a

Jean-Noël Chaintreuil is the founder of Change Factory, a laboratory for acculturation and support for change where people are at the center.
The main missions are the understanding of cultures, support for Comex, cultural transformations and the implementation of disruptive strategies.

He also works at various universities (La Sorbonne, Sciences Po, Berkeley, Dauphine, Sorbonne Abu Dhabi, etc.) on the future of work, human resources, cultural transformations and supports intrapreneurship programs.

You can find his articles on Quora: https://fr.quora.com/profile / Jean-Noel-Chaintreuil, Twitter: @jnchaintreuil or LinkedIn: https://www.linkedin.com/in/jnchain winch/ – on the themes of the future of work, entrepreneurship and intrapreneurship, human resources and the cultural impacts of digital.