The Use of Generative AI in HR
In the Middle Eastern folktale “One Thousand and One Nights”, Aladdin, a poor young man, comes across a magical lamp in a hidden cave. A powerful genie appears when he rubs the lamp and grants him three wishes. Aladdin uses the genie’s power to improve his life and win the heart of Princess Badroulbadour.
In other folktales, genies are less helpful. Some interpret a wish by its exact words and not by its meaning. There are genies with a trickster nature, enjoying the chaos when manipulating the wisher. And there are those that challenge people to think carefully about their desires and the potential ramifications.
The newest genie out of the bottle is generative AI. It’s a good comparison because of its immense power, the necessary care in conversations, ironic or harmful outcomes, the ethical complexity, and the far-reaching consequences. How will this genie influence the work in human resources?
Why Generative AI Is Important for HR
We are looking at generative AI from an HR perspective. It’s particularly complex because HR professionals not only have to figure out how to use it themselves. They also have to manage how it changes everyone else’s work in their organizations. But there are some safe assertions that we can confidently make.
- Assertion Nº 1: Generative AI is a powerful and accessible technology that can create various types of content, such as text, images, audio, video, and code, based on prompts or queries.
- Assertion Nº 2: Generative AI has a dramatic impact on the world of work, as it can enhance efficiency, productivity, customization, and innovation in various HR functions and activities.
- Assertion Nº 3: Generative AI adoption is fast and widespread. Many employees already use it for work purposes, regardless of organizational policies or leadership perspectives.
- Assertion Nº 4: Generative AI poses significant opportunities and challenges for HR, such as enhancing employee experience, learning and development, talent acquisition, and people analytics, but also raising ethical, legal, and security issues.
The potential is clearly immense. It can be used by people with any education level, anywhere in the world, and with any job. OpenAI research suggests that 80% of all jobs will be impacted in at least 10% of the tasks. This means that the large majority of people will blend technology into their workflow which changes how they are doing their jobs, their efficiency, relationships, and outcomes.
HR needs to prepare and prepare rather quickly. But before we think about how we need to define the what.
It’s Not How We Prepare, but What We Prepare For
For example, generative AI can help draft company policies that are aligned with the organization’s vision, mission, and goals. But it’s not clear how AI can incorporate the culture and context of the organization. AI can’t be made accountable.
Or think about job descriptions. Generative AI helps write effective job descriptions that attract and retain diverse talent. But it faces limitations in ensuring consistency across the organization, avoiding bias, and capturing the company culture. It is not clear which human intervention is needed.
It is also unclear how it can be applied to create learning content. It creates engaging and personalized learning experiences, such as courses, quizzes, or videos. But the accuracy and relevance for a specific job are not necessarily respected. Moreover, it cannot replace the human element of learning, such as feedback, coaching, mentoring, and collaboration. The human element might well become more important.
Generative AI will not develop linearly. Just like in any folktale, there is usually a twist to the story. How can we find out for which reality HR needs to prepare?
The Drivers of Change and the Key Uncertainties
To make predictions about the development of generative AI in HR, we engaged in scenario planning. In the first step, we identified the key uncertainties and the key drivers of change to generate plausible and coherent scenarios based on different combinations of these factors.
In a second step, we tested the World Economic Forum toolkit for the responsible use of AI-based tools in human resources. This was specifically important for us because we believe managing people carries a special responsibility in using generative AI ethically correctly. The WEF’s checklists don’t provide a glimpse into the future. But they provide additional ideas, potential roadblocks, and possibilities through the verification of sample HR tools.
Thirdly, we looked at predictions and declarations of other thought leaders in the space. To name just a few, Lareina Yee, chair of the McKinsey Technology Council, co-authors the wonderful podcast Generative AI and the future of HR. Josh Bersin, founder of the consultancy of the same name, and author of the article The Role of Generative AI and Large Language Models in HR, analyses new emerging generative AI tools for HR purposes. Jennifer Rozon, president of McLean & Company gives valuable guidance for HR professionals, i.e., how HR Departments Can Help Organizations Capitalize On Generative AI. Or Matissa Hollister, a fellow at the World Economic Forum and leader of the Human-Centred AI for HR project, which produced the Artificial Intelligence for Human Resources Toolkit.
Three Scenarios for the Near Future of Generative AI in HR
Additionally, to external data and ideas, we looked inside and drew on the combined experience of our consultants. We created a long list of the most likely combinations of the change-drivers and the uncertainties. We identified textual intersections and temporal overlaps to combine, delete, or detail them. As a result, we created three coherent and plausible scenarios, that provide a practical starting point.
What Do the Scenarios Mean for the Contribution of HR to the Business Outcomes?
The takeaway from all three scenarios is that if us HR professionals want to keep contributing to business outcomes, we need to proactively embrace the potential of generative AI. We also need to ensure responsible implementation and transparent governance. But it’s clearly not easy.
We need to upskill ourselves and the workforce. We need to experiment, monitor, measure, and collaborate with other functions. We need to pay attention to organizational culture and to the impact on job design, workforce structure, and pay. We have to figure out the best path to get there, while we’re on it.
- Assertion Nº 5: We can count on the support of the powerful genie generative AI if we upskill ourselves and our workforces, if we collaborate, and if we responsibly embrace it through culture and governance.
- Assertion Nº 6: The genie helps us to truly interlace people and technology for value creation. We can advance how work is being done in our organizations, with positive effects on employees and outcomes.
The first step on the path is training and experimentation. Because (for now) it’s not more data that produces valuable results, it’s the tested prompts of your employees that encode their expertise and can be shared among them.