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.

Drivers of change

1. The rapid advancement and accessibility of generative AI technology and tools.


2. The increasing demand and expectation for efficiency, productivity, customization, and innovation in HR functions and activities.


3. The changing nature and composition of work, talent, roles, and skills in the digital era.


4. The emergence of new regulations and guidelines for responsible AI usage in organizations.


5. The development of new competencies and mindsets for leveraging generative AI in HR.

Key uncertainties

1. The level of awareness and understanding of generative AI among HR professionals and leaders.


2. The degree of adoption and experimentation of generative AI tools by HR professionals and employees.


3. The quality and accuracy of the outputs generated by generative AI tools.


4. The ethical, legal, and security implications of using generative AI tools in HR.


5. The impact of generative AI tools on the role, function, and skills of HR professionals.

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.

Scenario 1: Fully Dive In - Generative AI Accelerates HR Transformation

HR professionals have widely adopted generative AI to maximize efficiency, productivity, customization, and innovation in their various functions and activities. These tools are used to create and refine learning content, write job descriptions, draft company policies, design interview questions, and provide personalized feedback and career recommendations. Furthermore, the professionals collaborate with other departments to ensure a secure and transparent governance framework for using these intelligent algorithms, such as protocols for security and privacy, data ethics principles, accountability mechanisms, and feedback loops. Moreover, effective learning and development programs are designed and implemented to help employees acquire the necessary skills and competencies to leverage generative AI in their work. Ultimately, these initiatives have positive outcomes for both HR professionals and employees, saving time and money, reducing human error and burnout, and increasing job satisfaction, retention rates, performance levels, and innovation capabilities. With this quick and wide adoption of generative AI in HR, other HR transformation activities are been greatly accelerated.

Scenario 2: Wait - Generative AI Creates HR Disruption

In this scenario, employees are rapidly adopting generative AI tools, using them for work purposes without seeking any guidance or oversight from HR professionals or leaders. They use generative AI tools to augment their tasks or projects without considering the quality or accuracy of the outputs, or the ethical or legal implications of their actions. In some cases, they use generative AI tools to bypass or manipulate HR processes or policies without being detected or held accountable. Furthermore, they do not share or disclose their usage of generative AI tools with their managers or colleagues unless they are required to do so, nor do they seek or receive any training or support on how to use generative AI tools effectively and responsibly. Ultimately, this can lead to a variety of negative outcomes for both employees and HR professionals, such as increased data privacy risks, increased bias/discrimination issues, compliance violations, increased conflicts or disputes, increased turnover rates, decreased trust levels, decreased performance levels, and decreased innovation capabilities. This scenario has a disruptive effect on HR as a whole, as it is not involved in the adoption of generative AI by employees.

Scenario 3: Cautious Steps - Generative AI Faces HR Resistance

In this scenario, HR professionals have adopted generative AI cautiously, using it sparingly and selectively for only certain low-risk tasks or projects, and not exploring the possibility of using it for other HR functions or activities. They have resisted or rejected initiatives or proposals that involve generative AI usage, have not communicated or collaborated with other functions or departments regarding governance and strategy, and have not invested in any learning and development programs related to generative AI. As a result, both the HR professionals and employees have missed out on the potential opportunities and benefits of generative AI, such as cost and time savings, enhanced equality, reduced human error and burnout, increased data privacy, improved job satisfaction, and performance levels, and increased innovation capabilities. Despite the cautious approach, this can have a negative impact on the business strategy if a certain threshold of collaboration and risk is not exceeded.

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.