Generative AI

Leaders have long perceived Human Resources as a slow-moving piece of their organization. In recent years, there's been a reevaluation of talent teams and they've been granted a more strategic role. Today, Human Resources is a critical piece of any organization. There's a lot of pressure on teams to deliver meaningful results. Traditionally, the labor-intensive activities of talent teams slowed down their ability to make quick progress. That's changing very fast with the introduction of generative AI.

The trending term GenAI stands for generative artificial intelligence. It's a machine learning model trained on existing data to introduce new data. It specifically seeks to create objects that look like the data the model was trained on. The most popular examples of GenAI are generating text or images. Think of ChatGPT and DALL-E. Objects generated through the machine learning model share the same characteristics as the input data. It explains why a requested text looks like any other text on the web. While the hype around the technology is relatively new, the research goes back decades. A majority of people and organizations have started experimenting with and adopting GenAI, but the technology isn't bulletproof. The output often contains mistakes. A good example of this is the viral AI-generated images of persons with too many fingers or teeth. The mass use of generative artificial intelligence has, however, enabled AI developers to optimize their models for more accurate results. What makes GenAI special is the unmatched speed at which it provides the requested new data. That is something humans cannot replicate.

The impact of generative artificial intelligence on the workplace is immense. Submitting one well-formulated prompt significantly reduces the time spent on an activity. Information that would take humans months or years to analyze takes seconds to be scrawled by GenAI. At the same time, the activity of creating and formatting the output is taken over by the technology. It shifts the workers' efforts from research and development to formulating clear objectives, reviewing output, and applying corrections. This is a big win for organizations that want to automate activities that do not require specialized work. According to data by the McKinsey Global Institute (2023) these types of activities make up 30% of hours worked across the United States economy. The organization estimates that the percentage of task hours to be automated will continue to rise. Through the use of GenAI, leaders can leverage an opportunity to reduce resources spent on mundane repetitive activities and invest in training more specialized resources for jobs that require creativity,  business or legal acumen, or STEM skills.

GenAI affects all business units. Talent teams can be among the biggest beneficiaries. Every employee engages in activities that can be automated. Yet, human capital has long been rooted in administrative work. As these teams transition to a more strategic role in their organizations there's a profound need to automate. The potential impact of generative artificial intelligence on HR teams is substantial. According to the Boston Consulting Group (BCG, 2023), GenAI, in the near term, can drive 30% increased productivity across the HR value chain. The influence of generative AI on HR self-service and open-access information reduces employee request approval times by as much as 40% and its impact on learning and development results in 60% cost savings (BCG, 2023). The technology enables talent teams to truly push the needle. Every step to anticipate, attract, develop, and engage talent can be enriched with data extracted from machine learning models. Among others, GenAI can be used to create content for job roles, onboarding steps, and career paths. It's an effective tool to support HR teams that have long been understaffed and exhausted.

Leaders in HR are allowing generative artificial intelligence to make its entry into their teams. However, the majority (67%), for now, is not planning to add GenAI-related roles (Gartner, 2024). Gartner (2024) found that, by the end of January this year, 38% of HR leaders had been piloting, planning implementation, or already implemented GenAI. In a period of six months, the number of HR leaders experimenting with and implementing generative AI doubled. It was at 19% in June 2023. At the moment, the use of generative artificial intelligence is mostly concentrated on chatbots for employees (43%), automating administrative activities in HR (42%), and enriching recruitment processes with enhanced job descriptions and skills data (41%) (Gartner, 2024). The implementation of machine learning affects the headcount in HR teams. According to Gartner (2024), leaders are expecting to cut fewer talent jobs (5.1%) than previously anticipated (6.7%). Nearly half of them (46%) said they wouldn't replace employees leaving organizations naturally. It underlines that GenAI creates new jobs and eliminates old ones.

Human Resources is starting to play a role in how other business units leverage GenAI. Talent teams are helping employees to assess and develop relevant skills and preparing them for the (partial) augmentation of their jobs. More specifically, data by Gartner (2024) shows that 34% of HR functions are updating their plans to upskill employees, 29% are identifying talent based on their AI skills and proficiency, 28% are prepping employees for AI-related automation, and 20% is training executives. For many HR teams, it's still early to assess, prepare, and educate other teams. A significant portion of HR leaders (41%) has not initiated any training on GenAI for employees yet (Gartner, 2024). The pace at which talent teams are adopting generative artificial intelligence will soon put them in the strategic position to lead organizations and teams in their transition to a highly automated work environment. 

The early adopters of GenAI are already seeing results. It must stimulate laggards to bring their teams together and start experimenting with the technology. The easiest way to get started is by engaging teams that have a longer history of working with AI. Tech teams are a good starting point. Much of the technology is available for trial at zero or low cost. Through minimal investments, leaders in human capital can equip their team members with intuitive GenAI-powered tools that save hours of work each day. Especially in Human Resources, there's plenty of low-hanging fruit. Step by step a large volume of tasks will be automated. As agendas clear out and the backlog of activities decreases, there are more resources to invest in learning about machine learning and the potential cases to which it can be applied. That's the foundation needed to lay out a strategy for (generative) AI use within the team and later on across the organization. 

Using machine learning on existing data to generate new data in seconds, that's what GenAI is. Its mass adoption is quickly eradicating the last faulty outputs. The potential of generative artificial intelligence is expressed in the hours of work that can be automated. Generative AI affects all workers and is expected to automate more than a third of the time spent today on completing repetitive tasks. Human Resource teams, in particular, have a high volume of these tasks and win big by adopting machine learning. By moving quickly on the adoption of GenAI, they materialize their strategic role and lead the way for other teams. In other words, leaders implementing GenAI accelerate the progress in their teams, position themselves strategically, and deliver meaningful results.