Robot and young woman face to face.
Artificial Intelligence, or AI, is like a highly specialized tool in an enterprise environment, capable of performing specific tasks such as analyzing data, predicting patterns, or automating routine processes. This isn’t new and has been around for a while – after all, wasn’t Netflix recommending content for us to use AI to watch almost a decade ago?
Generative Artificial Intelligence, or GenAI, on the other hand, is a subset of AI and is relatively newer. It can create new content, such as creating an image or drawing, using its programming to “imagine” and produce things that didn’t exist before. Think of AI as a highly skilled worker, while GenAI is more like an innovative artist or creator.
HR leaders are now expected to go beyond their typical area of expertise (people) and understand/adopt new technologies (such as artificial intelligence) in the workforce to make teams more productive and create policies for safe use.
The difference between Artificial Intelligence (AI) and Generative AI (GenAI)
To differentiate these concepts further, let’s break it down.
Netflix’s recommendation system is an example of AI, not GenAI. It uses advanced algorithms and machine learning techniques to analyze your viewing history, preferences and behaviors. This way you can predict and recommend content that you are likely to enjoy. This system constantly learns and adapts based on your interactions with the platform, making its recommendations increasingly personalized and accurate over time. The use of artificial intelligence in this context is a prime example of how technology can improve the user experience by providing tailored recommendations for the end user. An example of machine learning in HR applications is the use of applicant tracking systems (ATS) that leverage machine learning algorithms to screen resumes and applications. These systems analyze CVs to match job seekers with jobs based on criteria such as skills, experience and education.
GenAI, in contrast, is about generating new content or data that didn’t exist before. It includes AI systems that can create new images, text, music or other media that mimic human creativity. So while Netflix’s recommendations are a sophisticated use of AI, they don’t include the creative, productive processes that characterize GenAI. An example of GenAI in HR applications is the creation of personalized training programs and content. GenAI can analyze an individual employee’s learning style, performance data and career development goals to create customized learning modules, activities and training materials. This customized approach ensures that training is more engaging, effective and directly aligned with the employee’s development path and organizational needs.
Implications of GenAI in the workplace
GenAI will be the most significant change in the workplace since the agricultural and industrial revolutions. This may sound extreme, but in its early stages, there are promising revolutions in many aspects of how organizations operate.
According to recent McKinsey report, the adoption of AI is expected to sharply accelerate the timeline for automation, potentially automating up to 29.5% of work hours in the US economy by 2030, compared to 21.5% without AI. The report suggests that this change is not limited to manual or routine tasks – but extends to areas that require creativity, expertise and interaction with people.
However, introducing GenAI to teams poses unique challenges. Research from Columbia Business School indicates that the integration of artificial intelligence into human teams can affect performance and coordination, leading to a decrease in productivity. Despite the productivity gains offered by AI, there is a notable human aversion to working with AI agents, which raises concerns about trust and job satisfaction—key competencies of employee engagement and retention. This aversion is not uniform across cultures, suggesting the need for differentiated strategies in global organizations. HR professionals and organizational leaders must work together to create common practices and guidelines that address cultural differences and trust issues, ensuring that the implementation of GenAI in the workforce enhances rather than hinders employee engagement and productivity.
Artificial intelligence creates a landscape where individuals can evolve from specializing in one or two skill areas to mastering many interconnected skills simultaneously. Deepening the integration of GenAI into organizations will require stronger learning programs and a culture that emphasizes teaching and learning across three dimensions: individual, organizational, and AI itself. About 75 percent of the value that GenAI use cases could deliver falls into four areas: customer operations, marketing and sales, software engineering, and R&D, according to Mckinsey Report.
I believe that AI will not replace all humans soon, but rather both humans and machines will enhance their capabilities over time to effectively harness the full potential of GenAI for an organization. To truly understand and leverage this transformative technology, I encourage you to take the time to learn about the power of GenAI by immersing yourself in it and testing it out.
