Artificial Intelligence, or AI, is like a highly specialized tool in a corporate setting, adept at performing specific tasks such as analyzing data, predicting patterns or automating routine processes. This is not new and has been around for a while now – after all, wasn’t Netflix recommending content for us using 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, like generating an image or design, 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 (like AI) within the workforce, to both make teams more productive and create policies for safe use.
The difference between Artificial Intelligence (AI) and Generative AI (GenAI)
To further differentiate these concepts, let’s break it down.
Netflix’s recommendation system is an example of AI and not GenAI. It uses advanced algorithms and machine learning techniques to analyze your viewing history, preferences, and behaviors. Doing so can predict and suggest content you’re likely to enjoy. This system continually learns and adapts based on your interactions with the platform, making its recommendations increasingly personalized and accurate over time. The use of AI in this context is a prime example of how technology can enhance user experience by providing tailored suggestions 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 resumes to match job seekers with job openings based on criteria such as skills, experience, and education.
GenAI, in contrast, is about creating new content or data that didn’t exist before. It involves AI systems that can generate new images, text, music, or other media that mimic human creativity. So while Netflix recommendations are a sophisticated use of AI, they don’t involve the creative, generative processes characteristic of 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 generate customized learning modules, activities, and educational materials. This tailored approach ensures that training is more engaging, effective, and directly aligned with the employee’s growth path and the organization’s needs.
Impacts of GenAI on the Workplace
GenAI will be the most significant change to workplaces since the agricultural and industrial revolutions. This may sound like an extreme, however, in its early stages, it’s shown promising revolutions across many facets of how organizations work.
According to a 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 U.S. economy by 2030, compared to 21.5% without AI. The report suggests this change is not limited to manual or routine tasks – but extends to areas requiring creativity, expertise, and interaction with people.
However, the introduction of GenAI into teams poses unique challenges. Research from the Columbia Business School indicates integrating AI into human teams can impact performance and coordination, leading to a decline 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, indicating a need for differentiated strategies in global organizations. HR professionals and organizational leaders must collaborate to create common practices and guidelines that address cultural differences and trust issues, ensuring GenAI implementation within the workforce enhances rather than hinders employee engagement and productivity.
AI creates a landscape where individuals can evolve from specializing in just one or two skill areas to proficiently handling several interconnected skills simultaneously. Deepening the integration of GenAI in organizations will need more robust learning programs and a culture that emphasizes teaching and learning across three dimensions: individual, organizational, and the AI itself. About 75 percent of the value that GenAI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D, according to a Mckinsey report.
I believe AI will not replace all humans anytime 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 dedicate time to learning about the power of GenAI by immersing yourself in it and giving it a try.
