The excitement surrounding generative AI is unprecedented, even in the rapidly evolving tech industry. Experts at McKinsey predict that this technology could generate between $2.6tn to $4.4tn of economic value every year, spanning industries from banking to life sciences.
Chat GPT, one of the most famous examples of generative AI, reached 100 million users just two months after its launch and has grown to over a billion users by most estimates. Multiple recent studies, along with a framework for assessing the impact of automation on work, as outlined in Reinventing Jobs (HBR Press, 2018), demonstrate the significant potential benefits that can be achieved using RPA implementation and the four generations of AI currently available to us: rule-based systems, machine learning, deep learning, and generative AI.
Generative AI is Changing Jobs
To fully comprehend the impact of generative AI on work, it is essential to distinguish its disparities from the previous generations of AI. The subsequent evaluation elucidates the most notable contrasts.
AI’s advanced predictive capabilities have reshaped industries, and now, the evolution of Generative AI promises even more. While generative AI has shown instances of creative exploration, we’re focused on harnessing its potential to drive innovation and practical solutions.
Regarding tasks like transaction-processing work, it’s essential to focus on minimizing variance and hitting a target level of performance. There’s no need to go above and beyond in these types of tasks if they are completed accurately and efficiently.
Enhancing efficiency in a salesperson’s work can lead to a proportional increase in the value brought to the organization.
Consider innovative tasks, like data analysis, where even a slight enhancement in efficiency can significantly enhance its worth.
When addressing tasks requiring minimizing variability and exhibiting a greater acceptance of risk, well-established automation solutions like Robotic Process Automation (RPA) prove exceptionally valuable in replacing manual labor. For instance, the highly repetitive, rules-based work of analyzing and synthesizing financial data can benefit from the application of RPA. In the past, AI has been used to augment analytical work to achieve productivity improvement or breakthroughs.
Let’s explore the inspiring case of oncologists who have elevated cancer detection accuracy with the assistance of machine learning. This isn’t about replacing their expertise, but rather amplifying their capabilities and highlighting their experience. Now, consider the realm of generative AI. While it holds immense promise, refining it for error reduction is a nuanced endeavor. Occasional instances of creative missteps emphasize the role of human insight, enhancing its value. It’s important to recognize that Generative AI offers exciting possibilities and practical applications across various domains.
Leaders must understand when and where to rely on something other than various technologies and what specific role they should play in either substituting, augmenting, or transforming human work. Generative AI is an excellent tool for democratizing knowledge and creativity through augmentation, which can help reduce the skills premiums traditionally required for various creative tasks. This technology can be beneficial for boosting productivity in domains where the risk tolerance is higher. From copywriting to call center operations, generative AI has already demonstrated significant value in increasing productivity, especially for less experienced talent.
It’s fascinating to consider how the democratization of access could potentially reduce the inequality we’ve seen in the past two industrial revolutions. With generative AI increasing the productivity of those with lesser skills, much like the automation of the second industrial revolution, we can level the playing field.
With AI progressively diminishing the exclusivity of creativity and making access more widespread, it’s vital to explore ways we can intelligently and intricately reshape our business model and workforce to harness these advancements. It’s an exciting time to think about the future of work and how we can harness the power of AI to create a more equitable and productive society.