Though the generative AI transformation that is occurring worldwide is still in its infancy, here’s what we’ve learned in the two-plus years since Gen AI made its public debut with the introduction of OpenAI’s ChatGPT:
GenAI makes many companies more productive by making their employees more productive—enabling some workers to do more of what they need to do, faster and better.
- GenAI makes many companies more productive by making their employees more productive—enabling some workers to do more of what they need to do, faster and better.
- These improvements will accelerate as GenAI’s use increases, fueling demand for AI-ready employees.
- We are also learning—and this is a huge plus—that GenAI enables users to do new things, often well-beyond their current capabilities. This suggests a potential solution may be at hand for some of the talent shortages plaguing businesses the past several years.
In short, GenAI is changing both work and the workplace. But there’s one thing that GenAI won’t change, as history has shown repeatedly as other new technologies have been introduced: the need for the human touch—empathy, ethical judgement, negotiating skills, building and maintaining relationships.
GenAI will make some jobs obsolete, or reduce the number of people needed to perform them, just as automation and robotics helped pare the number of U.S. factory jobs over time, from more than 17.3 million in 1975 to about 12.8 million today, according to the St. Louis Fed. But the most significant impact of advanced technology isn’t always the destruction of jobs and businesses, it’s the creation of new and better jobs, businesses, products, and services—the process economist Joseph Schumpeter described more than 80 years ago as “creative destruction.”
And that’s where we are today with GenAI—not at the end of an era, where things are being blown up, but at the beginning of a new one, where old processes, methods, businesses and jobs are being reinvented and new ones are being created.
An expert suggested we try to visualize GenAI as an exoskeleton: a new tool that not only empowers workers to perform better, but to tackle tasks and challenges that otherwise would be beyond their current capabilities, while freeing up time to exercise their distinctively human skills.
This isn’t wishful thinking. Research backs them up.
Working with Boston University academics and researchers at OpenAI’s Economic Impacts unit, BCG’s Henderson Institute put the theory to the test in research published last September. Forty-four data scientists and 480 other professionals with limited, or no, training or experience in data science participated in the experiments, with eye-opening results.
For example, on one of the assigned tasks, involving coding, the participants without any coding experience, who were allowed to use GenAI “achieved an average score equivalent to 86% of the benchmark” set by the data-science professionals. The inexperienced participants who not allowed to use GenAI, scored 49-percentage-points lower on average (at 37% of data scientists’ average).
But that wasn’t all. The group of non-specialists using GenAI not only came close to matching the experts in their level of performance, they actually outperformed them in speed, finishing the assigned work “roughly” 10% faster than the professionals who participated in the study. That’s because GenAI enabled the novices “to instantly expand their aptitude for new tasks” even when they had no experience doing those tasks.
While using data science in their case study, the BU/OpenAI/Henderson Institute research team believes their findings “can be applied to any field that is within the [AI] tool’s capabilities.”
For example, organizations with technology-heavy workforces, many of which have been struggling for years to find the talent they need, may be able to cast wider nets as GenAI technologies enable non-experts to take on more-complex roles. In fact, the first place they probably should look is within their own organizations, where many employees may be looking for new challenges that lead to advancement.
This also could mean new talent and teaming arrangements, with AI-augmented generalists teaming with technical specialists, whose new roles might include mentoring, problem-solving, trouble-shooting, and quality control.
As the study team concluded, “We are only at the beginning of the GenAI transformation journey, and the technology’s capabilities will continue to expand. Executives need to be thinking critically about how to plan for this future, including how to redefine expertise and what skills to retain in the long term. … Preparing for the GenAI-augmented workforce must be a collective endeavor—because our collective future depends on it.”