McKinsey has released a detailed report on generative AI, which according to several use cases could add “the equivalent of $2.6 trillion to $4.4 trillion annually” to the global economy.
Press coverage has focused on one particular finding. Here’s Bloomberg:
According to a new report from consultants McKinsey & Co, the global explosion of generative artificial intelligence will usher in an era of accelerated productivity and greater wealth for some – and profound disruption for others, primarily knowledge workers.
This is clearly bad news for all knowledge worker industries that produce large volumes of general content based on general research.
The 68-page report, The economic potential of generative AI: the next productivity frontiercan be read here.
Takeaways include that higher-paid workers are more vulnerable, and that having a high level of qualification may be less necessary for work in the future.
This, of course, makes for worrying reading for certain industries, especially those working in content-producing consulting roles.
Fortunately, according to the widely distributed research report, about applying generative AI to a field like marketing required human involvement (our emphasis):
However, introducing generative AI into marketing functions requires careful consideration. First, mathematical models trained on publicly available data without sufficient safeguards against plagiarism, copyright violations, and brand recognition risk infringing intellectual property rights. A virtual fitting application may skew certain demographics due to limited or biased training data. So, considerable human oversight is required for conceptual and strategic thinking specific to each company’s needs.
Other areas may be more affected, with the authors insightfully using the typical work patterns of a “post-secondary” English teacher as a possible example:
As an example of how this might play out in a specific profession, consider post-secondary English language and literature teachers, whose detailed work activities include test preparation and evaluation of student work. With the improved natural language capabilities of generative AI, more of these activities could be done by machines, perhaps initially to create a first draft for educators to edit, but perhaps eventually with much less human editing. This allows these teachers to free up time to devote more time to other activities, such as supervising class discussions or supervising students who need extra help.
The analysis captures the massive shifts in capital allocation that widespread adoption of generative AI could drive:
In a cheeky footnote, the report adds:
It also contains some notes on methodology:
One concern many knowledge workers may have as they read this is that one day they will lose their job to a computer. McKinsey has insight into potential staffing trends:
(T)his analysis does not assume that the magnitude of work automation directly equates to job losses. Like other technologies, generative AI typically makes it possible to automate individual activities within professions, not entire professions. Historically, activities in many professions have shifted over time as certain activities have become automated. However, organizations may decide to realize the benefits of increased productivity by reducing employment in some job categories, a possibility that we cannot rule out.
This is the confirmation page of the report:
