Generative artificial intelligence, to say nothing of machine learning or neural networks (and eventually general AI), might collectively represent a new general-purpose technology comparable in impact to electricity, the internet and other innovations that have widespread economic impact.
But there is reason to be cautious about just how much benefit AI will bring to specific firms in different industries, as important as AI is expected to become. Consider the productivity impact, for example.
Though some observers believe AI could produce a startling rate of productivity increase perhaps an order of magnitude higher than what we have experienced in recent decades, there are reasons to believe such forecasts are far too optimistic.
Keep in mind that total productivity changes include changes from all sources, not just information technology. So unless you believe IT was solely responsible for total productivity change since 1970, the actual impact of IT arguably is rather slight, perhaps on the order of 0.5 percent up to about 1.5 percent per year, maximum.
And those years would include the impact of personal computers, the internet and cloud computing, to name a few important information technology advances.
The point is to understand that even if generative AI winds up becoming a GPT, its measurable impact on productivity will not be as great as some expect, and productivity gains will vary by firm and industry.
Inevitably, those who argue generative artificial intelligence will “transform” firms in various industries will undoubtedly prove to have offered an overblown and incorrect argument.
Keep in mind that GenAI is used to create content. So it is firms in industries that principally “create content” that stand to benefit the most.
Recent strikes by Hollywood actors and writers illustrate that point. The entertainment media industry--which principally creates content--is among those most exposed to GenAI and most able to use the tools.
Media also is an industry estimated to have had higher productivity gains in 2022 than most others. Where all “non-farm” industries might have seen an average one-percent productivity gain in 2022, media saw a boost of up to 2.5 percent, according to Bureau of Labor Statistics figures.
Likewise, firms in the product design business; marketing and advertising; pharmaceutical development and finance industries are among segments that routinely create content as a core function, and might therefore be expected to be areas where GenAI has early impact.
Professional services might have seen a boost in 2022 productivity of perhaps two percent.
On the other hand, many industries do not rely principally or even significantly on content creation, and should lag in terms of GenAI producing measurable business results.
Basic resource extraction, such as mining or forestry should see limited impact, one way or the other. In fact, goods-producing industries tended to see negative productivity growth in 2022. AI might help, but we need to be realistic about the degree of potential change.
Even if you assume we can measure knowledge worker or office worker productivity--and there remains doubt on that score--correlations between productivity growth and application of information technology arguably remain correlational.
We might see a relationship without being able to prove causation.
GSMA and Deloitte researchers, for example, almost always find a correlation between mobile phone penetration and economic growth. A 10-percent increase in mobile penetration could increase Total Factor Productivity (TFP) by 4.2 percentage points in the long run, they tend to argue.
But we might also find that other correlations between economic growth and productivity exist, without being able to prove a causal effect. It might be that better-managed firms simply use any new technology more effectively than poorly-managed firms, for example.
Faster-growing economies might be better able to deploy new technology, as the infrastructure already is in place. Faster-growing economies might have many highly-profitable firms; in growing industries; producing lots of knowledge-related jobs in areas where new technology offers an advantage.
Faster-growing economies might also have higher percentages of highly-skilled workers; well-educated workers; with higher incomes or wealth to begin with.
The point is that expectations of AI benefit in general, and generative AI benefit in particular, are likely overblown and exaggerated, as important as they likely will become.
Measurable results are almost bound to disappoint, in most cases, as even the cumulative effect of all prior information technology advances since 1970 have shown only relatively modest impact on cumulative productivity growth rates in most industries.
As was the case for the internet in general, look for early signs of significant change in any industry that is largely concerned with content creation. That means media (video, film, music, newspapers, magazines) as well as marketing and advertising.
To use a very-broad analogy, as the internet destroyed legacy media and shifted business models, so generative AI, for example, is likely to affect media and advertising early on. Which largely explains the urgency many firms now attach to mastering GenAI in search, social media and content-creating industries as a whole.
We have seen this story before.
