Thursday, March 28, 2024

Many Winners and Losers from Generative AI

Perhaps there is no contradiction between low historical total factor annual productivity gains and high expected generative artificial intelligence revenue impact; productivity impact or profit impact for some firms in some industries. 


Keep in mind that total productivity changes include effects 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. 


Industry Sector (NAICS Code)

Description

Percent Change in Labor Productivity (2022)

Total Nonfarm Business (All)

Covers all industries except agriculture, government, and private households

1.0%

GoodsProducing Industries (1133)

Includes mining, construction, and manufacturing

0.4%

Manufacturing (3133)

Factory production of goods

0.5%

Construction (23)

Building, renovation, and maintenance of structures

1.2%

Mining (21)

Extraction of minerals and natural resources

2.3%

ServiceProviding Industries (4892)

Covers a wide range of service businesses

1.4%

Wholesale Trade (42)

Selling goods to businesses in bulk

1.2%

Retail Trade (4445)

Selling goods directly to consumers

0.4%

Transportation and Warehousing (4849)

Moving people and goods

2.1%

Information (51)

Publishing, broadcasting, and telecommunications

2.5%

Financial Activities (52)

Banking, insurance, and real estate

1.2%

Professional and Business Services (5456)

Legal, accounting, consulting, and scientific services

2.0%

Education and Health Services (6162)

Schools, hospitals, and other social services

1.3%

Leisure and Hospitality (7172)

Accommodation, food services, and entertainment

3.9%

Other Services (8189)

Repair shops, personal care services, and religious organizations

0.8%


On the other hand, some forecasts of higher impact for some firms in some industries are not necessarily incompatible with the “all industries” trends for productivity improvements. The best firms in the industries most able to use GenAI might well wring more benefit from the technology. 


In fact, that might tend to be the case for the best and worst firms in almost any industry. 


Also, cumulative productivity gains over a period of years will of course be higher than single year gains. 


Revenue gains in excess of 10 percent for some companies in some industries over a multiyear period are conceivable, even if single-year gains are in single digits or less. 


Industry

Potential Impact

Source, Forecast

Manufacturing

Increased product design efficiency and innovation  Improved production line optimization  Reduced waste and defects

McKinsey & Company: 20% to 40% productivity gains by 2030 PwC: Up to $3.7 trillion global GDP impact in manufacturing by 2030

Retail and  Ecommerce

Personalized marketing and promotions  Enhanced customer experience (chatbots, product recommendations)  Optimized pricing and inventory management

J.P. Morgan: Up to 10% revenue growth for retailers by 2030 Accenture: Up to $1 trillion in annual revenue growth for retailers by 2035

Financial Services

Fraud detection and risk management  Algorithmic trading and portfolio management  Personalized financial advice and wealth management

Goldman Sachs: Up to $1.2 trillion in annual cost savings for financial institutions McKinsey: Up to $200 billion in annual revenue growth for wealth management by 2030

Healthcare

Drug discovery and development  Personalized medicine and treatment plans  Improved medical imaging analysis

PWC: Up to $150 billion in annual savings in the US healthcare system McKinsey: Up to $6 trillion in global healthcare productivity gains by 2030

Media & Entertainment

Content creation (music, scripts, video)  Personalized content recommendations  Streamlined content production workflows

Bain & Company: Up to 10% productivity gains in media content creation by 2030


The point, though, is that big numbers predicted for applied GenAI have to be understood in context. Total-economy gains will be far smaller than many expect, even if some firms, in some industries, will show higher revenue growth; profit rates or productivity gains. 



Where is Telco "Core Competency" Going?

If you ask just about any telco executive or middle manager what their firm’s “core competency” is, the traditional answer almost always has something to do with “creating and operating communications networks.”


Keep in mind that a core competency is not a list of “things we do well.” Instead, it is the combination of resources and skills that give a company a strategic advantage in the marketplace. It's essentially what a company does best and what differentiates it from competitors.


In the monopoly era before 1980, that answer would have made sense, as the law prohibited all others from operating in the business. In the competitive era the traditional answer is eroding. Firms such as Google and others actually fund, build and operate their own connectivity networks. So do cable TV companies and all sorts of mobile communications companies. 


So it is hard to make the argument that “creating and operating networks” actually is the core competency anymore, especially as new suppliers continue to enter the market.  


Decade

Core Competency Claim

Supporting Studies

Limitations

1980s

Network Building & Operation

* Caves, R. E. (1982). Multinational enterprise and economic structure. North-Holland ([study of vertical integration in telecoms])

Network infrastructure was seen as a significant barrier to entry, giving telcos a strong advantage.

1990s

Network Building & Operation (contested)

* Faulkenberry, G. D., & Caves, R. E. (1995). Telecommunications infrastructure: The missing link to economic development. Brookings Institution Press. ([study on telecom infrastructure's role in economic development])

Technological advancements and regulatory changes began to challenge the dominance of network ownership.

2000s

Network Building & Operation (further challenged)

* Witt, R. (2004). How the mobile network became ubiquitous: The telco industry and the regulators. Information, Communication & Society, 7(1), 73-95. ([analysis of co-opetition and network sharing in mobile telecoms])

The rise of wholesale fiber networks and joint ventures cast doubt on network ownership as the sole core competency.

2010s - Present

Shifting Landscape

* Brynjolfsson, E., Rockaway, R., & Van Alstyne, M. W. (2017. Platform revolution: How networked markets are transforming the economy and making winner-take-all competition irrelevant. W. W. Norton & Company. ([study on platform business models in telecoms])

Regulatory expertise, innovation & service delivery, and customer experience are increasingly seen as crucial alongside network capabilities.

Precisely where core competency might eventually be identified is among the core questions for industry leaders, especially as “network operation” ceases to be a clear and indisputable core competence. 


Some might suggest the eventual core competency could be as an “orchestrator of connectivity.” In other words, some tier-one telcos could evolve as system integrators for global communications across all networks (fiber, wireless, satellite) for businesses and consumers. They might own some of the resources used, but largely function as one-stop-ship global connectivity suppliers. 


Perhaps some might try to become “platforms” and “enablers,” essentially becoming connectivity infrastructure providers supporting business partners who develop and deliver the actual end-user services.


Roles for smaller firms could be dramatically different, as smaller telcos might not have the means to support global integrator roles, and might function as suppliers of local resources in a particular geography to the larger tier-one suppliers. 


Arguably less likely are evolutions that would reposition telcos as suppliers of targeted advertising, network optimization solutions, or location-based services supported by their ability to target network users. 


And though cybersecurity is increasingly embedded into all hardware and software, it seems unlikely that most tier-one telcos and smaller firms can become cybersecurity specialists.


The core competency underlying all  these future scenarios includes ability to manage and integrate complex communication ecosystems; creating seamless and personalized communication experiences.


If I had to guess right now, I’d assume the global connectivity integrator role would make sense for a handful of tier-one providers. 


The enabler role might become more prominent for smaller service providers, in the same way that the internet separates app development and ownership  from network access; or compute infrastructure from apps. 


The big switch is from specialized app provider (voice and data connectivity for business customers) to “internet access and transport” provider; global system integration rather than regional franchise; retail point of contact rather than physical layer transport provider. 


Even the move to joint ventures, wholesale network operation and ability of third parties to enter the business all suggest that the “network operator” competence is changing to something else.


The issue is how firms discover that new core competence. 


Wednesday, March 27, 2024

Generative AI Will NOT have the Impact Many Expect

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. 


Industry Sector (NAICS Code)

Description

Percent Change in Labor Productivity (2022)

Total Nonfarm Business (All)

Covers all industries except agriculture, government, and private households

1.0%

Goods-Producing Industries (11-33)

Includes mining, construction, and manufacturing

-0.4%

- Manufacturing (31-33)

Factory production of goods

-0.5%

- Construction (23)

Building, renovation, and maintenance of structures

1.2%

- Mining (21)

Extraction of minerals and natural resources

-2.3%

Service-Providing Industries (48-92)

Covers a wide range of service businesses

1.4%

- Wholesale Trade (42)

Selling goods to businesses in bulk

-1.2%

- Retail Trade (44-45)

Selling goods directly to consumers

-0.4%

- Transportation and Warehousing (48-49)

Moving people and goods

2.1%

- Information (51)

Publishing, broadcasting, and telecommunications

2.5%

- Financial Activities (52)

Banking, insurance, and real estate

1.2%

- Professional and Business Services (54-56)

Legal, accounting, consulting, and scientific services

2.0%

- Education and Health Services (61-62)

Schools, hospitals, and other social services

1.3%

- Leisure and Hospitality (71-72)

Accommodation, food services, and entertainment

3.9%

- Other Services (81-89)

Repair shops, personal care services, and religious organizations

0.8%

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. 


source: Wikipedia 


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. 


Factor

Correlation with Economic Growth

Notes

High Education

Positive

A skilled workforce can develop new technologies, innovate, and improve efficiency.

Wealth

Positive (Up to a point)

Wealth can be invested in new businesses and infrastructure, but extreme wealth inequality can hinder growth.

Income

Positive (Up to a point)

Higher incomes allow for increased consumer spending and investment, but unequal distribution can limit overall growth.

Population Density

Positive (Up to a point)

Densely populated areas foster innovation due to knowledge spillovers and access to a large talent pool. However, overpopulation can strain resources.

Research and Development (R&D) Spending

Positive

Investment in R&D leads to technological advancements that drive productivity and economic growth.

Political Stability

Positive

Stable governments create an environment conducive to business investment and long-term planning.

Infrastructure

Positive

Strong infrastructure (transportation, communication) facilitates the movement of goods, people, and ideas, boosting economic activity.

Financial Markets

Positive

Well-developed financial markets allow businesses to access capital for investment and growth.

Trade Openness

Positive (Generally)

Openness to trade allows countries to specialize in areas of comparative advantage and benefit from economies of scale. However, unfair trade practices can harm domestic industries.

Property Rights

Positive

Strong property rights encourage investment and innovation as people are assured they can benefit from their efforts.

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.


Many Winners and Losers from Generative AI

Perhaps there is no contradiction between low historical total factor annual productivity gains and high expected generative artificial inte...