Generative AI: Finding the competitive edge amid creative destruction Generative AI: Finding the competitive edge amid creative destruction

In a generative AI world, two new sources of competitive advantage are emerging – the quality of your data and the quality of your people, especially those with advanced AI skills.

Turning first to data, long-term advantages can come from how a business fine-tunes its large language models.

For example, a company that exists in a business where the start-up costs are prohibitive for new entrants would have a formidable competitive advantage. Similarly, a pharmaceutical company with a patent for a miracle drug would still benefit from the exclusive right to market the drug.

Of course, AI will not breach all traditional economic moats.

That puts asset-light intelligence-based businesses like law firms, architecture and engineering at the top of the list, according to Goldman Sachs’ insights into where work is most likely to be automated. Similar businesses to education technology – such as translation and financial advice companies – might also prove to be at risk.

Despite a bleak backdrop of rising interest rates and possible recession, the price of big U.S. tech companies leapt in the first six months of 2023.

Some investors argue that the big tech companies’ generative AI models are becoming increasingly commoditized and may be outcompeted by smaller open-source models – and the first quasi-autonomous agents may be developed by nimble start-ups. After all, the large language models used by chatbots like ChatGPT are available to everyone.

In a world where all businesses have access to generative AI, how do you sustain competitive advantage? The technology looks likely to disrupt, or at least dilute, many existing economic moats – the characteristics of a business that protect it from competition and maintain its profit margins. AI could reshape entire industries and create completely new ones.

It fell by 50% in one day during May after reporting a hit to its business from generative AI, as some students turned to chatbots for answers rather than subscribing to its services.

THE RALLY’S FLIPSIDE

OpenAI expects this growth to drive rapid financial gains; in a 2022 pitch to its private investors, it estimated reaching $200 million of revenue in 2023, rising to $1 billion in 2024.

With rapid adoption across sectors and use cases, the technology is improving exponentially faster at a rate not previously seen. Indeed, a new wave of AI helpers, or agents, like the Microsoft 365 Copilot are being developed to perform complex personal and work tasks without needing close supervision.

Beyond the big tech companies, there are already signs of companies being disrupted. For instance, the share price of Chegg, the U.S. edtech company, has fallen by two thirds in the first six months of 2023.

The sectors most at risk of having work tasks automated could also be those most at risk of losing their competitive advantages.

So, too, has the price of the Netherlands’ ASML, a leading supplier of the equipment needed for making the semiconductor chips that generative AI requires, as well as the price of Taiwan Semiconductor.

Generative AI quickly became 2023’s stock market sensation, sparking a huge rally mainly in the U.S. for shares in Microsoft and other tech companies poised to benefit.

Source: Reuters, December 2022

One of the reasons that data is very critical to artificial intelligence, and machine learning in general, is that the models themselves are useless without data. There are sometimes trillions of parameters that need to be estimated, and unless you have enough data to train the models, the output is not going to be useful at all. So data is really critical and people and firms that have large amounts of proprietary data are going to be at a clear advantage in this space. ”

$120

$100

$80

$60

May ‘23

Apr ‘23

Jan ‘23

Feb ‘23

Mar ‘23

Aug ‘23

Jul ‘23

Jun ‘23

U.S. :NYSE

Taiwan Semiconductor Manufacturing Co. Ltd. ADR

U.S. :NYSE

ASML Holding N.V.

Source: Refinitiv

May ‘23

Apr ‘23

Jan ‘23

Feb ‘23

Mar ‘23

Aug ‘23

Jul ‘23

Jun ‘23

$800

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But rather than just incorporating more and more data, can generative AI autonomously outperform humans at the most economically valuable work, as outlined in the OpenAI charter? And when? Researchers have put GPT to the test, literally, to measure performance against prospective lawyers.

FINDING THE COMPETITIVE EDGE AMID CREATIVE DESTRUCTION

It’s expected to have a profound impact on economic growth by exponentially increasing productivity. That’s because everything today – from culture to consumer products – is a product of intelligence. If the excitement around generative AI proves justified, it may unleash the biggest wave yet of what Joseph Schumpeter, the famed Austrian economist, termed “creative destruction.” AI innovation will refresh the economy by destroying traditional businesses, replacing them with something more productive. For investors, though, the key question is: If generative AI chatbots quickly commoditize intelligence, where will competitive advantage lie in a world of endemic generative AI?

Source: PwC, July 2023

$15.7 trillion

The amount of value that generative AI could add to the global economy by 2030

The rapid explosion of generative AI for general use has captured the global imagination with what the technology might enable.

AI Job Postings (% of All Job Postings) by Geographic Area, 2014-22

AI Job Postings (% of All Job Postings)

Source: Lightcast, 2022 | Chart: 2023 AI Index Report

0.45%, New Zealand

0.72%, Italy

0.84%, France

0.86%, Belgium

0.89%, Austria

0.98%, Germany

1.01%, Netherlands

1.14%, United Kingdom

1.16%, Switzerland

1.20%, Sweden

1.23%, Australia

1.33%, Spain

1.45%, Canada

2.05%, United States

7337

1903

1608

854

ChatGPT

Instagram

Facebook

Twitter

Netflix

Accelerated Adoption - Number of Days to Reach 100 Million Users

Source: Refinitiv

Chegg’s AI Reckoning

U.S. : NYSE

*Meta's Threads microblogging app has since surpassed it by reaching 100 million users in five days.

When ChatGPT-3, the first generative AI chatbot, was launched by Microsoft-backed OpenAI in November 2022, it quickly became the fastest-growing app ever, attracting an estimated 100 million users within two months.

GPT-4 March 2023

More than 1 trillion (estimated)

Google Bard March 2023

540 billion

GPT-3 June 2020

175 billion

GPT-2 Feb 2019

1.5 billion

GPT-1 2018

120 million

Parameters are one of the defining characteristics of AI models. They determine how the model processes the data and how it generates predictions.

Rapid Growth of GPT Models

Source: Open AI [1, Feb. 2019] [2, Nov. 2019] [3, Sept. 2020], Semafor, March 2023, Google, July 2023

2014

2015

2016

2017

2018

2019

2020

2021

2022

2.00%

1.50%

1.00%

0.50%

50%

40%

30%

20%

10%

Share of Industry Employment Exposed to Automation by AI in the U.S.

Bdg & grounds clean/maint

Installation, maint, repair

Construction & extraction

Production

Transport & material moving

Food prep & serving

Personal care & service

Art, dsgn, ent, sport, media

Healthcare support

Edu instruction & library

HC practitioners & technical

Protective service

Farming, fishing, forestry

Computer & mathematical

Sales & related

Management

Community & social service

Business & financial ops

Life, physical, social sci

Architecture & engineering

Legal

Office & admin support

All industries

Source: Goldman Sachs GIR, April 2023

$12

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How GPT Models Performed on the Multiple-Choice Multistate Bar Examination (MBE)

GPT-2

ada 001

babbage 001

curie 001

davinci 001

GPT-3.5

ChatGPT

GPT-4

Student Avg. (NCBE BarNow)

Correct Rate

80%

70%

60%

50%

40%

30%

20%

10%

Source: “GPT-4 Passes the Bar Exam,” Katz, Bommarito, Gao, Arredondo. March 2023

Q1 2023

Q4 2022

Q1 2019

Average MBE Passing Range

Random Guessing

2023’s AI rally anticipates a rapidly approaching future

SUSTAINABLE COMPETITIVE ADVANTAGE IN AN AI WORLD

Source: Reuters, July 2023

NCBE

GPT-4

GPT <=3.5

$300

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U.S. Tech Stock Rally

NVDA

MSFT

META

AAPL

AMZN

GOOG

ORCL

$400

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Close Price ($)

Source: Refinitiv

PRESENT

OUTFRONT SERIES

Mark van Rijmenam

Strategic futurist

The big companies who are already very, very powerful, who also have access to a lot of data, it's likely that these big tech firms will only grow bigger, more powerful with fewer employees. They can do the same work with fewer employees because they use the same technology…. So they will become leaner and smaller, but also a lot more powerful. And then on the other end, we have the open-source approach. That might also be a company coming from left field. So it's very difficult to see where this will go.”

If investment in AI leads to competitive advantage, then the U.S. is far ahead of even China, its nearest rival in the race to become leader.

In 2022, the $47.4 billion invested by the U.S. was roughly 3.5 times the amount invested by the next highest country, China, and 11 times the amount invested by the U.K. Notably, all of the big generative AI releases have come from the U.S.

Total Investment (in Billions of U.S. Dollars)

Private Investment in AI by Geographic Area, 2022

Source: NetBase Quid, 2022 | Chart: 2023 AI Index Report

0.61

0.72

1.04

1.13

1.35

1.52

1.77

1.83

2.35

3.10

3.24

4.37

13.41

47.36

Finland

Japan

Switzerland

Singapore

Australia

Argentina

France

Canada

Germany

South Korea

Israel

United Kingdom

India

China

United States

WHICH COUNTRIES ARE GAINING COMPETITIVE ADVANTAGE?

Developed countries are likely to adopt generative AI fastest because wages are highest and so they have most incentive, according to McKinsey. But this will only feed into productivity gains if displaced workers find new activities with at least the same economic output.

What’s more, its citizens are among those who feel most positively about AI products and services. A 2022 IPSOS survey found that 78% of Chinese respondents agreed with the statement that products and services using AI have more benefits than drawbacks. By contrast, only 35% of Americans agreed that products and services using AI have more benefits than drawbacks.

However, there are areas where China pulls ahead. For instance, China dominates industrial robot installations, enabled by AI to collaborate with humans in factories. In 2021, China installed more industrial robots than the rest of the world combined.

Estimated number of jobs lost to AI over a 10-year period

The potential for AI to replace humans in the workforce inspired a UK-based thinktank called Onward to advocate for a shift in the burden of taxation from labor to capital.

300 MILLION

Of course, the huge excitement around generative AI’s potential is as yet untested. There are many reasons why the future of generative AI may not prove as revolutionary as supposed.

Yet there are possible hurdles that could slow the growth of AI. Firstly, regulation is even now being crafted but its eventual shape is unclear. And, secondly, there are battles underway over the ownership of intellectual property scraped by AI companies to train their models. 2023’s rapid share price rallies signal the excitement about generative AI. It’s a fast-moving business revolution that looks sure to breach some economic moats while creating an opening for building others.

CONCLUSION

Looking to the future, companies with a combination of high-quality proprietary data, and with people with advanced AI skills who can fine-tune data or integrate it into business processes, are likely to gain a competitive advantage. By contrast, the asset-light business sectors where there are predictions of job losses such as law firms, architecture or engineering may prove most at risk.

Positive Sentiment Toward Products and Services Using AI by Country

Source: Ipsos, January 2022

78%

China

71%

India

42%

Japan

37%

Australia

76%

Saudi Arabia

50%

Italy

53%

Spain

38%

U.K.

37%

Germany

35%

U.S.

Most important is the technology’s limitations. Ask ChatGPT what its IQ is and it answers the following:

What’s more, amid existential fears about machine super-intelligence and job losses, there is regulation looming in the U.S., EU and China.

Turning to specific problems, it’s fair to say that generative AI has an intellectual property problem.

There’s a flurry of lawsuits accusing generative AI companies of breaching copyright. Among them, three artists have sued Stability AI, Midjourney and DeviantArt in San Francisco for alleged unauthorized copying of their work to train their systems.

A record 37 AI-related laws were passed in 2022, according to Stanford University. The EU’s AI Act aims to be the first comprehensive regulatory scheme.

Source: Ipsos, January 2022

Source: ONWARD, May 2023

Source: Goldman Sachs, April 2023

Source: Reuters, April 2023

POSSIBLE DRAGS TO DISRUPTION

There's no question that the initial breakthroughs and the current leadership as of 2023 in generative AI technology is really with the U.S. Why? In part, when you look at some of the other biggest players in the world that are trying to compete, for instance, for some of the Chinese launch language models, there is far less Internet data in Chinese language. So unless they want to build their launch language models in English, they're starting off with a linguistical disadvantage and a volume disadvantage in the amount of data available to train their models. “And then there is more likelihood of intrusion and heavy-handed regulation in a country like China than there would be in the U.S. But of course, it's contingent on regulation being able to strike a good balance between protecting the public but allowing the development of this very powerful new technology.”

Source: Boston Consulting Group, March 2023

Source: Deloitte, 2023

If, for example, you wanted to use an AI program to automatically identify building materials from photographic images, you would need to take photos of hundreds of thousands of structures and map those structures to the relevant building materials, according to Deloitte. Most of the work in building the AI program would go into gathering and organizing the data. It’s not proprietary but the scale of the effort involved acts as a barrier to entry.

The U.S. saw nearly 800,000 AI-related job openings in 2022, according to the Stanford Institute for Human-Centered Artificial Intelligence’s 2023 AI Index Report. And in March 2023, LinkedIn reported that there were just over 100,000 jobs on its site that mentioned artificial intelligence in the job description.

Sometimes the data doesn’t need to be proprietary — just very hard to gather.

Turning to people, employees with AI skills who can help a business fine-tune data or integrate AI into its processes can also create a competitive advantage.

Cost to fine-tune a large language model to complete a complex legal classification according to a model by Snorkel AI that equips organizations to build AI models. Such an application could save hours of a lawyer’s time, which can cost up to $500 per hour.

Fine-tuning data for an existing open-source or paid model is inexpensive.

$1,915 - $7,418

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GENERATIVE AI:

Loans

Days to 1M

Days to 10M

Accelerated Adoption - Number of Days to Reach 100 Million Users chart

Source: Reuters, July 2023

Days xxto 1M

Days to 10M

Days to 100M

Netflix

Twitter

Facebook

Instagram

ChatGPT

854

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7337

How GPT Models Performed on the Multiple-Choice Multistate Bar Examination (MBE)

Correct Rate

GPT <=3.5

GPT-4

NCBE

Random Guessing

Average MBE Passing Range

Q1 2019

Q4 2022

Q1 2023

Student Avg. (NCBE BarNow)

GPT-4

ChatGPT

GPT-3.5

davinci 001

curie 001

babbage 001

ada 001

GPT-2

10%

20%

30%

40%

50%

60%

70%

80%

AAPL