Near-Zero Marginal Cost for AI-Enabled Knowledge Goods?

Mustafa Suleyman, DeepMind cofounder and now Microsoft AI's CEO argues that, because of artificial intelligence, "the economics of information are about to radically change because we're going to reduce the cost of production of knowledge to zero marginal cost."

At least two observations are possible. The perhaps-negative view is that such thinking tends to happen with technology bubbles. The perhaps-positive interpretation is that a major disruption of information-related businesses and industries--perhaps on a greater scale than the internet--is possible. 

Most digital products can have marginal costs close to zero, which is quite different from physical goods. 

source: IP Cariier 

It might be fair to note that what Suleyman refers to is marginal cost, not sunk cost. In other words, the cost of information infrastructure is one matter. The cost of producing the next unit can be marginally close to zero.

Think about communications infrastructure and platforms, where the sunk cost of networks is quite high and very capital intensive, while the cost of producing the next unit is almost immeasurably low. All that has huge costs for many content creators, distributors and firms in many industries. 

Product/Service	Description	Near-Zero Marginal Cost Explanation
E-books	Digital books	Once created, distributing additional copies has negligible cost
Software	Applications, operating systems	Copying and distributing software digitally has minimal incremental cost
Streaming Media	Music, movies, TV shows	Serving content to additional users has minimal bandwidth costs
Digital Information	News articles, blogs	Sharing information online has negligible distribution costs
Online Courses	MOOCs, video tutorials	Adding more students to an online course has minimal additional cost
Cloud Storage	File hosting services	Incremental storage has very low cost due to economies of scale
Social Media	Platforms like Facebook, Twitter	Adding new users has minimal cost once infrastructure is in place
Digital Advertising	Online ads	Displaying ads to additional viewers has negligible cost
Open Source Software	Linux, Drupal	Community-developed software has near-zero distribution cost
3D Printed Objects	Custom products	Once design is created, additional prints have low material costs
Renewable Energy	Solar, wind power	Generating additional electricity has very low marginal cost
Ridesharing	Services like Uber	Adding passengers to existing routes has minimal additional cost
Home Sharing	Platforms like Airbnb	Renting out unused space has low incremental cost for hosts

“Near-zero pricing” (or the perhaps-better known expression of “marginal cost pricing”) is a business principle that underpins and complicates business strategy in a wide range of industries, ranging from internet apps to computing; retailing to media; communications and consumer electronics.

Marginal cost is a universally accepted pricing principle, representing the incremental cost to produce one more unit. The key idea is that it is profitable to keep producing additional units right up to the point where marginal cost and marginal revenue hit zero. At that point, one stops producing, as losses will occur.

But physical goods and digital goods have different marginal cost curves. For a communications service provider, at some point there is so much demand that a network has to be upgraded. That adds capital investment cost, so the marginal cost actually has to rise.

Digital products are different. Once the original is created, the marginal cost can actually remain infinitesimal, even with vastly-greater usage. That also implies that retail price can be very close to zero, and still yield a profit.

In fact, some believe zero marginal cost might be among the most-important business drivers in the early 21st century, though the idea remains controversial.

A company that is looking to maximize its profits will produce “up to the point where marginal cost equals marginal revenue.” In a business with economies of scale, increasing scale tends to reduce marginal costs. Digital businesses, in particular, have marginal costs quite close to zero.

source: Praxtime

In other words, the incremental cost of adding one more Gmail user or one more Facebook user are infinitesimally small.

But marginal costs also are immeasurably small even in some industries with high capital intensity. What, for example, is the incremental cost to supply one more megabyte of internet access capacity; one more minute of voice usage; one more text message, on a network that already is built and operating?

To be sure, additional sales help most businesses, digital or physical. But profit margins for digital goods--based in large part on near-zero marginal costs--often exceed those of physical goods. 

source: Barbara Hoisl

But the danger of pricing at marginal cost (increasingly a price very nearly zero) is that “where there are economies of scale, prices set at marginal cost will fail to cover total costs.”

Think of the “sunk cost” of building a mobile or fixed network. Retail pricing has to be set at a level that allows recovery of that initial network cost, plus profit. So overall pricing cannot be set at the marginal cost of the last units, but at a rate including recovery of sunk costs.

Add to that the possibility that product prices for the end user also include revenue generated by third party partners (advertisers, retailers on a platform) and end user consumption can actually be subsidized.

The point is that even if the incremental cost of supplying one more megabyte of data consumption, one more minute of a voice call or one additional text message is quite close to zero, a service provider cannot price at marginal cost, forever.

That accounts for the business advantage many app, content and services providers hold over a facilities-based connectivity provider selling apps and services. An over-the-top app provider does not have to recover a physical network’s sunk costs.

If Suleyman is correct--and many will disagree--we could see dramatic new disruptions of existing information-based industries and activities as well as the potential creation of entirely-new industries. 

The near-zero marginal cost of digital goods has led to the emergence of various business models. to Freemium models, advertising-supported content, and almost anything that can be bought “as a service” provide examples. 

Digital platforms and marketplaces that leverage create massive scale and network effects that create the platform for revenue and monetization. Using past history, when low marginal cost created cloud computing, software as a service, social media, video and audio streaming, digital versions of physical products (e-books) emerged, AI is likely to produce new products, platforms and industries. 

As was the case for the internet impact on digital goods in general, AI has the potential to alter any number of functional costs. How much of that impact will be incremental, and how much exponential, remains to be determined. 

Aspect	Physical Goods	Digital Goods
Production cost	Significant material and labor costs for each unit	Near-zero cost for additional units after initial creation
Distribution cost	Shipping, handling, and storage expenses	Minimal costs for digital distribution (e.g., bandwidth)
Inventory management	Requires physical storage and logistics	No physical inventory needed
Scalability	Limited by production capacity and resources	Highly scalable with minimal additional costs
Customization cost	Often expensive to customize individual units	Can be customized at little to no additional cost
Geographical limitations	Subject to shipping costs and trade barriers	Can be instantly delivered worldwide
Depreciation	Physical wear and tear over time	No physical degradation (though may become obsolete)
Replication cost	Significant cost to produce exact copies	Virtually costless to create perfect copies

Will AI Disrupt Non-Tangible Products and Industries as Much as the Internet Did?

Most digital and non-tangible product markets were disrupted by the internet, and might be further disrupted by artificial intelligence as well. Non-tangible products are goods or services that cannot be physically touched or held.  

These products  provide value through experiences, expertise, or access, rather than a physical object. Services including legal advice, consulting, haircuts, car washes, travel experiences provide examples. 

So do content products such as e-books, software, online courses, music downloads and video games.

Intellectual property such as patents, trademarks, copyrights, as well as financial Instruments such as stocks, bonds or insurance policies, are examples of intangible products. 

For many of us, internet access and data processing, though supported by very-real tangible platforms, might also be considered intangible products. One uses internet access, but the service is intangible. One uses platforms to process data, but those physical platforms are not the product. Rather, insights, perspectives, discussions, communications and documentation are common outputs and the “products” of the platforms. 

Business models for intangible products have been reshaped by the internet, and stand to be disrupted by AI as well, though the mechanisms might differ. 

In part, the internet disrupted value chains by attacking distribution costs and methods. AI is more likely to disrupt non-tangible product value by altering content production costs and methods. 

But digital technology--and AI--reshape the ways non-tangible products are produced, distributed and consumed.

When analog products are transformed into digital products, they can be replicated and distributed at minimal cost. So scalability grows dramatically, explaining why Netflix can operate globally in a way that legacy media content companies have found difficult. 

New distribution platforms also are possible, as online marketplaces connect creators with customers directly and globally, with fulfillment often possible on-demand. 

Marketing also shifts to online and targeted vehicles, though true for tangible and intangible services, with greater importance on customer experience issues.  

The overall impact of internet mechanisms has been to put pressure on non-tangible product business models, as competition is easier. AI should have many of the same effects.  

Of course, many intangible products have both minimal marginal costs (the cost of producing one additional unit) but also high sunk costs. Connectivity networks, water and electrical networks provide examples. Other networks--such as transportation networks--might also have similar characteristics: high sunk costs to produce the first unit, but low to relatively-low marginal costs for supplying additional units. 

That might suggest the ability to use marginal cost or forward pricing, both of which account for volume or network effects.

Marginal cost pricing sets the price equal to the marginal cost. For most digital goods, this translates to near-zero pricing, as replicating and distributing the product incurs minimal extra expense. But recovery of the sunk costs means that, in practice, marginal cost pricing is rare, even for non-tangible products. 

Forward pricing uses the concept of setting current prices with a view to future expected production costs, as when scale effects occur. 

Traditional pricing models often focus primarily on current production costs (materials, labor) to determine the initial price. Forward pricing takes a longer-term view, factoring in the expectation that production costs will likely decrease as the technology scales up (more units are produced).

Another possible related concept is near-zero pricing, where digital products can take advantage of Moore’s Law impact on the cost of digital infrastructure (computation, memory, bandwidth), and therefore the cost of producing and distributing digital products. 

Near-Zero Pricing: This strategy sets a very low price, often free, to attract a large user base. Revenue can then be generated through advertising, in-app purchases, or freemium models (free basic version with premium features for a fee). Near-zero pricing works best for products with network effects, where value increases with more users (e.g., social media platforms).

Will Near-Zero Pricing Happen with Medical and Legal Advice?

Legendary venture capitalist Vinod Khosla predicts free medical and legal advice in about a decade, because of artificial intelligence. Some will dismiss the prediction as fanciful, given many similar predictions in the past. 

As outlandish as that might appear, it is a common belief or prediction in the digital era, though there were some predictions that electricity, for example, would be “free” in the older analog world. 

There were inaccurate predictions that nuclear power, for example, would be so cheap it would not be worth metering its use. 

Study Title/Publication	Prediction	Date of Prediction	Publisher	Reason for Inaccuracy
"The Promise of Nuclear Power" by Lewis Strauss, Chairman of the U.S. Atomic Energy Commission	Predicts that nuclear power will become so cheap that it will be "too cheap to meter."	1954	U.S. Atomic Energy Commission	Underestimated the costs of constructing and maintaining nuclear power plants, as well as the risks associated with nuclear accidents.
"Nuclear Power: The Answer to the Energy Crisis" by Alvin Weinberg, Director of the Oak Ridge National Laboratory	Predicts that nuclear power will make electricity "too cheap to meter" by 1969.	1960	Public Affairs Press	Overestimated the rate at which nuclear power plants would be built and underestimated the costs of building and operating them.
"Nuclear Energy and the Future of Power" by David Lilienthal, former Chairman of the U.S. Atomic Energy Commission	Predicts that nuclear power will provide "a virtually inexhaustible supply" of electricity at "extremely low cost."	1967	Basic Books	Underestimated the environmental and safety concerns associated with nuclear power.

In recent decades, predictions of dramatically-lower product pricing--essentially free or near zero--have been made in a variety of areas where digital technology was expected to operate. In virtually all cases, assumptions were made about substitute products that would operate so affordably that existing products would not be attractive. 

Study Title/Publication	Prediction	Date of Prediction	Publisher	Reason for Inaccuracy
"The World Without Cars" by Peter Newman and Jeff Kenworthy	Predicts that cars will become obsolete in cities by 2030.	1989	Pluto Press	Underestimated the continued popularity of cars and the challenges of transitioning to car-free cities.
"The Information Economy: How Digital Networks Will Transform the World" by Manuel Castells	Predicts that the information economy will lead to a more equitable society.	1996	Blackwell Publishers	Overestimated the potential of the information economy to reduce inequality.
"The Long Tail: Why the Future of Business Is Selling Less of More" by Chris Anderson	Predicts that the internet will allow niche products to become more profitable than mass-market products.	2006	Hyperion	Underestimated the power of marketing and branding in the digital age.
"The Second Machine Age: Work, Progress, and the Future of Mankind" by Erik Brynjolfsson and Andrew McAfee	Predicts that automation will lead to widespread unemployment.	2011	W. W. Norton & Company	Overestimated the speed at which automation will replace human workers.
"The Rise of the Robots: Automation and the Future of Work" by Martin Ford	Predicts that robots will eventually replace most human workers.	2015	Basic Books	Overestimated the capabilities of robots and underestimated the adaptability of human labor.

All that noted, predictions about near-zero pricing for any variety of products continue to be made. It might be too soon to know whether such predictions will prove incorrect. And relative abundance, in some instances, might have outcomes largely indistinguishable from predictions of absolute abundance. 

Internet access is not “free,” for example, but its price is low enough that usage is not a barrier. Many other products, such as search, shopping, social media and some forms of content cost so little that consumption can be subsidized fairly easy by advertising or low usage fees. 

Study/Story	Prediction	Date of Prediction	Publisher
"The Age of Free: Why We'll Soon Pay Nothing for Most of What We Use"	"Within the next two decades, many of the things we now pay for—electricity, food, transportation, housing, healthcare—will become essentially free."	2014	Jeremy Rifkin
"The Free Economy: When Everything's Free"	"In the future, we will be able to produce goods and services in great abundance at very low cost, or even for free."	2016	Tom Slee
"The Future of Abundance: How the Products of Human Ingenuity Will Make the World a Better Place"	"The abundance created by technology will eventually lead to a world where everyone has access to the basic necessities of life."	2019	Peter Diamandis and Steven Kotler
"Radical Abundance: How to Create a World of More Than Enough"	"The potential for abundance exists in every sector of the economy."	2020	Marianne Williamson
"The World We Made: How Our Future Will Be Shaped by Technology - For Better or for Worse"	"We are on the cusp of a new era of abundance, in which the cost of producing goods and services will continue to decline, and the potential for human flourishing will expand."	2021	Michael J. Sandel
"The Future of Electricity: Scenarios and Forecasts to 2040" by the International Energy Agency (IEA)	Electricity prices will fall significantly in the coming decades, with the average price in industrialized countries expected to be about 50% lower in 2040 than in 2018.	2019	IEA
"The Free Economy" by Jeremy Rifkin	The marginal cost of producing and delivering many goods and services, including electricity, information, and transportation, is approaching zero. This will lead to a new era of economic prosperity in which many products and services will be essentially free to consumers.	2014	Jeremy Rifkin
"The Zero Marginal Cost Society" by Thomas Philippon	The marginal cost of producing and delivering many goods and services, including electricity, information, and transportation, is approaching zero. This will lead to a new era of economic inequality in which a small number of companies will control the vast majority of wealth.	2019	Thomas Philippon
"The Rise of the Sharing Economy" by Rachel Botsman	The rise of digital technologies is making it easier for people to share goods and services, such as cars, homes, and clothes. This will lead to a new era of economic prosperity in which many products and services will be essentially free to consumers.	2013	Rachel Botsman
"The Age of Disruption" by Geoffrey G. Parker	The rise of digital technologies is disrupting many industries, including the energy, telecommunications, and transportation industries. This will lead to a new era of economic uncertainty in which many companies will struggle to survive.	2014	Geoffrey G. Parker
"The Economics of Energy" by Jeremy Rifkin	Predicts that solar power will become so abundant and inexpensive that it will be essentially free for consumers.	2014	Jeremy Rifkin
"The Future of Work" by Martin Ford	Predicts that automation will eventually make many jobs obsolete, leading to a situation where governments provide a universal basic income to all citizens.	2016	Basic Books
"The Age of Surveillance Capitalism" by Shoshana Zuboff	Predicts that data will become the most valuable resource in the world, and that companies will be able to extract immense profits from it by selling it to advertisers and other third parties.	2019	PublicAffairs
"The Next Revolution: Work, Wealth, and the Future of Capitalism" by Nathan Myhrvold	Predicts that artificial intelligence will eventually surpass human intelligence, leading to a new era of unprecedented economic prosperity.	2022	Crown Business
"The 21st Century Revolution: A New Economic Vision" by Jeremy Rifkin	Predicts that a third industrial revolution, based on renewable energy and distributed manufacturing, will eventually replace the fossil fuel-based industrial economy.	2021	St. Martin's Press

But sometimes, intangible products and digital products do approach near-zero pricing levels, reducing barriers to usage. And that is the reason some believe AI is going to attack price levels for any number of intangible products including advice and diagnosis. 

Near-zero pricing might seem outlandish, but not for intangible products. We already have seen that impact in content delivery, shopping and information discovery, as well as social media. And advice based on experience might be the next large set of areas to be affected by the near-zero pricing trend.