Thursday, May 9, 2024

Generative AI Might Create the Next Digital Real Estate

To the extent that generative artificial intelligence could enable the creation of rivals to search, and improve search, it also creates monetization opportunities for advertising. To that extent, gen AI is another form of “creating digital real estate.”


The “real estate” metaphor long has been applied in the “virtual” spaces created by operating systems (homescreens and notifications), applications (content apps, search, social media, e-commerce venues), lockscreens and browsers (home screens and tabs), with monetization platforms thereby created for advertising or other forms of sponsorship. 


All create value based on user attention and interaction, much as traditional pre-internet linear media and content also created attention, and thereby audiences and ad potential. 


Digital Real Estate

Monetization Platforms

Examples

Lockscreen

Targeted advertising & content, app discovery, In-screen commerce

Glance, Apple Lockscreen widgets

Browser Homepage & New Tab

Search engine results, sponsored content, tiles, bookmark monetization

Google Search homepage, Yahoo New Tab

Operating System (OS) Home Screen & Notifications

Pre-installed apps and bloatware, paid app placements, Sponsored notifications

Android app placements, iOS Spotlight suggestions

App

In-app advertising (banners, interstitials, video ads), Freemium model with in-app purchases, Subscriptions

Most mobile games, Social media apps

In-Game Environments: The virtual world players navigate within the game.

In-Game Advertising: placing billboards, product placements, or branded content within the game environment. Virtual goods sales: selling cosmetic items, outfits, or customizations for characters or in-game objects. Limited-time events: creating temporary events or challenges that players can access for a fee.

Forza Horizon (Virtual billboards), Product placement in sports games like FIFA or Madden

Menus and Interfaces: Screens and interfaces players interact with to manage their game experience.

Targeted in-app advertising: displaying ads based on player data and preferences within menus or loading screens. Premium Currencies: Selling a secondary currency used for specific purchases within the game (separate from in-game currency earned through gameplay). Battle passes: offering tiered reward systems where players progress through challenges to unlock exclusive items or features.

Fortnite (Cosmetic microtransactions), Apex Legends (Battle Pass), Diablo 3 (Expanded inventory slots)

Gameplay Mechanics: The core rules and systems that govern how players interact with the game.

Subscription models: providing access to additional content, features, or servers through a monthly subscription. Expansion Packs: selling downloadable content that adds new levels, storylines, or features to the base game. Loot boxes: offering randomized virtual items through purchasable containers, potentially including rare or desirable items.

World of Warcraft (Subscription services), Call of Duty: Mobile (Double XP Boosters)


Some idea of the value of such digital real estate can be seen in changes in ad placement in pre- and post-internet advertising. 


Put simply, digital now claims up to 82 percent of all U.S. ad placements and revenue. Print has declined from 42 percent to less than three percent. Linear video dropped from 38 percent to 16 percent. Radio dipped from 10 percent to half a percent. 


Channel

1996 (Billions)

1996 (%)

2023 (Billions)

2023 (%)

Print (Newspapers, Magazines)

80.0

42.1%

10.0

2.7%

Linear Video (TV Broadcast, Cable)

72.0

37.9%

60.0

16.2%

Network Radio

10.0

5.3%

2.0

0.5%

Other (Radio Spots, Out-of-Home)

28.0

14.7%

18.0

4.9%

Digital Ads (Search, Social Media, Display)

-

-

300.0

81.7%

Generative AI Helps Consumer Products A Lot, Telecom Services Not So Much

No doubt, we are going to see a cascade of articles and recommendations about why it is imperative that connectivity service providers apply artificial intelligence to their businesses, perhaps starting with the customer service functions, as might be true for many industries.


On the other hand, it seems highly unlikely that the benefits of AI will accrue evenly across industries, as that has not tended to be the case for past information technologies, either. 


Industry

Generative AI Impact

Rationale

Consumer Products (Retail, Fashion)

High

Generative AI can personalize product recommendations, design new products, and optimize marketing campaigns, leading to increased sales and customer satisfaction.

Healthcare

High

Generative AI can assist in drug discovery, personalize treatment plans, analyze medical images for faster diagnoses, and even create new medical devices.

Finance

High

Generative AI can generate personalized investment advice, analyze financial markets for better risk assessment, and even automate fraud detection, improving overall efficiency and security.

Manufacturing

Moderate-High

Generative AI can optimize product design and manufacturing processes, reduce waste, and even personalize products for individual customers.

Media & Entertainment

Moderate

Generative AI can personalize content recommendations, create new forms of entertainment like AI-generated music or videos, and automate content creation tasks.

Education

Moderate

Generative AI can personalize learning experiences for students, create interactive learning materials, and even automate grading tasks.

Transportation

Moderate

Generative AI can optimize traffic flow, improve route planning for self-driving vehicles, and personalize transportation options for users.

Connectivity Services (ISPs, Telecom)

Moderate-Low

AI's impact might be limited in core network functions. However, it can benefit customer service, marketing, and potentially network security.

Some industries are likely to benefit more. So AI impact might be higher for industries including financial services, for example, as has been the case in the past. Consider generative AI, which McKinsey consultants believe will drive the most value in software engineering, customer operations. 


On the other hand, generative AI impact might be least for human resources, strategy, pricing, legal and finance operations, for example. 


source: McKinsey


Many would guess that healthcare will be a bigger beneficiary from AI than has traditionally been the case for information technology investments, based on diagnostics for patient care and discovery of new drug and other care therapies. 


But even that position is contested at the moment. 


According to job site Indeed, generative AI, for example, is going to supplant more human activity in software development than in driving; more replacement in information technology help desks and less for beauty or wellness jobs. 

source: Indeed


As with so many other metrics, it appears connectivity services and data centers are somewhere in the middle of industries where it comes to the degree of process automation and improvement.


The issue is how that impact will be primarily felt, though. If the internet largely reduced marginal costs and therefore enabled global platforms to emerge, what will AI bring?


Two broadly-different drivers of outcomes might happen: AI reshapes processes in roughly the same way the internet did, or AI reshapes processes in a new way. 


In other words, if the internet primarily recase marginal cost, AI might work the same way. If AI automates processes, it could likewise lower marginal cost of any operation. 


On the other hand, AI, by enabling massive personalization and customization of products and experiences; allowing faster innovation based on better research and development processes; might drive change primarily by allowing new products to be created and discovered. 


The primary change driver would be as a value multiplier more than a marginal-cost reduction mechanism.


Tuesday, May 7, 2024

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).


Unrealistic Enterprise IT Spending Expectations for 2024?

According to a new survey conducted by Coleman Parkes including 500 C suite information technology professionals working at organizations with a minimum of 1,000 employees (U.S.; U.K.; France; Germany; Turkey), respondents expect IT budgets to grow by a whopping 27 percent in 2024. 


Parenthetically, the report says 2022 respondents overestimated their projected spending by 10 percent. And while it is always possible that this particular sample is unusual in some way, such year over year increases or decreases in IT budgets do not tend to reach those reported levels. 


Also, an increase in IT spending of that magnitude would be hugely out of step with trends of the past few years. Rates of growth in past immediate decades probably was higher because spending was growing from a smaller base. 


Year

% Change

Source

2024 (forecast)

6.80%

Gartner

2023

3.30%

Gartner

2022

3.0%

IDC, Gartner


A reasonable assessment is that IT spending as a percentage of firm revenue has increased since 1980, to support the use of personal computers; the internet; the web; enterprise software innovations; cloud computing and mobility; cybersecurity and now preparation for artificial intelligence. 


But even optimistic forecasts have topped out between 12 percent and 14 percent expected increases in IT spend as a percentage of revenue in past decades, and even those boosts can be characterized as outliers. 


It might also be fair to note that almost all forecasting tends to be optimistic, for IT or any other product, in any other industry. 


Year Range

IT Spend % of Revenue

1980s

Low Single Digits

1990s

Mid-Single Digits (5-8%)

2000s

Mid-Single Digits to Low Teens (5-12%)

2010s

Low Teens (10-14%)

2020s (as of 2023)

High Single Digits to Low Teens (8-14%)


The point is that the self-reported claims of expected increases in IT budgets are enough out of character with recent trends, and with longer-term trends, as to be suspect. In life and business, it often makes sense to note what people and firms actually do, not what they say they will do.


Monday, May 6, 2024

AI is Just a Tool

Artificial intelligence, like any tool, can be used well, or in troubling ways. In this case, an artisit uses AI to recreate his own voice, so he can sing his own song. 

Directv-Dish Merger Fails

Directv’’s termination of its deal to merge with EchoStar, apparently because EchoStar bondholders did not approve, means EchoStar continue...