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Friday, May 29, 2026

AI Undermines "Answer Questions" Business Models

Chegg is one of the clearest early examples of a public company whose core business was rapidly undermined by generative AI.


But those of you who have worked in any content production industry have seen this before, in the impact of the internet on content business models.


Industry

Traditional Revenue Model

AI Threat

Risk Level

Newspapers

Ads + subscriptions

AI summaries replace clicks

Very High

News websites

Programmatic ads

Search traffic declines

Very High

Magazines

Ads + subscriptions

Commodity lifestyle content

High

Trade journals

Subscription + data

AI-generated research summaries

High

Music labels

Streaming + licensing

AI-generated songs and voice clones

High

Stock photography

Licensing fees

Text-to-image generation

Very High

Online reference sites

Ads + subscriptions

Direct AI answers

Very High

Product review sites

Affiliate commissions

AI recommendation engines

Very High

Educational publishers

Textbook sales

Personalized AI tutoring

High

Local journalism

Ads + classifieds

Reduced traffic and lower cost AI content

Very High


Chegg built a subscription business around three core assets:

  • A massive library of solved textbook problems and Q&A

  • Human experts and tutors

  • A recurring subscription model (students paid monthly for homework and study help). 


So the business moat was built on:

  • Proprietary content accumulated over years

  • Search traffic from students looking for specific solutions

  • Willingness to pay for reliable, structured answers


Generative AI changed all three assumptions, and undermined the business model.


Tools like OpenAI ChatGPT and Google Gemini offered:

  • Instant answers

  • Natural-language explanations

  • Low or zero cost

  • Broad subject coverage

  • Personalized tutoring


This turned Chegg’s premium service into a commodity.


Metric

Peak / Before AI Shock

After AI Disruption

Market capitalization

~$14.7 billion (2021 peak)

~$150–200 million (2025–2026)

Share price

~$113/share

Around $1/share

Revenue trend

Strong pandemic growth

Sustained year-over-year declines

Subscribers

Multi-million paid base

Persistent subscriber losses

2025 layoffs (May)

~248 employees (22%)

2025 layoffs (October)

~388 employees (45% of remaining workforce)


But Chegg likely will not be alone. Other lines of business might have similar characteristics:

  • Sell information rather than physical goods

  • Depend on labor-intensive expert work

  • Have low switching costs

  • Offer outputs that can be generated in text, image, audio, or code. 


Industry

Traditional Value Proposition

AI Substitute

Risk Level

Examples

Homework help

Solved problems and tutoring

ChatGPT-style tutoring

Very High

Chegg

SEO content agencies

Human-written articles

Automated article generation

Very High

Jasper

Translation services

Human translation

Neural machine translation

Very High

DeepL

Basic legal drafting

Contracts and standard documents

AI document drafting

High

Harvey AI

Tax preparation

Form completion and guidance

AI tax copilots

High

Intuit

Customer service BPO

Human support agents

AI chat and voice bots

Very High

Zendesk AI

Coding contractors

Routine software work

Code generation assistants

High

GitHub Copilot

Graphic design for simple tasks

Logos and ad creatives

Image generators

High

Adobe Firefly

Market research summaries

Analyst reports

Automated synthesis

High

AlphaSense

Recruiting screening

Resume review

AI candidate matching

High

LinkedIn Talent Solutions

Medical transcription

Dictation and coding

Speech-to-text + AI coding

Very High

Nuance Communications

Stock photography

Generic images

AI image generation

Very High

Shutterstock


As was the case when the internet disruption began, content suppliers will be in the line of fire:

  • Research report subscriptions

  • Professional tutoring services

  • Basic legal document preparation

  • Simple coding tutorials

  • Generic content websites

  • Q&A platforms charging for access

  • Standardized test prep companies. 


If you can describe your service as “We answer questions about X,” danger clearly exists, as AI will provide a substitute.


Monday, February 2, 2026

AI Impact: Analogous to Digital and Internet Transformations Before It

For some of us, predictions about the impact of artificial intelligence are remarkably consistent with sentiments around the importance of innovation in the technology business we have heard since the 1980s and up through the internet revolution.


“In 2030, I think we will be bringing offerings and solutions to market that we can’t even envision

today because the technology isn’t there yet,” says Maureen Power Sweeny, RapidScale chief revenue officer.” I would say 50 percent of our revenues will come from new offerings.”


Some of us have been hearing that since the 1980s, and the sentiment seems borne out by events, and especially for digital products that can be created and adopted faster than older physical-only products. 


Five to 10 years is now multiple generations of product evolution in software, cloud, data, and AI.


Company

Product generating major revenue today

Year introduced (approx.)

What it displaced or superseded

Amazon (AWS)

Lambda, SageMaker, Bedrock

2014–2023

EC2-only compute, on-prem ML

Microsoft

Azure OpenAI, M365 E5, Copilot

2019–2024

Perpetual Office licenses, on-prem Exchange

Salesforce

Einstein AI, Platform, Industry Clouds

2016–2023

Standalone CRM licenses

NVIDIA

Data center AI accelerators

2017–present

Gaming GPUs as primary revenue driver

Adobe

Creative Cloud subscriptions

2013–2017 ramp

Perpetual boxed software

ServiceNow

Creator workflows, AI ops

2018–2024

ITSM-only positioning

Zoom

Phone, Contact Center, AI Companion

2019–2024

Single-product video meetings

Apple

Services (TV+, Pay, Arcade, Fitness)

2019–present

Hardware-only growth

Google

Cloud AI APIs, Workspace AI

2018–2024

Ad-only monetization model

Netflix

Ad-supported tier, originals

2016–2023

Licensed content distribution


But many industries feature high rates of innovation and product replacement. In many fast-moving consumer categories, 40 percent to 70 percent of active SKUs (stock keeping units) at major retailers are replaced within five years, even though the brand name on the shelf barely changes.


Category

Brand

Current high-volume SKUs (examples)

Introduced (approx.)

What they replaced or supplemented

Beverages

Coca-Cola

Zero Sugar reformulations, mini-cans

2017–2023

Full-sugar flagship SKUs

Snacks

PepsiCo (Lay’s)

Baked, Kettle, limited flavors

2016–2024

Core salted potato chips

Dairy alternatives

Danone

Oat-based yogurts, creamers

2018–2024

Traditional dairy SKUs

Household

P&G (Tide)

Pods, hygienic clean, cold-water

2015–2023

Liquid detergent bottles

Beauty

L’Oréal

Clean beauty, dermocosmetic lines

2017–2024

Mass cosmetic formulations

Food

Nestlé

Plant-based frozen meals

2019–2024

Animal-protein frozen SKUs

Alcohol

AB InBev

Hard seltzers, flavored malt drinks

2018–2023

Core beer SKUs

Personal care

Unilever

Sulfate-free, refill formats

2019–2024

Traditional shampoo bottles

Candy

Mars

Sugar-reduced, portion-controlled

2016–2023

Standard single-serve bars

Pet food

General Mills

Fresh, functional pet foods

2019–2024

Dry kibble-only lines


So one commonality with prior industry changes is rapid and continual product innovation. 


The other perhaps-obvious potential change is industry disruption. 


In 2030, enterprise success won’t be measured by steady progress toward long-term targets but by how much an enterprise disrupts its industry quarter by quarter, IBM researchers argue. 


The biggest risk won’t be making the wrong bets, but making bets that are too small, the authors argue. 


That again will sound familiar to those who witnessed the changes in firms and industries wrought by the internet. Netflix provides an example. 


Netflix disrupted multiple stages of the video entertainment value chain, first by unbundling physical retail rentals and later by collapsing production, aggregation, and direct distribution into a single global streaming platform.

source: Digital Leadership 


Value chain stage

Traditional role

Netflix’s move

Why it was disruptive

Content creation & commissioning

Studios and networks funded, developed, and greenlit shows and films, often for domestic first windows.

Became a major commissioner and producer of originals, including local-language series with global ambitions.academic.oup+1

Shifted power from broadcasters to a data-driven buyer with global reach, reducing reliance on legacy networks and altering bargaining dynamics.academic.oup

Aggregation & programming

Broadcasters and cable networks assembled schedules and channel line‑ups; video stores curated shelves.

Offered a huge on-demand catalog with personalized rows and recommendations instead of fixed schedules or shelves.accio+1

Undermined the value of linear programming and physical curation, making algorithmic discovery the primary gatekeeper of attention.accio+1

Distribution to consumers

Cable/satellite operators and retail chains controlled access via physical locations or set‑top boxes; households subscribed to bundles or rented per title.forbes+1

Delivered content over the open internet to apps on TVs, phones, and PCs via a flat-rate subscription.accio+1

Bypassed cable operators and retail stores, drove cord‑cutting, and shifted consumer spend from channel bundles and rentals to streaming subscriptions.intrinsicinvesting

Retail / rental monetization

Video rental stores monetized individual rentals and late fees, constrained by local inventory and store hours.linkedin+1

Introduced queue-based subscription rentals by mail, then streaming with no late fees and no trip to the store.linkedin+1

Eliminated the core revenue levers of incumbents (late fees, impulse rentals), making their store-heavy model uncompetitive.linkedin+1

Marketing & discovery

Studios and networks relied on mass advertising, trailers, and prominent placement in stores or schedules.

Used in‑product recommendations, personalized homepages, and data-informed promotion of titles.accio+1

Reduced dependence on external marketing funnels, internalized discovery, and extended tail consumption of niche titles.accio

International sales & licensing

Rights sold territory-by-territory with complex windowing across cinema, pay TV, free TV, and home video.

Negotiated multi-territory and global rights and launched near-simultaneous international releases on one platform.academic.oup+1

Collapsed layers of local intermediaries and windows, standardizing global access and weakening traditional territorial carve‑ups.academic.oup


The internet accelerated innovation by making information, markets, and coordination vastly cheaper and faster, turning experimentation by firms into a continuous, global, software-driven process. 


Enablers included:

  • Radically lower information and transaction costs 

  • Continuous software-based iteration, shortening innovation cycles from years to weeks or days.

  • Global market access​

  • Real-time feedback loops

  • Platform and ecosystem effects (e-commerce, app stores, social networks).


The take-away is that, as we have seen before, AI is going to enable more industry and firm disruption. 


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