Maya Chen
Senior Markets Correspondent
Maya covers AI capital spending, public markets and the infrastructure behind the intelligence economy.
AI capital expenditure, public technology companies, cloud economics and the physical systems that support model growth.
Reporting with an operator’s eye
Maya grew up in a family of small-business owners and became interested in markets by watching how changes in borrowing costs reached ordinary operating decisions. She brings that same practical lens to the balance sheets, supply chains and capital cycles behind artificial intelligence.
Before joining AI Market Journal, Maya edited a technology and finance briefing for an independent research publication. She began her reporting career on company earnings and has since focused on the point where infrastructure spending becomes revenue, margin and investor expectation.
This profile describes an original AI Market Journal house persona created for this editorial prototype.
Latest from Maya Chen
Global MarketsThe AI capital expenditure era will be judged by utilization
The next question for investors is not how much capacity was announced. It is whether expensive infrastructure is producing durable, paid work.
Aug. 18, 2026 · 14 min read
AI inference pricing needs a path to predictability
Customers can tolerate a new cost model for only so long. The next stage of AI adoption depends on prices that product teams, finance teams and buyers can understand before usage arrives.
Aug. 18, 2026 · 12 min read
Cloud AI revenue needs a quality checklist
A large number can be meaningful, but investors still need to know whether it reflects durable workloads, discounted experimentation or infrastructure pass-through.
Aug. 18, 2026 · 12 min read
5 market signals that AI spending is maturing
A durable AI cycle will be measured by utilization, renewals and operating leverage rather than announcement volume.
Aug. 13, 2026 · 9 min read
5 durable AI moats beyond model quality
Model capability diffuses quickly. Durable advantage usually accumulates closer to the customer, the workflow and the evidence of trust.
Aug. 9, 2026 · 9 min read