Grab raised its full-year revenue guidance to $4.10-$4.15 billion on Tuesday after reporting second-quarter results, citing artificial intelligence tools that have cut product development cycles to one-third their prior length.
The Southeast Asian ride-hailing and delivery company reported $997 million in second-quarter revenue. The new guidance range represents an increase from the prior $4.04-$4.10 billion forecast. Chief Financial Officer Peter Oey said the company is shipping products three times faster than before after deploying AI-assisted development.
Grab operates in eight countries across Southeast Asia and runs ride-hailing, food delivery, and financial services units. The company went public on Nasdaq in December 2021 at a $39.6 billion valuation and has since faced pressure to demonstrate profitability and revenue growth to justify its scale. Second-quarter revenue of $997 million marks a $31 million sequential increase from the first quarter, according to the company's announcement.
Other Southeast Asian technology companies have begun experimenting with code generation and test automation tools to accelerate feature rollout. Grab did not specify which products benefited most from the faster shipping cycle or whether the three-fold speed gain applied across all engineering teams.
The company also announced a $750 million share repurchase program. Grab's path to positive net income has been a focal point for investors since its public debut, with the company posting losses in prior years despite strong revenue growth.
Grab has now raised its full-year guidance twice in 2026, with the prior increase coming earlier this year. The new range implies annual revenue of $4.10-$4.15 billion, placing the midpoint at approximately $4.125 billion, a 25 percent increase over 2025's estimated figure of roughly $3.3 billion based on the company's prior public statements.
The metric that will test Oey's claims about AI-driven productivity is whether Grab maintains or improves its engineering headcount relative to product output in coming quarters. If the company's engineering team size remains flat or shrinks while revenue per engineer climbs, the velocity gains would carry credibility; growth in both headcount and output would mean AI is merely scaling existing capacity rather than compressing timelines.
