Opera has begun rolling out AI models that run locally in its browser, potentially allowing enterprises to perform certain AI tasks on existing PCs without sending the relevant data to cloud AI providers.
The company said it has introduced support for WebAI, a proposed web standard, through an opt-in early preview in Opera One. The technology allows websites and browser extensions to access AI models running locally in the browser for tasks such as generating text and classifying content.
The WebAI preview supports 64-bit Windows PCs running Intel or AMD processors and Macs powered by Apple silicon. Opera does not specify a requirement for a dedicated neural processing unit, although it says performance depends on the device’s hardware.
The preview does not currently support Windows on Arm, potentially limiting its availability across some newer AI PCs.
The feature is optional, with AI models downloaded only after users enable it. Opera said website-specific permissions allow users to control which sites can access the locally running models.
Opera said its implementation supports models including Google’s Gemma and Apple’s on-device foundation model on compatible Macs. The company said it plans to introduce additional models optimized for different devices as it expands the technology.
Local AI shifts enterprise security risks
Opera’s implementation could have implications beyond its own browsers if the proposed WebAI standard gains wider adoption, potentially bringing locally running AI models to more enterprise users.
The privacy benefits for enterprises could depend on how organizations control access to locally running models, particularly through websites and browser extensions.
Pareekh Jain, CEO of Pareekh Consulting, said processing sensitive information locally could reduce enterprise security risks by limiting the need to send data to external AI providers. However, he warned that the approach could make it harder for IT departments to monitor activity on individual devices.
“It is easier for IT to monitor internet traffic,” Jain said, adding that monitoring activity on individual laptops can be more difficult.
He warned that malicious websites could potentially manipulate local AI models through hidden prompts, while rogue browser extensions could gain access to sensitive information displayed on a user’s screen.
“Local processing reduces risks but does not eliminate them,” Jain said.
Enforcing consistent safeguards across employee devices would become imperative for enterprises, according to Tulika Sheel, senior vice president at Kadence International.
“Enterprises still need controls over which websites and extensions can access local models, how information is used, and how models and browser permissions are managed across the organization,” she said.
Could browser AI reduce the need for new AI PCs?
While WebAI can run on existing computers, its ability to reduce enterprise spending on new AI PCs will depend on whether those machines can deliver acceptable performance for everyday business tasks.
Jain said smaller AI models could handle tasks such as summarization and rewriting on existing PCs, potentially reducing the need for immediate hardware upgrades.
“Complex reasoning and advanced AI workloads will still benefit from dedicated AI hardware or cloud infrastructure,” he said.
WebAI’s support for compatible models from different providers could give developers greater flexibility in choosing which AI systems to use.
Browser-based AI could also reduce enterprise spending on cloud services by lowering API usage and dependence on external AI providers. However, limitations in model capabilities and enterprise integration could restrict its usefulness for more sophisticated applications.
“The future will likely be hybrid, with browser AI handling simpler tasks and cloud AI supporting advanced workloads,” Jain said.
Sheel said enterprises would still need to account for the costs of model updates and integration with existing systems, even if local processing reduces their cloud AI usage.
“Lower usage costs do not automatically mean lower total costs,” she said.