Agentic Browser Automation: The Next AI Core Competency
Browser agents will create hundreds of billions of dollars of value for the infrastructure companies who create them and the application layer companies who commercialize them.
AI tools are fundamentally changing entire vertical sectors of the economy through a set of horizontal foundational competencies. Chat capabilities are overhauling customer service. Coding agents like Cognition’s Devin and Cursor are redefining the efficacy and efficiency of software engineering. Robots will move goods and provide services that augment blue collar workers’ skills and free up human time for more important physical tasks. In the digital world, a new, foundational competency is emerging that will drive similar impact for white collar professionals: Agentic Browser Automation.
The History of Digital Process Automation
Just as robots are the next evolution of machines – capable of seeing and thinking in ways that the previous generation of hardware could not – agentic browser automation is the next evolution of Robotic Process Automation (RPA). RPA emerged in the early 2000s as a way to automate repetitive digital tasks. Over the next two decades, RPA became a multibillion-dollar industry. Forrester Research projected the market size as $22 billion in 2025. The dominant company within RPA is UiPath (>$6bn enterprise value); in 2023, UiPath alone held about 36% of the RPA market share (more than 3x any competitor). Classic RPA tools enable organizations to script software bots that mimic user actions for tasks like data entry or form processing, yielding huge efficiency gains.
However, traditional RPA has clear limitations. RPA bots follow predefined rules and UI scripts, so they perform well on structured, repetitive processes. They struggle when confronted with change or complexity. Even minor interface updates or unexpected inputs can break a scripted bot, because these systems lack contextual understanding or adaptability.
Agentic Browser Automation: Why it Matters
Agentic browser automation represents the next leap. Enabled by advances in AI (especially LLMs), this approach introduces autonomous agents that bring reasoning and flexibility to automation. Instead of rigid scripts, an AI agent can perceive a web interface, interpret content, and decide actions autonomously, much like a human would. These agents use a combination of techniques, including computer vision, to understand the page, allowing them to adapt on the fly to new layouts, pop-ups, or changes in workflow.
Agentic browser automation is uniquely effective for complex, internet-based use cases. A critical difference between browser agents and RPA is that agents aren’t stymied by the lack of formal APIs. In traditional integrations, if a service had no API, automation was limited to brittle UI scripts. Given how frequently those scripts broke, humans ended up shouldering the bulk of these often-times menial tasks – or just as often, the task was abandoned altogether. Now, an agentic system can use the web interface itself as the medium for interaction, just as a person would.
Browser agents provide robustness in the face of change. If a page layout shifts or a modal dialog interrupts, the agent can intelligently navigate or dismiss it and continue. Vision-based agent tools have shown the ability to self-adjust to UI changes that would break a normal RPA bot. This resilience is crucial for complex, long-running web workflows on the modern internet. The result is far fewer failed runs and less bot maintenance, making automation feasible for processes that evolve frequently.
Browser-based agents thus unlock processes that were previously off-limits to automation due to lack of integration. Many real-world enterprise workflows live in this gap. Browser agents can tackle the messy parts of the internet – legacy web portals, third-party sites, password-protected pages, old SaaS tools – by having an agent simply use the front-end like a user, rather than requiring back-end access. This point is critical and bears highlighting: the RPA market size is $22bn, but consistent bot maintenance made it an unfeasible investment for many repetitive tasks. Using browser agents unlocks an entire new set of tasks that consumers and businesses will be willing to pay for – the agentic browser market will quickly become an order of magnitude larger than the RPA market ever was.
The Players Providing the Infrastructure
To achieve that, a new generation of infrastructure tools and platforms has emerged to support AI agents in the browser.
BrowserBase: A platform that provides reliable, high-performance headless browser infrastructure for AI agents at scale. BrowserBase can launch thousands of cloud browser instances in parallel within milliseconds, which developers can control via APIs. It also offers an open-source framework called Stagehand that combines the precision of scripted steps with the flexibility of AI guidance.
AnchorBrowser: A cloud platform designed to make browser automation enterprise-grade and reliable. Anchor explicitly tackles the common failures of traditional web automation – what it calls “fragile, costly, and brittle” browser scripts. The service runs “humanized” browser instances that are nearly undetectable as bots (avoiding anti-scraping measures), complete with proxy management and CAPTCHA solving built-in for global web access.
Browser Use: An open-source project and service that aims to democratize agentic automation with a no-code interface. The motto of Browser Use is that anyone should be able to automate a web task by simply telling an AI what to do. Under the hood, Browser Use provides an AI agent with specialized capabilities to extract interactive elements from webpages and navigate complex workflows step-by-step. For the user, it’s as simple as writing a natural language instruction (e.g. “Log into my email and download the monthly report”), which the agent then interprets and executes in the browser. This approach removes the need for programming or writing scripts altogether.
These examples are part of a growing ecosystem. Other notable names include Skyvern, HyperBrowser, Steel, and Kernel for browser cloud infrastructure.
From Infrastructure to Application
As with other forms of AI, browser agents won’t just ease the burden of low-level human tasks – they’ll also create a whole new category of workflows that provide value, but were too trivial for humans to do in the first place. Whether as a replacement or augmenter of human capability, browser agents will be applied vertically to the largest parts of the economy.
Financial Services: In an industry where speed and precision are paramount, autonomous agents can bring real-time decision-making to processes that were once manual or overnight batch jobs. Banks and insurers are beginning to deploy AI agents alongside their workforce, albeit carefully within compliance guardrails. In fact, the market for AI agents in financial services is expected to grow by 815% from 2025 to 2030 as firms invest in these capabilities. The potential applications span nearly every corner of finance. Browser agents can be used to systematically trade on behalf of retail investment portfolios, authorize payments by voice, and gather information on behalf of a Loan Origination System (LOS). Agents will also significantly lower the friction associated with opening new accounts, boosting conversion rates for wealth managers, brokerages, and others.
Healthcare: Hospitals and insurers face enormous operational inefficiencies – according to the American Hospital Association, over 40% of hospital expenses are administrative, as opposed to clinical. There is a huge opportunity for agents to reduce this overhead, accelerate processes, and let healthcare professionals refocus on patient care. Browser agents can navigate EMRs to extract or input patient information. They can help patients fill out online paperwork and assist with appointment creation. And they can help practices submit regulatory documentation to governing bodies and insurance companies.
E-commerce: E-commerce is the primary stage for the rise of agentic commerce, as both consumers and retailers begin to leverage AI agents in the shopping journey. On the consumer side, shoppers are starting to delegate tasks to AI: for example, instead of manually searching and comparing products, they ask a shopping agent to find the best options. Recent research by Adobe found that 24% of online consumers now skip Google entirely and use AI platforms to get curated product recommendations. These agents can handle everything from product discovery to price comparison, and companies like Henry even enable agents to check out on behalf of the user.
The Future of Browser Automation
Browser agents are already driving a step-function improvement to traditional RPA methods. And yet, the commercialization of browser automation began less than two years ago. The tools that drive browser agents are still a work in progress, and with each incremental improvement, they unlock a whole new set of vertical use cases. Across major verticals, new market entrants will operationalize browser agents as a wedge to create major value for their customer base. We’re just beginning to scratch the surface of this hundred-billion-dollar opportunity.
blue collar workers’ skills and free up human time for more important physical tasks. In the digital world, a new, foundational competency is emerging that will drive similar impact for white collar professionals: Agentic Browser Automation.
The History of Digital Process Automation
Just as robots are the next evolution of machines – capable of seeing and thinking in ways that the previous generation of hardware could not – agentic browser automation is the next evolution of Robotic Process Automation (RPA). RPA emerged in the early 2000s as a way to automate repetitive digital tasks. Over the next two decades, RPA became a multibillion-dollar industry. Forrester Research projected the market size as $22 billion in 2025. The dominant company within RPA is UiPath (>$6bn enterprise value); in 2023, UiPath alone held about 36% of the RPA market share (more than 3x any competitor). Classic RPA tools enable organizations to script software bots that mimic user actions for tasks like data entry or form processing, yielding huge efficiency gains.
However, traditional RPA has clear limitations. RPA bots follow predefined rules and UI scripts, so they perform well on structured, repetitive processes. They struggle when confronted with change or complexity. Even minor interface updates or unexpected inputs can break a scripted bot, because these systems lack contextual understanding or adaptability.
Agentic Browser Automation: Why it Matters
Agentic browser automation represents the next leap. Enabled by advances in AI (especially LLMs), this approach introduces autonomous agents that bring reasoning and flexibility to automation. Instead of rigid scripts, an AI agent can perceive a web interface, interpret content, and decide actions autonomously, much like a human would. These agents use a combination of techniques, including computer vision, to understand the page, allowing them to adapt on the fly to new layouts, pop-ups, or changes in workflow.
Agentic browser automation is uniquely effective for complex, internet-based use cases. A critical difference between browser agents and RPA is that agents aren’t stymied by the lack of formal APIs. In traditional integrations, if a service had no API, automation was limited to brittle UI scripts. Given how frequently those scripts broke, humans ended up shouldering the bulk of these often-times menial tasks – or just as often, the task was abandoned altogether. Now, an agentic system can use the web interface itself as the medium for interaction, just as a person would.
Browser agents provide robustness in the face of change. If a page layout shifts or a modal dialog interrupts, the agent can intelligently navigate or dismiss it and continue. Vision-based agent tools have shown the ability to self-adjust to UI changes that would break a normal RPA bot. This resilience is crucial for complex, long-running web workflows on the modern internet. The result is far fewer failed runs and less bot maintenance, making automation feasible for processes that evolve frequently.
Browser-based agents thus unlock processes that were previously off-limits to automation due to lack of integration. Many real-world enterprise workflows live in this gap. Browser agents can tackle the messy parts of the internet – legacy web portals, third-party sites, password-protected pages, old SaaS tools – by having an agent simply use the front-end like a user, rather than requiring back-end access. This point is critical and bears highlighting: the RPA market size is $22bn, but consistent bot maintenance made it an unfeasible investment for many repetitive tasks. Using browser agents unlocks an entire new set of tasks that consumers and businesses will be willing to pay for – the agentic browser market will quickly become an order of magnitude larger than the RPA market ever was.
The Players Providing the Infrastructure
To achieve that, a new generation of infrastructure tools and platforms has emerged to support AI agents in the browser.
BrowserBase: A platform that provides reliable, high-performance headless browser infrastructure for AI agents at scale. BrowserBase can launch thousands of cloud browser instances in parallel within milliseconds, which developers can control via APIs. It also offers an open-source framework called Stagehand that combines the precision of scripted steps with the flexibility of AI guidance.
AnchorBrowser: A cloud platform designed to make browser automation enterprise-grade and reliable. Anchor explicitly tackles the common failures of traditional web automation – what it calls “fragile, costly, and brittle” browser scripts. The service runs “humanized” browser instances that are nearly undetectable as bots (avoiding anti-scraping measures), complete with proxy management and CAPTCHA solving built-in for global web access.
Browser Use: An open-source project and service that aims to democratize agentic automation with a no-code interface. The motto of Browser Use is that anyone should be able to automate a web task by simply telling an AI what to do. Under the hood, Browser Use provides an AI agent with specialized capabilities to extract interactive elements from webpages and navigate complex workflows step-by-step. For the user, it’s as simple as writing a natural language instruction (e.g. “Log into my email and download the monthly report”), which the agent then interprets and executes in the browser. This approach removes the need for programming or writing scripts altogether.
These examples are part of a growing ecosystem. Other notable names include Skyvern, HyperBrowser, Steel, and Kernel for browser cloud infrastructure.
From Infrastructure to Application
As with other forms of AI, browser agents won’t just ease the burden of low-level human tasks – they’ll also create a whole new category of workflows that provide value, but were too trivial for humans to do in the first place. Whether as a replacement or augmenter of human capability, browser agents will be applied vertically to the largest parts of the economy.
Financial Services: In an industry where speed and precision are paramount, autonomous agents can bring real-time decision-making to processes that were once manual or overnight batch jobs. Banks and insurers are beginning to deploy AI agents alongside their workforce, albeit carefully within compliance guardrails. In fact, the market for AI agents in financial services is expected to grow by 815% from 2025 to 2030 as firms invest in these capabilities. The potential applications span nearly every corner of finance. Browser agents can be used to systematically trade on behalf of retail investment portfolios, authorize payments by voice, and gather information on behalf of a Loan Origination System (LOS). Agents will also significantly lower the friction associated with opening new accounts, boosting conversion rates for wealth managers, brokerages, and others.
Healthcare: Hospitals and insurers face enormous operational inefficiencies – according to the American Hospital Association, over 40% of hospital expenses are administrative, as opposed to clinical. There is a huge opportunity for agents to reduce this overhead, accelerate processes, and let healthcare professionals refocus on patient care. Browser agents can navigate EMRs to extract or input patient information. They can help patients fill out online paperwork and assist with appointment creation. And they can help practices submit regulatory documentation to governing bodies and insurance companies.
E-commerce: E-commerce is the primary stage for the rise of agentic commerce, as both consumers and retailers begin to leverage AI agents in the shopping journey. On the consumer side, shoppers are starting to delegate tasks to AI: for example, instead of manually searching and comparing products, they ask a shopping agent to find the best options. Recent research by Adobe found that 24% of online consumers now skip Google entirely and use AI platforms to get curated product recommendations. These agents can handle everything from product discovery to price comparison, and companies like Henry even enable agents to check out on behalf of the user.
The Future of Browser Automation
Browser agents are already driving a step-function improvement to traditional RPA methods. And yet, the commercialization of browser automation began less than two years ago. The tools that drive browser agents are still a work in progress, and with each incremental improvement, they unlock a whole new set of vertical use cases. Across major verticals, new market entrants will operationalize browser agents as a wedge to create major value for their customer base. We’re just beginning to scratch the surface of this hundred-billion-dollar opportunity.