For years, brands have spoken about delivering the right message to the right person at the right time. In reality, most websites still present the same layout and content to every visitor. That gap is now narrowing as companies explore what many in the industry call autonomous personalization. Instead of manually creating a limited set of page variations, marketers are beginning to use artificial intelligence to assemble different versions of a website for each individual user in real time.
The core idea behind autonomous personalization is simple. AI systems analyse behaviour, context, traffic source and historical interactions to decide which layout, messaging or content modules are most relevant for each visitor. Two users can land on the same homepage and see entirely different versions of it. This shift is being driven by changing consumer expectations. Surveys conducted over the past year show that more than seventy percent of global users expect some form of personalisation, and a large majority in India prefer websites that remember their preferences and offer tailored choices.
This behavioural shift is also reflected in investment patterns. A recent study indicated that Indian marketers now direct more than sixty percent of their MarTech budgets toward GenAI and decisioning technologies, signalling a move from basic personalisation to deeper, automated models. The industry is increasingly aligning around the idea that manual configuration will not keep pace with fast-moving digital behaviour.
Moving from rules to autonomous systems
Website personalisation historically relied on rules and manual testing. New users saw one banner, returning users another. Marketing teams layered A/B tests over these rules to improve performance over time. Autonomous personalization changes that model. Instead of waiting for marketers to define rules, the AI constantly evaluates signals like scroll behaviour, dwell time, device type, past purchases and category engagement to determine what to show in each moment.
These systems do not simply choose between preset options. In many cases, they can generate new variations of images, copy or page modules using generative AI. The goal is not just optimisation but ongoing adaptation. When deployed widely, autonomous personalization can change the structure of a website more often – and more precisely – than a human team could.
Speaking at an industry forum in 2024, Goda Doreswamy Ramkumar, Vice President of Data Science at Swiggy, described this evolution across digital touchpoints. She said, “Generative AI stands as a transformative force in modernizing customer interactions and content broadcasting.” Although her remarks focused on content flows, the same underlying AI principles are now being applied to how websites render for each user.
Global platforms are also embedding this into marketing infrastructure. Anjul Bhambhri, Senior Vice President of Engineering at Adobe Experience Cloud, noted that Adobe’s recent AI developments are “aimed at embedding intelligence into existing workflows and enhancing enterprise teams’ ability to deliver personalised experiences at scale.” These tools enable brands to personalise web journeys in real time while reducing manual effort for marketing and product teams.
In India, large digital-first brands are exploring similar paths. Ravi Vijayaraghavan, Chief Data and Analytics Officer at Flipkart, commented last year that “AI and ML tools are revolutionising Flipkart’s ability to deliver hyper personalised product recommendations by leveraging vast amounts of user data and advanced personalisation algorithms.” While his emphasis was on recommendations, the same data pipelines are now being used to update layouts, content blocks and promotional modules based on live behaviour.
Where website personalization is gaining traction
Retail, travel, financial services and education are emerging as the earliest adopters of autonomous personalization. These sectors have a mix of logged-in and anonymous traffic, providing rich behavioural signals without always relying on personally identifiable data.
Education platforms, for example, report significant lifts from personalised engagement. One Indian edtech brand recently measured a retention improvement of more than twenty percent after integrating personalised messaging and dynamic web experiences. While the numbers vary across sectors, multiple case studies point to similar results: personalised pages deliver more efficient journeys, higher repeat visits and improved lead quality.
AI advisors argue that the technology behind these journeys is no longer experimental. Industry expert Jaspreet Bindra observed in a 2024 retail essay that “the technology exists for this, with AI algorithms predicting consumer behaviour with remarkable accuracy and tailoring recommendations and content to suit individuals.” That prediction is now playing out across commerce and media, where brands are testing micro-variations in copy, layout and content to see how they influence different segments of visitors.
Globally, experimentation is accelerating. Streaming services reorder rows and artwork based on micro-signals like completion rates and viewing times. Fashion brands test dynamic product grids where pricing sensitivity, browsing history and style cues influence what a user sees first. In hospitality, travel platforms personalise search results pages by location, previous stays and in-session behaviour.
Even B2B companies are experimenting. Some SaaS platforms adjust hero sections, case studies and call-to-action blocks depending on the industry or region of the visitor. A returning enterprise prospect, for instance, may see a proof-of-concept module first, while a new search visitor might see broader product explanations.
Despite these advances, adoption still has ground to cover. A 2024 global study from a leading optimisation platform found that only around thirteen percent of marketers were actively applying AI to deliver personalised website experiences, even though most said they already used basic personalisation. The same research showed that about seventy percent of consumers remained frustrated with generic promotions that did not reflect their interests.
Reflecting on this gap, Shafqat Islam, Chief Marketing Officer at Optimizely, said, “While personalised experiences are a staple in today's marketing landscape, our research exposes a critical gap between intention and execution.” His comments capture the distance between what customers expect and what many brands currently deliver.
What a “unique website for each user” looks like
The phrase can sound dramatic, but in reality, it is implemented through modular design. Brands break their sites into sections such as hero banners, navigation items, category grids, videos, trust badges and forms. The autonomous system then decides, page by page, which combination of modules to show each user.
A new visitor might see broad discovery content and social proof. A returning repeat customer might see quick re-order shortcuts and personalised offers. A user with a history of researching sustainability might find impact stories and ethical sourcing headlines pushed higher on the page.
In India’s mobile-first market, this approach is becoming more relevant across app ecosystems. Large marketplaces already personalise feeds, assortments and offers. Extending the same logic to mobile web and desktop is increasingly seen as essential for consistency across touchpoints.
Experience platforms are packaging this as a set of features that marketing teams can manage without heavy engineering support. AI agents can detect high bounce rates, identify broken journeys or recommend page elements that may perform better. The potential benefits include higher conversion rates and less dependence on manual UX fixes.
Navigating data and trust
While technology is advancing quickly, the ability to personalise responsibly is equally important. Autonomous personalization depends heavily on first-party behavioural data. As third-party identifiers are phased out, brands must ensure that the data they collect is accurate, consented and used transparently.
Privacy expectations and regulatory frameworks are also evolving. Indian marketing leaders often highlight the need to balance relevance with restraint. Brands are encouraged to build opt-in models and clear explanations of how data influences personalisation. This is especially important in multilingual markets, where personalisation must account for cultural nuance as well as user behaviour.
Companies are also setting guardrails for how autonomous systems operate. Some restrict AI from altering brand tone or imagery. Others require human approval of new modules created by generative models. While the ambition is to automate more of the design process, most organisations remain cautious about allowing AI to act without supervision.
The road ahead
Autonomous personalization is still at an early stage, but its direction is clear. Brands are moving from static websites to adaptive digital environments shaped by real-time data and AI decisioning. Early results suggest strong potential. Where personalisation has been applied effectively, companies have seen double-digit improvements in conversion and retention, alongside more efficient marketing spending.
Still, experts caution that autonomous personalization is a gradual journey. Most companies will evolve from simple segmentation to dynamic modules, then to AI-assisted page assembly, and finally to more independent systems capable of designing and testing experiences with minimal manual input.
As Bindra noted, the underlying technology is already capable. The next phase will depend on whether brands can build trust, safeguard data and integrate AI responsibly into their digital experience strategies. With consumers expecting more personalised journeys at every touchpoint, websites that adapt uniquely to each visitor may soon become not just innovative, but expected.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.