From creating videos to buying media and answering customer questions, artificial intelligence is moving into almost every stage of advertising. As Google, Meta and other platforms develop increasingly automated advertising tools, brands face a changing landscape where campaigns can respond to consumers in real time. But will more intelligent advertising necessarily make it more effective?
Imagine searching for a family holiday and receiving more than a sponsored hotel listing. Instead, an AI-powered advertisement explains which property suits the family’s requirements, answers questions about facilities and helps narrow down the options.
Or consider a fashion retailer running a campaign where different audiences encounter variations of the same advertisement, with images, language and product recommendations adjusted according to context.
These possibilities illustrate how artificial intelligence is beginning to change advertising beyond the familiar applications of writing copy and generating images.
For years, digital advertising has been built around creating campaigns, selecting audiences, purchasing media and directing interested consumers towards a website or store.
AI is increasingly connecting these activities.
It can assist with creative development, analyse campaign performance, recommend budget changes and support advertisements that respond to specific customer questions.
Google is testing conversational advertising formats within AI-powered Search, while Meta is expanding tools that help advertisers create, manage and optimise campaigns.
The developments raise a broader question about what advertising will look like when creative production, media buying and consumer engagement become more automated.
The shift is occurring as digital advertising captures a growing share of marketing expenditure.
According to the dentsu exchange4media Digital Advertising Report 2026, India’s advertising industry reached approximately ₹1,21,339 crore in 2025 and is projected to touch ₹1,40,001 crore by 2027.
Digital advertising grew 19% in 2025 to ₹71,621 crore and is expected to approach ₹98,034 crore by 2027, accounting for nearly 70% of total advertising expenditure.
Narayan Devanathan, President and Chief Strategy Officer, South Asia, dentsu, emphasised the importance of bringing “creativity, data, media and technology together” as the industry evolves.
The opportunity extends beyond reducing production costs. AI is gradually changing how advertisements are developed, delivered and experienced.
What Happens When Every Ad Can Be Different?
One of the most visible changes is taking place within creative production.
Traditional advertising campaigns generally begin with a central idea that is developed into a limited number of advertisements for different media formats.
Producing additional variations requires time, resources and creative approvals.
Generative AI can reduce some of those constraints.
A single campaign concept can be adapted into multiple languages, visual formats, product combinations and audience-specific messages without recreating each asset from the beginning.
This is particularly relevant for advertisers operating across fragmented digital platforms.
A consumer goods brand, for instance, could develop different versions of a campaign for regional markets while retaining its central proposition.
Similarly, an ecommerce advertiser could produce product videos using existing images and adapt messaging for different customer requirements.
Industry research suggests advertisers are increasingly considering such applications.
IAB’s 2025 Digital Video Ad Spend and Strategy research found that 86% of digital video buyers were already using or planning to use generative AI for video advertising.
Respondents expected approximately 40% of digital video advertisements to be created or modified using generative AI by 2026.
These figures reflect buyer expectations and intentions rather than a verified measure of all advertisements produced.
Nevertheless, they indicate the growing role of AI in creative workflows.
Meta has expanded generative tools that convert product imagery into video and support the development of creative variations. Google has similarly incorporated Gemini capabilities into advertising production and campaign management.
However, the ability to produce more advertisements introduces another challenge.
Canva’s 2026 State of Marketing and AI study, conducted with The Harris Poll among 1,415 marketing leaders and 3,547 consumers across seven countries, including India, found that 97% of marketing leaders used AI in their daily creative work.
Yet 70% of consumers said they could usually recognise AI-generated advertising because something appeared to be missing. Another 87% believed effective advertising still required a human touch.
At the same time, 68% said they were comfortable with AI-supported advertisements when they were useful or relevant.
“AI has changed how marketing gets made, but not what makes it effective,” said Emma Robinson, Head of B2B Growth Marketing at Canva.
The findings suggest that faster production does not automatically translate into stronger communication.
An advertiser may produce 50 variations of a campaign, but those versions still depend on the strength of the original idea.
As AI reduces production barriers, creative teams may increasingly spend more time deciding what should be communicated rather than producing every individual execution.
Could AI Start Managing the Media Budget Too?
The next change is taking place behind the advertisement.
Programmatic advertising has already automated significant parts of digital media buying, including the selection and delivery of advertising inventory.
Agentic AI could extend this automation by analysing campaign outcomes, recommending changes and carrying out certain activities within defined parameters.
Instead of requiring teams to continuously examine separate dashboards, AI systems could identify performance patterns and suggest adjustments to creative, audience targeting or expenditure.
IAB’s 2026 Outlook Study, involving 205 US buy-side advertising decision-makers, found that 66% planned to increase their focus on agentic AI for buying and campaign execution.
Among respondents familiar with agentic systems, 93% were using or likely to use them for performance analysis, while 91% indicated interest in creative testing and optimisation.
Another 84% cited media planning and buying recommendations, and 82% identified budget allocation and pacing.
However, willingness was lower for activities involving commercial negotiations and direct advertising deals.
This indicates that advertisers are more prepared to automate analytical and operational processes than surrender control over commercially sensitive decisions.
Consider a campaign operating across search, social media, connected television and ecommerce platforms.
An AI-supported system could examine performance across those channels and recommend moving expenditure towards better-performing placements.
It could also identify creative variations that are attracting attention without generating meaningful conversions.
These applications could allow planners to spend less time compiling reports and more time evaluating campaign strategy.
Google’s Ask Advisor initiative is designed to support advertisers across products including Google Ads, Analytics and Merchant Center. Meta has also been developing an AI business assistant for campaign-related guidance.
Such tools indicate movement towards advertising systems that support connected decisions rather than isolated tasks.
However, automation also depends on reliable information.
An AI system optimising towards inaccurate conversion data could redirect expenditure towards activities that appear successful without delivering the intended business results.
Consequently, marketers would still need to establish campaign objectives, performance measures and approval requirements.
AI may change how advertising decisions are executed, but responsibility for those decisions remains with advertisers.
What If an Advertisement Could Answer Back?
Perhaps the most noticeable change for consumers could come from the advertising format itself.
Conventional digital advertisements typically encourage an action. A consumer sees a promotion, clicks it and moves to another page to find additional information.
AI-powered conversational formats could bring more of that interaction into the advertisement.
At Google Marketing Live 2026, the company announced tests of Conversational Discovery ads and Highlighted Answers within AI-powered Search.
The formats are designed to provide advertising experiences connected to the details of a user’s question.
Google has also been testing shopping advertisements capable of generating product explanations and tools that allow consumers to interact with businesses directly through advertising experiences.
The distinction is significant.
A consumer looking for running shoes might ordinarily encounter several sponsored listings before comparing product specifications independently.
An AI-supported advertisement could potentially address questions about terrain, fit or product suitability during the discovery process.
Similarly, a prospective hotel guest could seek information about accommodation features without immediately navigating through several websites.
These formats remain subject to testing and availability, and their eventual commercial impact is not yet established.
Nevertheless, they demonstrate how advertising could move from simply presenting information towards participating in a conversation.
Consumer behaviour is also changing.
Kantar’s Media Reactions 2026 study, covering more than 23,000 consumers across 33 markets and 800 senior marketers, found that 73% of consumers used AI assistants in their personal or professional lives.
Thirty-three per cent were already using AI assistants to research brands and products.
A net 75% of marketers planned to increase investment in visibility within AI assistants in 2027, including advertising.
However, only 24% of consumers said they trusted brand recommendations made by AI assistants.
The contrast illustrates both the commercial opportunity and the challenge associated with advertising inside AI experiences.
As consumers increasingly use conversational systems to research products, brands may need to ensure their information is accurate, accessible and understandable to those systems.
Product details, pricing, availability and reliable external references could influence how a brand appears within AI-generated responses.
WARC Managing Editor Paul Stringer observed that “the established model for media planning and buying is breaking apart.”
The emerging environment may require marketers to consider not only where advertisements appear, but also how AI systems interpret and present information about their brands.
How Personal Can Advertising Get Before It Feels Intrusive?
Greater automation also makes personalisation more sophisticated.
AI can combine contextual signals with creative generation to produce advertising that appears more relevant to individual situations.
A retailer might promote different products depending on location or availability. A travel advertiser could present different accommodation options based on the information a consumer voluntarily provides.
Such applications could reduce irrelevant messaging.
However, personalisation becomes more complicated when consumers are uncertain about how an advertiser obtained or interpreted their information.
Canva’s 2026 research found that 52% of consumers considered an advertisement excessively personal when it appeared to know what they intended to purchase before they had searched for it.
Another 58% said they did not want brands using AI to predict their preferences.
Meanwhile, 74% indicated they would feel more comfortable with AI-supported advertising if companies had formal policies governing its use.
These findings suggest that relevance and consumer comfort do not always increase together.
An advertisement can be technically accurate in predicting an interest while still creating concerns about privacy.
For advertisers, this introduces questions around consent, transparency and the limits of automated targeting.
Brands may also have to reconsider how they evaluate advertising effectiveness.
Producing more creative variations, optimising expenditure faster or generating additional interactions does not necessarily demonstrate that a campaign has improved brand awareness or commercial performance.
Measures such as incremental sales, customer response, brand recognition and long-term business outcomes remain relevant.
The implications are particularly important in India’s expanding digital advertising market, where brands are managing increasingly diverse consumer journeys across search, social media, video and commerce platforms.
AI could support those journeys by making advertisements more adaptable and responsive.
But the emerging advertising model is unlikely to become entirely automated in the near term.
Industry research indicates that advertisers remain cautious about delegating sensitive decisions, while consumers continue to value authenticity and human judgement.
The distinction between what AI can produce and what audiences are willing to accept will influence how quickly these formats develop.
Advertising is already moving beyond fixed creative assets and conventional media plans. Some campaigns can now be assembled dynamically, performance can be monitored through AI-supported systems and new formats are being designed to respond to consumer questions.
The larger change may therefore be less about replacing advertisements with AI-generated content and more about changing the relationship between brands and consumers. As advertising becomes increasingly responsive, the test will be whether these capabilities make communication more useful and effective, rather than simply making it faster, more personalised and more abundant.
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.