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How AI Is Changing Digital Advertising: Opportunities, Risks, and the Future

Stephanie Pelaez

Written by:  Stephanie Pelaez

  |   Digital Marketing

AI Advertising: Current and future state

Artificial intelligence is transforming every corner of business, and online advertising is no exception.

Generative AI models like ChatGPT, Claude, and Google’s Gemini are no longer experimental toys; they’ve become important digital platforms with growing numbers of users.

Just as search engines defined the previous two decades of digital marketing, there is increasing evidence that generative AI tools may become the new foundation of digital marketing.

With adoption accelerating, it’s clear that the ad industry is on the verge of its next reinvention.

Specifically, the way brands try to reach customers is shifting from targeting static search phrases to understanding the dynamic intent behind conversations with AI chat bots.

One key element of digital marketing that will experience dramatic change is online advertising. Advertising inside AI models is still in its infancy, but, as I will explain below, the implications could be enormous.

The Current State of Advertising in AI Models

Early Experiments and Integration

Tech giants are already testing the advertising waters in AI. Google generates over from advertising, and it has begun rolling out AI-powered search ads to more than 100 million users. In addition, Perplexity has stated that it will introduce “sponsored follow-up questions and paid media positioned to the side of an answer.”

These are more than just experiments; they’re evidence that the next advertising battleground will occur inside AI conversations.

Risks and Opportunities of AI Ads

These new venues for ads bring new questions. Users on Reddit have voiced concerns about transparency and trust, worried that ads might blur into answers without transparent disclosure. Unlike search engines, where sponsored results are clearly separated and labeled, AI responses risk creating “hidden advertising” if platforms fail to establish strong guidelines.

Relevance is both a strength and a weakness in this context. On one hand, AI can deliver ads tailored to a user’s exact intent. If an AI user enters a prompt like, “I’m planning a trip to Rome. Help me find good hotels and affordable flights?”, the AI tool could serve up hotel and airline offers.

On the other hand, excessive personalization risks crossing the line into manipulation. When AI models infer users’ emotions or vulnerabilities, ads can subtly steer decisions rather than support them. The challenge for platforms will be maintaining transparency and user autonomy as personalization grows more powerful.

Challenges for Online Advertisers

For digital marketers, the road ahead is likely to be complex:

  • New focus on metrics: Unlike clicks or impressions for search ads, intent-based engagement metrics will be the key to measuring meaningful actions such as booking or inquiry.
  • Brand safety risks: Ads could appear next to inaccurate or AI-hallucinated until platforms guarantee stronger transparency and brand placement controls. Advertisers can face a real reputational risk every time their ads appear alongside generated content.
  • Regulatory uncertainty: Disclosure rules for conversational advertising remain unclear. The EU’s AI Act is already moving toward strict disclosure and transparency rules, requiring clear labeling of AI-generated or sponsored content. In contrast, the U.S. appears less eager to regulate, leaving brands to navigate a patchwork of voluntary guidelines and industry self-policing.
  • Zero-click marketing: If AI answers every question directly, referral traffic to brand sites could shrink dramatically. However, this also creates a unique opening for advertisers: when organic links disappear, a well-placed ad may become the only clickable pathway. Brands whose ads appear next to authoritative or link-free AI answers can actually reclaim visibility, transforming zero-click moments into high-intent entry points rather than lost traffic.

The Future of Advertising in AI Models

Hyper-Personalized Ad Experiences

AI promises a shift from broad targeting to hyper-contextual relevance. Instead of buying keywords, advertisers will engage based on signals: the meaning, tone, and intent of a user’s prompt. According to , a marketing intelligence platform, this opens the door to real-time offers embedded seamlessly into conversations, ads that feel less like interruptions and more like helpful suggestions.

Ethical and Regulatory Landscape

As the Marketing AI Institute’s 2024 State of Marketing AI Report emphasizes, regulation will be critical. Clear ad labels, consumer privacy protections, and stricter data-use guidelines are on the way, at least in the EU. Platforms must prioritize transparency to maintain user trust, especially as skepticism grows around “hidden ads.”

Evolution of Measurement & ROI

Neil Patel, co-founder of NP Digital, predicts a fundamental shift: from measuring clicks to tracking completed actions. That could mean conversions within the AI experience itself, such as booking a flight or making a purchase directly through the interface. Referral traffic may rebound as AI platforms refine attribution, but the real breakthrough will be measuring conversational outcomes instead of surface-level clicks.

Example: Perplexity’s “Sponsored Follow-Up Questions”

As mentioned earlier, Perplexity has tested sponsored follow-up questions that appear adjacent to conversational answers. Brands like Whole Foods and Indeed have purchased these prompts, which encourage users to dig deeper into a specific topic. Because these prompts are directly tied to how the conversation flows, they offer a more natural attribution path than a standard click in search results.

If a user sees a sponsored follow-up question, engages with it (e.g. by clicking or continuing the thread), the platform can attribute that engagement to the brand’s ad in context. That’s a more conversational outcome than just a standalone ad impression and click.

Marketing Strategy Shift

The keyword/SEO era is still going to persist, but it may not be as robust or important as it was just a few years ago.

As Frederick Vallaeys from Search Engine Journal, puts it: “When advertising shifts to prompts, what should advertisers do?”

The answer: Move from keyword obsession to contextual understanding. In AI-driven environments, ads aren’t triggered by exact phrases but by intent; how users express goals, emotions, or questions in natural language. Successful marketers will think less about search terms and more about conversation design, aligning their message with the meaning behind the query. In this new era for marketers, understanding context will determine visibility and relevance for their brand.

Example: Google AI-Mode & AI-Overview Ads

Google has started integrating ads into its AI-generated “Overviews” (i.e. AI summaries of search results).  In addition, Google has begun briefing brands on “AI Mode” ads, which will show text and shopping ads embedded in conversational or contextual results. In fact, advertisers using Performance Max, broad match, or shopping campaigns are already being included in AI Mode ad exposure automatically (without creating a totally new format). This suggests Google is already enabling some “AI ad” exposure, and brands are being nudged toward formats that respond to context and query semantics (i.e. signals beyond pure keywords).

Conclusion

Advertising in AI models is still in its earliest stages, but the direction is clear. Just as search advertising reshaped digital marketing in the 2000s, AI-driven advertising is poised to define the next decades.

The winners will be those who adapt early, brands that embrace signals over keywords, platforms that prioritize transparency, and consumers who demand value and honesty. The AI revolution in advertising isn’t coming. It’s already here. 

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