Google’s SGE vs. Meta’s AI Ads: How Generative AI is Reshaping Search and Social Marketing

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The rapid rise of generative AI is transforming how both search engines and social platforms serve users and advertisers. Google’s Search Generative Experience (SGE) is reinventing the familiar search results page, while Meta is planning to fully automate social media advertising by 2026 with AI. These developments have sparked debates in the SEO and marketing communities – from fears about declining organic traffic to excitement about more efficient ad campaigns. In this comprehensive report, we explore Google’s SGE and its impact on SEO/paid search alongside Meta’s AI-driven advertising revolution, providing a balanced look at opportunities and challenges for marketers. High-quality content, strategic adaptation, and a focus on user needs emerge as key themes in navigating this new landscape.

SGE: Google’s Search Generative Experience and the Evolution of Search

Google’s Search Generative Experience (SGE) is an AI-powered enhancement to Google Search that generates rich, conversational answers directly on the results page. Launched in 2023 via Search Labs, SGE uses generative AI (similar to ChatGPT) to provide summarized answers with cited sources for user queries (searchenginejournal.com). In essence, Google is transforming from a search engine into an “answer engine,” where users can get immediate answers without clicking through multiple results. As one BrightonSEO speaker noted, the classic “10 blue links” are giving way to this new answer-focused format (wavemakerglobal.com).

How SGE works: When SGE is enabled, Google’s algorithms pull content from indexed webpages and use AI to compile a conversational answer to the query, often with a few source links displayed. Follow-up questions can be asked within the search interface, making the experience more interactive. This is a big leap from traditional featured snippets – SGE responses are longer, more comprehensive, and occupy much more screen real estate than a single snippet or link (searchenginejournal.com) (searchenginejournal.com). By citing multiple sources and even pulling in information from pages beyond the top 10 results, SGE aims to provide users a quick, trustworthy overview on the SERP itself (searchenginejournal.com).

Google’s motivation: The push for SGE is partly a response to competition from AI chatbots (e.g. Bing’s AI search and ChatGPT). Nearly half of consumers (49%) have expressed interest in AI-powered search results (searchenginejournal.com), indicating a positive perception of such features. Google is betting that integrating AI answers will improve user experience and keep users on Google’s platform longer. In an earnings call, Google’s leadership doubled down on SGE as a long-term investment, signaling that this is not a short-lived experiment (searchengineland.com). While concerns exist, Google appears committed to making SGE a permanent part of search results to stay competitive in the AI era.

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SEO in the Age of SGE: Impact on Organic Traffic and Content Strategy

The SEO community has been intensely debating the impact of SGE on organic search traffic. With AI answers taking a prominent spot, many worry that fewer users will click on traditional organic results. Early analyses and conference discussions indicate that some decline in organic clicks is likely, especially for informational queries where the answer is fully covered on the SERP (searchenginejournal.com). A reasonable assumption is an organic traffic drop of up to ~30% for affected queries, based on parallels to how featured snippets reduced clicks in the past (searchengineland.com). At BrightonSEO 2024, experts noted that initial data and annual SERP comparisons suggest significant traffic dilution for top-ranking pages when SGE appears (fox.agency).

However, SGE “will not kill organic traffic, it will just evolve” the nature of SEO (fox.agency). This was a key message from speakers at BrightonSEO (including Tom Capper, Kapwom Dingis, and Marcus Tober) who shared their SGE findings. They acknowledged an inevitable decrease in clicks for simple fact-based queries (think weather, definitions, time zones) since users get what they need directly from Google. But they also argued that SEO is far from dead – instead, it must adapt. Generative AI cannot fulfill every information need, especially for users seeking in-depth information, diverse opinions, or official sources. In those cases, users will still click through to websites. In short, SEO is shifting to focus more on content depth, quality, and unique value, rather than just winning the top blue link for a quick answer.

Why SEO isn’t “dead”: SGE still relies on web content – it learns from indexed pages and even cites them. Notably, SGE sometimes cites pages that aren’t in the top 10 traditional results, broadening exposure for authoritative content beyond just the #1 position (searchenginejournal.com). If your page offers comprehensive, trustworthy information, it has a chance to be referenced by SGE, potentially offsetting some traffic loss. Moreover, many queries (especially those with “commercial” or research intent) will drive users to click for more details. As one expert put it, SGE is like “featured snippets on steroids,” meaning sites that provided only quick answers will suffer the most, while those offering deeper value can still attract clicks (searchenginejournal.com). For example, trivial FAQ-style content may see drop-offs, but original research, long-form guides, case studies, and product information are more likely to entice users to read further.

Adapting SEO strategy: Given these changes, SEO practitioners are shifting tactics. Key recommendations include:

• Emphasize E-E-A-T (Experience, Expertise, Authoritativeness, Trust): High-quality, expert-backed content is “AI bullet-proof”. If your content demonstrates real expertise or unique insight, SGE and users will regard it as valuable. Google’s algorithms (and SGE’s sources) still prioritize content with strong relevance, credible backlinks, and good user experience signals.
• Move beyond simple informational content: Sites built on answering simple questions should evolve by providing added value. This may mean covering topics more thoroughly (beyond just the basics), including analysis, examples, or up-to-date insights that a generic AI summary might miss (searchenginejournal.com). Some SEO experts suggest focusing more on “transactional” or deep informational content that naturally drives the reader to learn more on your site.
• Optimise for engagement and branding: With reduced visibility on SERPs, having a loyal audience and strong brand can mitigate traffic loss. If fewer new visitors click through, repeat visitors and direct traffic (from people who trust your brand) become crucial. This implies investing in brand-building, community, and other channels (email, social) so that your audience seeks you out deliberately.
• Monitor zero-click metrics: Expect a spike in “zero-click searches” (queries that don’t result in a website click). This challenges traditional success metrics. SEOs will need to measure value in new ways – for instance, tracking when your content is cited in SGE or focusing on conversions and engagement from the traffic you do get, rather than pure click volume.

In summary, SEO is entering a new phase. The fundamental practices of creating quality content and technically optimizing your site remain, but success will hinge on differentiation and understanding user intent better. As Nikki Lam (VP of SEO at NP Digital) advises, SEOs should “ensure your brand’s content surfaces in conversational and generative AI tools” and not just aim for old-school rankings (neilpatel.com). The consensus at Brighton was clear: SEO isn’t dying – it’s adapting to a landscape where AI-generated answers handle the simple stuff, and human-created content shines by going deeper.

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Google SGE’s Impact on Paid Search: What Happens to Ads?

Google’s revenue still heavily relies on advertising, so it’s no surprise that even as the search interface evolves with SGE, ads remain a critical element of the results page. Early research into SGE’s rollout indicates that it is affecting where and how ads appear on Google. An extensive study by SE Ranking (an SEO platform) analysed 100,000 keywords across various niches to map ad placements in SGE-enhanced SERPssearchengineland.com. The findings give us a peek into Google’s strategy:

• Top vs. bottom ads: In queries that triggered an SGE answer, traditional text ads were actually more likely to be shown at the bottom of the page (35% of cases) than at the top (23%) (searchengineland.com). This suggests that SGE often occupies the prime top space, pushing text ads down. However, when SGE is present, Google still frequently shows at least one ad – either above or below the AI snippet – in roughly 73% of cases, with only about 27% of SGE queries having no ads at all (searchengineland.com).
• Shopping ads get prominence: For commercial queries, Shopping ads (product image carousels) often appear above the SGE answer (searchengineland.coms). In fact, the study found that in ~81% of instances where shopping ads were shown, they were positioned on top of the SGE box. Google seems to prioritise showcasing product listings and visuals prominently, which aligns with its push to enhance the e-commerce experience on search. Niches like fashion, beauty, and retail searches were especially likely to trigger shopping carousels alongside SGE.
• Ads are still in the mix: Importantly, sponsored results can appear above the SGE snippet – especially text ads for certain queries and of course shopping units. Google has tested labelling these ads clearly in the new interface. From a marketer’s perspective, this means PPC (pay-per-click) opportunities haven’t disappeared; instead, the layout is being shuffled. In scenarios without an SGE answer, ads continue to behave normally (top of page as usual). But when SGE is active, you might find your search ads lower on the page or sharing space with AI content.

Google is iterating quickly on how ads integrate with SGE. In 2024–2025, Google began testing ads directly within the SGE conversational answers as well. For example, at Google Marketing Live 2025, the company announced that even AI-generated search results will include ad slots (marked as “Sponsored”) in line with the answer, ensuring monetization continues (xponent21.com). Advertisers can expect new formats where an AI answer might be followed by a few ads relevant to the query’s intent, possibly with images or generative elements. This blurs the line between organic and paid content but confirms that paid search is here to stay – just in new guises.

Beyond placement, Google is also using AI to help advertisers. Performance Max campaigns (launched 2021) already utilise machine learning to automate ad placement across Google’s channels (Search, YouTube, Gmail, etc.), and now Google is adding generative AI to create ad assets. In early 2025, Google introduced an “AI Max” upgrade for Search campaigns, allowing one-click generation of new ad headlines, descriptions, and even image assets using generative AI (januarydigital.com) (searchengineland.com). Early tests showed this could boost conversions ~27% without harming cost efficiency (januarydigital.com). Essentially, while Meta is automating the entire campaign process (as we’ll discuss next), Google is also moving toward more automated and AI-driven advertising – just in a somewhat more incremental way, layering AI onto existing ad systems like Google Ads.

Key takeaway: Google’s SGE does change the dynamics of paid search: advertisers may need to adjust bids and strategies knowing their ads might show lower on the page or alongside AI content. Tracking performance in SGE vs. non-SGE results becomes important. On the flip side, Google is arming advertisers with more AI tools (like generative asset creation and automated targeting through Performance Max/AI Max) to optimise campaigns. Marketers should stay informed on these updates – the ad formats and best practices of yesterday are evolving rapidly alongside the search experience.

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Meta’s AI-Powered Advertising Revolution: Full Automation by 2026

In the social media realm, Meta (Facebook & Instagram) is undergoing its own AI transformation – not on the user-facing feed content, but in the advertising backend. Meta has announced ambitious plans to fully automate ad creation, targeting, and optimisation with AI by the end of 2026 (vxtx.co.uk). In practical terms, Meta envisions a “goal-only” ad system where an advertiser simply inputs their objective and some basic creative material, and the AI handles the rest (vxtx.co.uk). This could fundamentally change how businesses (especially small ones) run campaigns on Meta’s platforms.

Here’s what Meta’s plan entails, as reported by Reuters and Meta’s own briefings:

• “One-Click” Ad Generation: A brand will be able to provide minimal input – say a product image and a budget – and Meta’s AI will generate the entire ad campaign from that (reuters.com). This includes creating the ad copy, imagery or video, choosing targeting criteria, adjusting bids, and allocating budget across Facebook and Instagram. Mark Zuckerberg described it as an AI one-stop shop where businesses set their goals and budget, and the platform handles the logistics from there (reuters.com).
• Key AI components: To achieve this, Meta is leveraging several AI tools:
  • AI Sandbox: a suite of generative AI tools for creating variations of ad copy, images, and even short videos automaticallyvxtx.co.uk. (For example, AI can generate different background visuals or text versions to test.)
  • Meta Lattice: a new machine learning architecture trained on trillions of ad data points (vxtx.co.uk)(vxtx.co.uk). Meta Lattice is designed to optimize targeting and delivery. Instead of advertisers manually defining audiences, the AI analyses user behaviour and conversion data across Meta’s apps to find the right people for your ads. It can discover high-potential audiences without preset targeting and improve results even if an advertiser has minimal previous data (helpful for new advertisers) (vxtx.co.uk).
  • Advantage+ suite: Meta has been rolling out features under the “Advantage+” label that automate various campaign aspects. Advantage+ campaigns automate placements, budget allocation, and bidding, outperforming many manual setups. For instance, Advantage+ Shopping Campaigns were shown to deliver +22% higher return on ad spend (ROAS) on average compared to manually managed campaigns (vxtx.co.uk). These are early building blocks toward the fully automated future.
• Timeline: The shift is happening in stages. Since 2023, Meta introduced tools like the AI Sandbox (for generative creative) and expanded Advantage+ globally (vxtx.co.uk)(vxtx.co.uk). In 2024, they are focusing on integrating generative AI into Ads Manager for broader use. By 2025, Meta expects to have an alpha version of “goal-only” campaigns in testing, and by 2026, end-to-end AI-driven ad creation should be broadly available (vxtx.co.uk). Each year is bringing Meta closer to that vision.

Meta’s end goal is to make advertising so simple that even a local business owner with no marketing team can launch an effective campaign. As the VXTX marketing blog put it, this “reduces time-to-launch and lets SMEs run campaigns like pros” (vxtx.co.uk). In early trials, Meta’s AI-driven campaigns have already matched or outperformed human-managed ones in metrics like ROAS and conversion rates, especially when targeting broad audiences (vxtx.co.uk). The implication is that the AI can optimise across so many data points (far more than a human could crunch) that it finds efficiency gains on its own.

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Opportunities and Risks of Fully Automated Ads

The prospect of AI-generated, AI-optimised ads offers clear opportunities: it promises to save time, lower the expertise barrier, and potentially improve performance through machine-driven optimisation. But it also comes with significant challenges and uncertainties for marketers, agencies, and even the platforms themselves. Let’s break down both sides as Meta leads this charge (and Google and others follow in their own ways).

Benefits and Opportunities

• Access and efficiency for advertisers: The most immediate benefit is that advertising becomes easier and more accessible to everyone. Small businesses and solo entrepreneurs who might lack in-house expertise or large budgets could let the AI handle complex tasks. Meta’s tools, for example, would allow a mom-and-pop shop to simply upload a product photo, set a budget, and trust the system to find the right customers. This lowers the skill threshold and empowers small advertisers to get “pro-level” results without a full team (vxtx.co.uk).
• Faster creative iteration: AI can generate countless variations of ad text, images, and videos in a fraction of the time it takes a human team. This means more rapid testing and optimisation. Advertisers can quickly discover what messaging or creative works best. Google’s generative ad tools similarly let you “supercharge” campaigns by creating new assets on the fly (datafeedwatch.com). The result should be campaigns that improve continuously and respond to trends or seasonality instantly.
• Personalisation at scale: One exciting aspect is the ability to tailor ads to individuals. Meta indicated that its AI will personalise ads so that users may each see a different version of the same ad, optimised for their profile and context (e.g. location, interests) in real time (reuters.com) (reuters.com). This kind of micro-targeting and dynamic creative optimisation could boost engagement, as people see ads that feel more relevant.
• Better performance (in theory): If the AI is doing its job, it should allocate budget to the best opportunities, find untapped audiences, and even adjust bids faster than any human can. Meta’s early data and third-party studies suggest AI-managed campaigns can yield higher conversion rates and ROI than manual campaigns, especially for broad targeting where the AI has more freedom to explore (vxtx.co.uk). Google’s automated campaigns likewise tout improved results (Performance Max case studies often report better conversion volume at similar cost). For marketers, this could mean better outcomes with less effort.

Challenges and Risks

• Loss of control and transparency: Handing over the keys to an AI means advertisers might lose some insight into why things are happening. Meta’s system will be a black box in many ways – decisions on who sees the ad, how the budget shifts, etc., are made by algorithms that aren’t fully transparent. Marketers worry about “opaque optimisation decisions,” where the AI chooses audiences or creatives and you can’t easily tell why (vxtx.co.uk). This lack of visibility can be uncomfortable, especially when trying to explain results to stakeholders or ensuring your ads align with strategy.
• Brand safety and consistency: Another major concern is maintaining brand voice and quality when AI is writing your copy or designing your visuals. AI might generate something off-brand or even problematic. For example, an auto-generated image might have the wrong vibe, or text might inadvertently misrepresent the product. The VXTX blog warns that brands risk losing control over tone and style unless they provide clear guidelines (prompt libraries) and do human quality checks (vxtx.co.uk). Essentially, companies will need to feed the AI with brand rules – e.g. preferred colours, phrases to avoid, desired messaging – and still plan to review AI outputs. Human oversight remains vital to prevent embarrassing or inconsistent ad content.
• Regulatory and ethical issues: As AI takes a bigger role, regulators are paying attention. There are growing calls (especially in the EU) to label AI-generated content and ensure transparency in automated decision-making. In advertising, this could mean requirements to disclose when an ad was AI-created or personalised by AI. Meta acknowledges that new compliance pressures are likely – marketers should be prepared to log AI-generated materials, explain ad targeting in certain cases, and follow guidelines on data usage (vxtx.co.uk). Privacy is another factor: AI systems like Lattice use heaps of user data to target ads, which could raise data protection questions. Companies will need to stay abreast of laws and platform policies (for instance, the FTC in the U.S. might issue rules on AI advertising).
• Over-reliance and creative stagnation: If everyone uses the same AI tools, could ads start looking and sounding the same? There’s a risk of creative homogenisation – AI, after all, often draws from existing data patterns. Without human input, brands might lose the distinctiveness of their campaigns. Also, an AI might favour a formula that works “OK” but misses out on breakthrough creative ideas that only humans would test. Smart marketers will likely use AI for efficiency but still inject human creativity to stand out. As one marketing leader noted, “AI will let humans focus on what matters” – strategy, big-picture ideas, and nuanced creative direction (vxtx.co.uk).
• Impact on jobs and agencies: The move to automation inevitably raises the question of what happens to marketing teams and agencies. If AI handles campaign setup, does that eliminate the need for campaign managers, media buyers, or even creative staff? In the short term, roles will indeed shift. Routine tasks like manual bid adjustments, basic copywriting, or audience research might be reduced. But rather than a total replacement, it’s more of a role evolution. Agencies and marketers will need to pivot to higher-level functions – strategy, analytics, AI oversight, and cross-channel integration (vxtx.co.uk). At BrightonSEO and other industry events, a common theme is that AI is a tool to enhance human marketers, not a substitute. Human expertise is still needed to set goals, interpret results, and ensure the AI aligns with business objectives. In fact, new specialties may emerge (like prompt engineers or AI auditors). The consensus is that agencies that adapt (by offering strategic guidance, creative storytelling, and multi-platform coordination) will remain very relevant. Those stuck only on execution might struggle as execution becomes automated.

In summary, fully automated ads bring a double-edged sword. The efficiency and scale benefits are tremendous, but smart oversight is required to harness them properly. Companies like Meta are proceeding with optimism – they believe reducing friction in ad creation will encourage more businesses to advertise and thus grow the pie for everyone. Still, as marketers, we should approach these tools with both enthusiasm and caution: test them, but also put in guardrails (brand guidelines, human review cycles, etc.). The winners will be those who combine AI’s speed and data-crunching with human creativity and judgment.

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Preparing for an AI-Driven Marketing Future (Search & Social)

Given the sweeping changes in both search and social advertising, what should marketers and businesses do to stay ahead? Here are some actionable steps and strategies gleaned from expert recommendations:

• Stay educated and experiment early: Both Google and Meta are continuously updating their AI offerings. Keep up with industry news and platform announcements. If you have access to beta features (like Google SGE in Labs or Meta’s Advantage+ and AI Sandbox tools), try them out on a small scale. For example, pilot Meta’s Advantage+ campaigns or AI creative tools with 10-15% of your ad spend to see how they perform (vxtx.co.uk). Similarly, experiment with Google’s Performance Max or new AI ad features on a subset of campaigns. Early familiarity will be invaluable.
• Develop an “AI readiness” framework: This might include creating prompt guides for AI tools (defining your brand’s tone, do’s and don’ts for the AI to follow) (vxtx.co.uk), and training your team on how to work alongside AI. Build internal knowledge on crafting good prompts, using analytics to verify AI decisions, and spotting AI mistakes. Essentially, invest in up-skilling staff – today’s SEO or PPC specialist should also be comfortable supervising AI outputs and providing the right inputs.
• Double down on content quality and uniqueness: In SEO, as discussed, content that offers something unique will stand out in an AI-dominated SERP. Identify what perspectives, data, or expertise your brand can bring that a generic AI summary can’t. This could mean conducting proprietary research, producing expert interviews, or creating interactive tools – anything that adds value beyond a Wikipedia-style answer. High-quality content is more likely to be referenced by SGE and also more likely to engage users who do click through.
• Optimise for new metrics and features: As zero-click searches rise, find ways to measure brand visibility beyond clicks. For instance, are you being cited as a source in SGE? Are people searching for your brand name (indicating they saw you in an AI snippet)? Also, watch for new Google Search Console or Bing webmaster tools reports that may cover AI impressions. On the paid side, start tracking performance in AI-heavy environments: if Google provides reports on SGE ads or if Meta provides AI campaign transparency, use those to adapt your tactics.
• Maintain a human touch in advertising: Even if you use Meta’s automated ad generation in 2026, always review and refine the outputs manually. Set up workflows where human marketers approve AI-generated content and test different creative angles. Continue to brainstorm original campaign ideas – use the AI to handle grunt work, but feed it with creative concepts that come from human insight. By blending human creativity with AI efficiency, you’ll get the best of both.
• Monitor policy and privacy developments: Be prepared for changes in what data you can use and how you must disclose AI usage. For example, if regulations require labeling AI-generated ads, incorporate that into your ad assets or metadata. Make sure you have consent for data that feeds into AI models (customer data, etc.). Keep an eye on the EU’s and FTC’s guidelines around AI in advertising (vxtx.co.uk) – compliance is not optional, and getting it wrong could be costly in terms of fines or reputation.
• Focus on strategy and big-picture value: With algorithms handling more tactical work, marketers should allocate more time to strategy. This means deeply understanding your customers and craft campaigns that align with business goals. SEO and PPC efforts should be tied to overall customer journey planning, not siloed. Use the time saved by AI to do things like user research, creative testing, or improving your website’s user experience. Those are areas where humans still have the edge.

The bottom line: the future of marketing is symbiotic with AI. In search, embracing AI-driven SERPs while continuing to push for quality will ensure you stay visible. In social advertising, welcoming AI automation while steering it wisely will keep your campaigns effective. Neither arena is a simple “set and forget” – success will come from those who actively manage these AI tools and adapt to the insights they provide. As we’ve seen, Google and Meta are setting the stage for an AI-centric 2025 and beyond; now it’s up to marketers to play on that stage skillfully.

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Frequently Asked Questions (FAQ) on SGE, SEO, and AI Advertising

Q1. What is Google’s Search Generative Experience (SGE)?

A: SGE is Google’s experimental AI-powered search feature that generates a conversational answer at the top of your search results. It uses generative AI to summarise information from across the web and present it directly on the Google results page, complete with source citations (searchenginejournal.com). In other words, instead of just showing a list of links (“10 blue links”), Google can provide an AI-generated answer to your query right within the search results.

Q2. How is SGE different from a normal Google search?

A: In a normal Google search, you see web page results and maybe a brief snippet for each. With SGE enabled, you’ll often see a large highlighted box containing an AI-generated summary of the answer you’re looking for, above the regular results. This summary is compiled from multiple sources and written in a conversational tone. You can also follow up with additional questions in the search interface. Essentially, SGE turns Google into more of an interactive Q&A or chat, rather than just a list of ranked webpages.

Q3. Will SGE kill SEO and organic search traffic?

A: No – SEO is not “dead,” but it is evolving. It’s true that SGE can reduce clicks on organic results (some estimates say up to a 30% drop in traffic for certain types of queries). Users might get their answers without leaving Google, especially for simple factual questions. However, SEO experts widely agree that good content will still get traffic. Generative AI answers can’t satisfy every need – users who want depth, detailed information, or diverse perspectives will click through to websites. In short, SGE is changing how people interact with search, but it won’t eliminate the need for search engine optimisation. Instead, SEO best practices are shifting toward making sure your content is high-quality, authoritative, and provides value beyond what an AI summary can show.

Q4. How can I optimize my content for SGE?

‍‍A: To increase your chances of being featured or cited in SGE’s AI summaries, focus on expert, trustworthy content and answer questions comprehensively. Incorporating clear headings, FAQ sections, and concise answers within your content can help – similar to optimising for featured snippets. Also, ensure your site is technically sound (fast, schema markup where appropriate) so Google can easily extract information. Remember that SGE sometimes pulls from pages beyond the top 10 results, so even if you’re not ranking #1, a high-quality answer on your page could be included. Monitoring what questions your audience is asking (and then addressing those in your content) is key. In a nutshell: write for the user, provide authoritative answers, and structure your content well, so that Google’s AI finds your material useful to draw upon.

Q5. Does SGE affect Google Ads and PPC campaigns?

A: Yes, it does have some impact on how ads appear. With SGE taking up space at the top, Google Ads (PPC text ads) are often pushed further down the page in the new layout. A study found ads in SGE results showed up more at the bottom of the results than the top. However, Google still shows ads – sometimes even above the SGE box (especially shopping ads). Google is also starting to inject ads into the AI-generated answer portion itself. For advertisers, this means you need to be aware that your search ads might not always be in the top slot; they could be below an AI answer or in a carousel. It’s important to keep an eye on performance and perhaps adapt your ad copy or use image assets (for Shopping) to remain visible. The good news is that Google is not removing ads from search; they’re just repositioned in the context of SGE.

Q6. What is Meta’s plan for AI in advertising by 2026?

A: Meta (which owns Facebook and Instagram) has announced a plan to fully automate the ad process with AI by the end of 2026 (vxtx.co.uk). The idea is that an advertiser will simply choose a marketing goal (like “increase online sales”), input a few basic things (maybe a product image or a URL), and the AI will create the ads, decide who to target, and optimise the campaign automatically. Meta is developing advanced AI models (like Meta Lattice) and tools (like the AI Sandbox for generating ad creatives) to make this happen. Essentially, Meta wants to make running ads as easy as “tell us your goal and budget, and our AI will do the rest.”

Q7. How would fully automated ads on Meta actually work?

A: In a fully AI-driven Meta campaign, you might upload an image of your product and a short description, set your overall budget and target outcome (e.g. website purchases), and then let the system go. The AI would generate different versions of your ad – various text captions, image styles, or video clips – using generative AI. It would test these across Facebook, Instagram, Messenger, etc., to find what works best. The AI (via Meta Lattice and other algorithms) would also handle targeting, meaning it decides which audiences to show the ads to, based on likelihood to convert (vxtx.co.uk) (vxtx.co.uk). It will adjust bids and budgets in real time to maximise results. Throughout, it’s learning which creative and audience combinations give the best ROI, and it continues to tweak the campaign. For the advertiser, this could mean less manual tweaking – you’d mostly monitor high-level results and maybe tweak the goal or provide new creative inputs if needed.

Q8. What are the advantages of AI-generated ads for advertisers?

A: The big advantage is efficiency and ease. It drastically cuts down the time and expertise needed to launch campaigns. Small businesses who can’t afford dedicated marketing staff could run effective ads without needing to know the intricacies of targeting or A/B testing – the AI handles that. AI can also personalize ads on the fly; for example, Meta’s system might show different ad variants to different user segments (youth vs. older users, different locales, etc.) to improve relevance. Moreover, AI can react quickly to performance data, adjusting campaigns faster than a human could. Overall, advertisers may see better performance (like more conversions for the same spend) because the AI optimises continuously and explores a huge combination of factors (audiences, creatives, timings) simultaneously. It’s like having an expert marketer working 24/7 on your campaign, albeit an artificial one.

Q9. What are the risks or downsides of relying on AI to create and target ads?

A: One risk is losing some control and transparency. When AI is making decisions, you might not always understand why your budget was spent a certain way or why a particular audience is being targeted – the AI’s “thought process” can be a black box. This can make some advertisers uneasy. There’s also a brand safety concern: AI might generate ad content that doesn’t match your brand voice or, worst-case, says something inappropriate. Without human oversight, errors or off-brand messaging could slip through. That’s why it’s important to set guidelines for the AI and still review what it’s doing. Another downside is that if everyone uses the same AI, ads might become very similar and less creative (diminishing differentiation). Finally, there’s the data privacy and regulatory aspect – using AI heavily means using a lot of user data, so advertisers will need to be mindful of regulations and ensure AI-targeting doesn’t inadvertently discriminate or breach privacy laws (vxtx.co.uk). In short, AI ads are powerful but need to be managed carefully to avoid pitfalls.

Q10. Will AI-driven advertising replace human marketers and agencies?

A: It will certainly change their roles, but not entirely replace them. Routine tasks like setting up basic campaigns or doing initial targeting might become automated. However, human expertise is still crucial for strategy, creative direction, and interpretation of results. Agencies and marketing teams will likely pivot towards higher-level functions – for example, developing the overall campaign strategy, crafting brand messaging, and feeding the AI the right inputs. As Meta’s CMO put it, AI will handle the grunt work and “let humans focus on what matters” (vxtx.co.uk), such as strategy, big creative ideas, and nuanced optimisations. There will always be a need for human oversight to ensure the AI is aligned with business goals and brand values. So, while fewer people may be needed for manual campaign management, there’s growing demand for those who understand both marketing and AI to guide these systems. Agencies that adapt by offering strategic consulting, creative services, and multi-platform expertise will still thrive in an AI-driven ad world.

Q11. How are Google’s AI efforts in ads different from Meta’s?

A: Both companies are infusing AI into advertising, but their approaches reflect their platforms. Google’s AI in ads (through things like Performance Max and the new AI features in Google Ads) is somewhat incremental – it helps automate bidding, placements across Google’s ecosystem, and even create some assets (like suggesting headlines or generating simple images). However, advertisers still typically provide a lot of the creatives and have oversight. Google’s AI also extends to search itself (with SGE), so they’re integrating ads into a new search experience. Meta’s approach is moving toward fully automated campaigns where the AI might do everything end-to-end. Also, Meta’s focus is on generative creative for highly visual, personalised ads in social feeds. One way to put it: Meta aims for a “hands-off” ad system by 2026 (vxtx.co.uk), whereas Google is progressively adding AI options but keeping advertisers in the loop. Additionally, Meta’s AI will span Facebook, Instagram, etc., and is very content-generation heavy, while Google’s is also about leveraging its search data and intent signals. In practice, we might see Google still expecting advertisers to set up campaign structures (albeit with AI assistance), whereas Meta wants to get to a point where you just trust the AI with your budget and goal.

Q12. How should marketers prepare for these AI changes in search and advertising?

A: Marketers should start by educating themselves and their teams about how these AI systems work. Begin experimenting with the available AI tools – for example, try out Google’s Performance Max campaigns or Meta’s Advantage+ automated campaigns on a small scale to learn how they perform. It’s wise to develop clear brand guidelines for AI (so when you use generative AI for ads, the outputs stay on-brand). You’ll also want to adjust your KPIs: for search, understand that impressions or visibility might come in new forms (like being listed as a source in an SGE answer even if you don’t get the click). For advertising, be prepared to shift metrics and testing methods as AI manages more – focus on overall outcomes like conversions or ROI, and less on micromanaging things like individual keyword bids. On the team front, encourage skill development in data analysis, prompt writing for AI, and strategy. Essentially, be proactive and adaptable: those who embrace and learn these AI-driven features early will have an advantage, while those who stick strictly to old methods might fall behind. The landscape is changing, but by staying agile and keeping the human creativity and strategic thinking in the loop, marketers can thrive alongside the new AI tools.

Bibliography

• Search Engine Journal – “Here’s What SEO Experts Have to Say About Leveraging SGE in 2024” – Search Engine Journal (Mar 27, 2024). Insights on Google’s Search Generative Experience and tips from SEO experts searchenginejournal.com searchenginejournal.com.
• Search Engine Land – “How to prepare for Google SGE: Actionable tips for SEO success” – Search Engine Land (Oct 11, 2023). Analysis of SGE’s potential impact on organic traffic (suggesting up to 30% decline) and recommendations for SEOssearchengineland.com searchengineland.com.
• Fox Agency – “Brighton SEO 2024: Actionable insights to take away” – Fox Agency Blog (May 2, 2024). Conference recap highlighting that SGE will not kill SEO (but will change it), with expert predictions on zero-click searches, e-commerce, and content quality fox.agency fox.agency.
• Search Engine Land – “How Google Search Generative Experience is impacting ads” – Search Engine Land (Feb 29, 2024). Reports findings from an SE Ranking study on how ad placements (top, bottom, shopping carousel) are affected by the presence of SGE in search results searchengineland.com searchengineland.com.
• Reuters – “Meta aims to fully automate advertising with AI by 2026, WSJ reports” – Reuters (June 2, 2025). News report outlining Meta’s plans for AI-driven ads, where brands could input a product image and budget and let AI generate and target the ads, including remarks from Mark Zuckerberg on building an AI one-stop shop for advertisers reuters.com reuters.com.
• VXTX Marketing Blog – “Meta’s AI Advertising Revolution: What Full Automation by 2026 Means for Marketers” – VXTX.co.uk Blog (June 6, 2025). An in-depth guide to Meta’s 2026 ad automation plans, describing tools like AI Sandbox, Meta Lattice, and Advantage+, plus advice for marketers to prepare vxtx.co.ukvxtx.co.uk.
• Wavemaker – “BrightonSEO 2024: Key Takeaways from our Organic Performance team” – Wavemaker UK Blog (April 2024). Notable point that the traditional “10 blue links” are disappearing as search engines become answer engines with the rise of SGE wavemakerglobal.com.
• VXTX Marketing Blog – FAQs excerpt from “Meta’s AI Advertising Revolution…” – VXTX.co.uk (June 2025). Q&A addressing common questions on Meta’s AI ads, including impact on small businesses and agencies, and emphasising that agencies must pivot to strategy and oversight vxtx.co.uk.