I recently explored the process of selecting an AI search optimization agency, and I wanted to share some insights for 2026. With the growing need for AI-driven solutions, it’s crucial to find an agency that aligns with your brand’s unique requirements.
Choosing the right agency can significantly enhance your brand’s AI visibility. To make an informed decision, I recommend focusing on key criteria and evaluation steps.
I’ve discovered that understanding the agency’s experience, evaluating their previous works, and considering their expertise in AI technologies are vital steps in this selection process.
I’ve noticed that the search landscape is evolving quickly, and it’s crucial for our companies to adapt. Are we appearing in Large Language Model (LLM) and AI-driven searches?
To thrive in this new era, understanding the Answer Engine Optimization (AEO) landscape is essential. Let me guide you on how to optimize your presence in AI search to stay ahead.
In December 2025, I led my research team through an in-depth analysis of the leading custom software development companies catering to medium and large enterprises in the U.S. Our study assessed 45 firms using carefully weighted criteria.
I’m excited to share some fantastic news for advertisers using Google Ads! They’ve introduced a new feature that lets us scale AI-generated ads quickly while keeping our brand’s voice consistent and under our creative control.
Google is granting us more influence over AI-generated ad copy, paving the way for us to expand our campaigns efficiently without compromising our brand consistency.
What’s happening: Google Ads is testing a beta feature where we can reuse text guidelines from existing campaigns. This means we don’t have to start from scratch each time, simplifying the process of maintaining brand rules.
How it works: With just one click, I can apply the approved tone, style, and messaging rules from one campaign to another, keeping AI-generated ads on-brand and cutting down on setup time.
Why we care: This feature is a game-changer, allowing me to launch campaigns faster while ensuring brand consistency across various accounts with multiple campaigns running at once.
Between the lines: It’s clear there’s an increasing demand among us marketers to “train” AI systems. This shift allows us to turn brand guidelines into reusable inputs, steering automation with more precision.
Bottom line: AI is accelerating the ad creation process, but what sets us apart is maintaining control, and Google is starting to return more of that control to us advertisers.
First spotted: This update first came to my attention through Paid Media expert Arpan Banerjee, who shared his find on LinkedIn.
I’ve been intrigued by how Google Search is set to transform. Sundar Pichai, the CEO of Alphabet, recently shared on the Cheeky Pint podcast that search is moving away from just providing information and answers. Instead, it’s evolving into a dynamic system that can complete tasks for us.
Why this matters to us: This shift marks Google’s transition from being a tool for information retrieval to becoming an assistant in task execution, which I’m sure will enhance our web interactions significantly.
Search’s agentic evolution: Sundar Pichai illustrates that our traditional way of searching is already seeing changes, and it’s only going to continue evolving.
He mentioned, “If I fast-forward, a lot of what are just information-seeking queries will be agentic in Search. You’ll be completing tasks. You’ll have many threads running.”
Pichai envisions a future where Google Search serves more as an agent manager, coordinating various actions for us. It’s like having multiple agents accomplishing different tasks, allowing us to get so much more done efficiently.
The CEO notes, “Search would be an agent manager in which you’re doing a lot of things. I think in some ways, I use Antigravity today, and you have a bunch of agents doing stuff. I can see search doing versions of those things, and you’re getting a bunch of stuff done.”
AI Mode’s impact: Pichai highlights that users are adapting their search behavior with Google’s AI functionalities. Even now, people perform deep research queries that redefine traditional search activities, implying that we’re already on a path to using search for more complex, long-running tasks.
He explains, “But today in AI Mode in Search, people do deep research queries. That doesn’t quite fit the definition of what you’re saying. But people adapted to that. I think people will do long-running tasks.”
Search and Gemini coexistence: Despite the introduction of Gemini, Sundar assures us that Google Search isn’t going anywhere. Instead, both will coexist and evolve together, balancing between some areas of overlap and profound divergence. This dual strategy aims to enhance how we utilize these technologies daily.
“We are doing both Search and Gemini. They will overlap in certain ways. They will profoundly diverge in certain ways. I think it’s good to have both and embrace it,” he shared.
I recently discovered that Google’s transition to AI-powered ads is transforming how brands engage with consumers, significantly boosting their performance in search results.
Google claims these AI-driven advertising tools are yielding impressive outcomes, with some retailers reporting substantial increases in sales as Google continues to innovate the functionality of ads within AI-driven searches.
The big picture. The anticipated disruption of Google’s search by AI chatbots like ChatGPT hasn’t happened. Instead, Google’s ad revenue continues to rise, illustrating that AI is enhancing search dynamics rather than replacing them.
By the numbers:
Alphabet Inc. exceeded $400 billion in revenue by 2025.
What’s happened. Google is integrating ads into its AI-powered search features, such as AI Mode using Gemini, while unveiling ad formats tailored for conversational searches. A new ‘business agent’ initiative helps brands like Poshmark and Reebok manage their AI representation.
Driving the results. Innovative campaigns, like Performance Max and AI Max, align ads with more nuanced conversational search intents. Google notes that AI Mode queries tend to be two to three times longer, providing better context and connecting users with fitting products. Aritzia, for example, has seen an 80% rise in revenue with AI Max.
How it works. The AI system assesses a retailer’s website and creative assets, interpreting user intent from conversational searches. It matches products and messages dynamically and in real time, crucial as 15% of daily searches are entirely novel.
Why we care. Google’s evolution from keyword-focused to intent-driven and AI-matched advertising enables more precise consumer engagement when they’re ready to purchase. As search becomes increasingly conversational, AI-powered ad formats are essential to stay competitive.
Zoom in. Google is exploring new formats like ‘direct offers’ which personalize promotions when users show buying intent. Using Gemini, these trials with brands like E.l.f. Beauty, Chewy, and L’Oréal analyze conversational context and behavior.
Commerce push. Google is advancing its commerce agenda with a Universal Commerce Protocol developed with Shopify, facilitating purchases directly within AI interactions.
Yes, but. Google isn’t alone in exploring AI-driven search ads. Early results vary; Amazon reports limited success with its AI shopping assistant, and OpenAI and Perplexity AI are navigating their monetization strategies.
What they’re saying. Google presents itself not as a retailer but as a ‘matchmaker,’ emphasizing how AI creates more relevant, personalized ads while allowing brands to control their message and foster user trust by displaying the right product at the perfect time.
What’s next. Though Google has no immediate plans to insert ads directly into Gemini, it will continue enhancing ad offerings within AI Mode, focusing on personalized promotions and AI-driven shopping experiences.
Bottom line. AI isn’t replacing traditional search; instead, it’s reshaping it. For Google, that means more conversational, targeted, and sometimes much more profitable advertising.
Dig deeper. Curious for more insights? Discover how Google’s AI ads are achieving an 80% sales boost for some brands here.
As someone who’s been closely observing AI advancements, I found Google’s AI Overviews to have improved significantly. By February, they correctly answered standard factual benchmarks 91% of the time, a notable rise from 85% back in October. This assessment came from a rigorous analysis conducted by The New York Times in collaboration with the AI startup, Oumi.
Yet, considering Google processes more than 5 trillion searches annually, this still implies that millions of answers could be incorrect every hour. In essence, there’s much room for improvement.
Why it matters to me. My interactions with Google have evolved from just link clicks to encountering AI-generated summaries. This evolution suggests that while AI Overviews have gotten better, they still mix accurate responses with poor sourcing and blatant errors, potentially misleading searchers and affecting visibility for many publishers.
The nitty-gritty details. Oumi put 4,326 Google searches to the test using SimpleQA, a benchmark known for measuring factual precision in AI systems. AI Overviews hit a 91% accuracy rate post-upgrade to Gemini 3 from Gemini 2’s 85%.
The more pressing issue for me is the sourcing. Oumi discovered that more than half of February’s correct responses were ‘ungrounded,’ meaning the linked references didn’t fully back the answers.
This lack of grounding makes verification a challenge. Even if the answer is correct, the linked pages might not sufficiently illustrate the reasoning.
What shifted. While the accuracy saw improvements from October to February, grounding declined. In October, 37% of accurate answers were ungrounded; by February, this figure increased to 56%.
Real-world examples. The Times pointed out several inaccuracies: For instance, Google incorrectly dated when Bob Marley’s home became a museum. Google’s answer was 1987, but the actual year was 1986, and the cited sources conflicted. A search about Yo-Yo Ma and the Classical Music Hall of Fame yielded a link to the Hall’s site, yet Google stated he wasn’t inducted. Moreover, while Google got Dick Drago’s age at death right, it flubbed his date of death.
Google’s standpoint: Google contested the Times’ findings, arguing that the benchmark used in the study was flawed and didn’t mirror actual search behavior. Google spokesperson Ned Adriance mentioned that the study had some ‘serious holes.’
Furthermore, Google asserted that its AI Overviews utilize search ranking and safety measures to minimize spam and has consistently cautioned that AI responses might contain errors.
I recently came across an intriguing Semrush study that revealed some fascinating insights into ChatGPT’s traffic patterns. Despite a whopping 206% increase in referrals, surprisingly few sites actually see significant traffic. This is largely because many queries are backed by pre-trained knowledge rather than live web searches.
According to the study, over 30% of outbound clicks go to just 10 domains. Google alone claims more than 20% of these clicks. It’s intriguing to see how much weight the tech giant holds in this landscape.
ChatGPT is gradually leaning less towards live web searches. It only triggers search functions in 34.5% of queries now, a decline from 46% in late 2024. This shift indicates a change in how the platform’s role is evolving in navigating the web.
Let me break it down further. Although ChatGPT’s referral traffic saw a significant rise, the traffic mainly flows towards a limited number of sites. In fact, about 21.6% of this traffic heads straight to Google, followed by nine other domains that make up a total of just over 30%.
Many other websites are left with a small fraction of residual traffic. The number of domains receiving any referrals peaked at around 260,000 in 2025 but has since settled near 170,000.
Why is this important for us? The visibility on ChatGPT doesn’t always translate directly into traffic. Often, the impact of referrals may seem marginal. Plus, the decline in search-triggered queries makes securing citations and traffic even more challenging.
While ChatGPT defaults to pre-trained knowledge, it resorts to web searches in certain scenarios, like when users request sources, inquire about current events, or when the model shows uncertainty.
I’ve noticed a shift in user behavior—most ChatGPT prompts don’t mirror typical search queries. Instead, between 65% and 85% reflect complex, conversational inputs, indicating a transformation in engagement. Interestingly, the number of queries per session jumped 50% in late 2025.
Looking into the data, Semrush analyzed over a billion lines of U.S. clickstream data between October 2024 and February 2026. This analysis tracked prompts, referral destinations, and patterns in search usage.
For those interested, more detailed insights can be found in the ChatGPT traffic analysis. The study, titled “ChatGPT traffic analysis: Insights from 17 months of clickstream data,” is an enlightening read.
I’ve recently discovered that Google has begun integrating sponsored ad units directly within the Images tab of mobile search results. This exciting new placement is accessible to eligible campaigns without requiring any changes to their existing keyword targeting.
What’s happening? Every time I check the Images tab on Google Search via mobile, I may now encounter sponsored units tucked within the image grid. Each ad displays a complete image creative as the primary visual element alongside text, and it is prominently labeled “Sponsored,” aligning with Google’s standard ad labeling throughout search results.
How it works. It amazes me how eligible campaigns can seamlessly serve into the Images tab without altering any keyword targeting or campaign structure. This placement leverages existing image assets, positioning advertisers who run Search or Performance Max campaigns with compelling visual creatives to gain the most. Thankfully, there’s no need to set up separate image-only campaigns.
Why it matters to us. This move significantly expands Google’s paid search real estate. For those of us engaged in product-led or catalog-heavy advertising, the Images tab is crucial, as it often serves as the starting point for purchase-intent discoveries — and now, our ads can appear right in that moment. If we are using robust image assets in our campaigns, we might be enjoying incremental impressions without any effort on our part.
The big picture. I’m noticing that this placement behaves more like a visual discovery surface rather than traditional paid search. While we should expect high impression volumes, the click-through rates might be lower, similar to display or Shopping ads instead of conventional text ads. Yet, the assist value in multi-touch conversion paths could be quite significant, especially for retail and direct-to-consumer brands. It’s an upper-funnel reach strategy, not a last-click channel.
What we should watch. Even though Google hasn’t officially announced it, nor is there a specific reporting breakdown for these Image tab placements yet, it’s crucial for us to monitor our impression share and segment data closely. This will help us understand its contribution, and whether it impacts organic image visibility for our competitors.
First seen. The innovative placement was first noticed by Google Ads Expert Matteo Braghetta, who shared this update on LinkedIn. At the time of writing, Google hasn’t published any official documentation regarding this development.
