Taboola’s New AI Search Engine “DeeperDive”: What It Is and Why It Matters

Taboola, a company best known for those “Around the Web” content recommendations at the bottom of news articles, is making headlines of its own. In June 2025, Taboola launched a generative AI-powered search engine called DeeperDive for its partner publishers. This marks a significant shift for Taboola from its traditional role in content discovery to a bold new venture in AI-driven search.

What exactly is Taboola’s DeeperDive, how does it work, and why are publishers like USA Today’s owner Gannett and The Independent on board? In this article, we’ll break down everything you need to know in an easy-to-understand way. We’ll explore how Taboola built its business, how DeeperDive compares to Google or ChatGPT, what makes it unique, and what it could mean for users, advertisers, and publishers.

We’ll also touch on the business strategy behind it, potential benefits and risks, ethical considerations, and how the tech world is reacting. By the end, you’ll have a clear picture of this new AI search tool and why Taboola believes it can “change how billions of people discover and decide online”.

What Is Taboola? From Content You May Like to Content You Search For

To understand DeeperDive, it helps to know a bit about Taboola’s background. Taboola is one of the world’s largest native advertising and content recommendation platforms, working with over 9,000 digital publishers around the globe per axios.com. If you’ve ever read an article online and seen a section titled “You may also like” or “Recommended for you” with a mix of news stories and sponsored content, chances are Taboola was behind it.

Taboola’s platform matches content from advertisers or other publishers with readers who might be interested, placing those links on big websites like news portals and blogs.

Taboola’s traditional business model is all about content discovery and native ads. Advertisers and content creators pay Taboola to get traffic – essentially to have their articles or videos recommended on popular websites – and Taboola shares some of that revenue with the host websites (the publishers). It’s a bit like an internet matchmaking service: Taboola connects people who want their content seen (marketers, brands, even other news sites) with publishers who have an audience and space to showcase links.

Those little content recommendation boxes are powered by Taboola’s algorithms, which use browsing data and other signals to suggest stories or ads a reader might click. This model is called native advertising because the sponsored links often mimic the look and feel of standard news or article suggestions. The goal is to engage readers without using flashy banner ads, by presenting ads as if they were just more articles to read (see: Investopedia).

Over the past decade, Taboola became a familiar presence on the “open web” (essentially, the world outside walled gardens like Facebook). The company was founded in 2007 by Adam Singolda and grew rapidly by partnering with major publishers. It even struck a 30-year deal with Yahoo in 2022, where Yahoo took a 25% stake in Taboola and made Taboola the exclusive native ads provider across Yahoo’s sites.

Taboola’s main rival in this space is Outbrain – the two companies often appear side by side in discussions of content recommendation tech. (Fun fact: Taboola and Outbrain once planned to merge, although that deal fell through, leaving them to compete separately.) Together, these companies’ widgets have been touted as alternatives to Google AdSense for publishers looking to monetize via content recommendations.

However, Taboola’s “you may also like” model has faced challenges. Some critics say the recommended content can be low-quality or clickbait, and not everyone loves the idea of clicking links that whisk them away to other sites. Publishers walked a fine line: they earned money from Taboola’s sponsored links, but risked sending readers off their site to potentially dubious content, see: investopedia.com.

In recent years, Taboola has been looking to innovate and improve the user experience. The company has been expanding into what it calls performance advertising, trying to deliver ads that lead to measurable actions like purchases or sign-ups (not just clicks). This is where generative AI comes into play for Taboola’s next act. Enter DeeperDive.

Introducing DeeperDive: Taboola’s Generative AI Search Engine

DeeperDive is Taboola’s new generative AI-powered search engine designed specifically for publisher websites. In simple terms, it’s like putting a mini-ChatGPT or intelligent search box right on a news site, but with the twist that it draws answers from that site’s own content (and potentially from Taboola’s network of content) rather than the entire web.

The tool lives as a widget on the publisher’s webpage – for example, on USA Today’s website, which is one of the first to implement DeeperDive in the U.S. Instead of the usual search function that might just match keywords and return a list of results, DeeperDive uses generative AI to answer reader questions in a conversational way, much like an AI chatbot would.

So, how does it work under the hood? According to Taboola, readers can ask questions about topics they’re interested in and get instant answers from the AI, sourced from the publisher’s own trustworthy content. For instance, if you’re on USA Today’s site reading about travel and you type, “What are some fun family activities in Los Angeles?”, DeeperDive might generate a quick answer summarizing the top attractions or tips, using information from USA Today’s travel articles and guides.

It won’t just give a one-liner answer; it’s designed to provide extra context and link to relevant articles on that site for a deeper read. In other words, it’s generative (it creates a custom answer for you on the fly), but it’s also a search engine for the site’s content, guiding you to pieces the publisher has already written that relate to your question.

Crucially, DeeperDive isn’t trying to index the whole open web like Google. It is more narrowly focused. Adam Singolda (Taboola’s CEO) explained that DeeperDive pulls its answers from Taboola’s network of publisher content and specifically from the site where the user is searching. Because Taboola has longstanding relationships and data from thousands of publishers, Singolda believes this gives their AI an edge in answering accurately with up-to-date info on what people are reading about.

In effect, Taboola has a real-time pulse of trending topics across different sites – they call it the “pulse of the internet” – which they can tap into for DeeperDive per globenewswire.com. Unlike AI systems that rely on static training data that might be months or years old, Taboola’s system is aware of what’s hot right now across its network, and can use that insight to deliver timely answers and even suggest follow-up questions related to current trends. This dynamic aspect is something Taboola emphasizes as a differentiator.

Let’s visualize the user experience: You’re on a participating news site and see a special search box or chat widget (perhaps labeled with something like “Q&A” or the DeeperDive name). You type a question in natural language. The AI quickly responds with a few paragraphs of answer, summarizing information from relevant articles on that site. Alongside the answer, you might see links or references to the articles where that info came from – for example, a link to a USA Today article on “Top 10 L.A. Family Activities” or a local story from the USA Today Network that delves deeper into a point.

Essentially, it’s giving you a quick, conversational answer and a roadmap to read more if you want. You might also notice that the tool sometimes prompts you with related questions or topics (“Still curious about California beaches?”), encouraging you to continue exploring the site’s content.This is why it’s called “Deeper Dive” – the idea is to dive deeper into the content without leaving the site.

Taboola debuted DeeperDive in mid-2025 with two major publishers as “design partners”: Gannett (which owns USA Today and hundreds of local newspapers) in the U.S., and The Independent in the U.K. Gannett’s CEO Mike Reed expressed excitement, seeing it as an innovative way to help readers explore their trusted content and keep them engaged. They started cautiously – at first, only about 1% of USA Today’s visitors (around 30,000 users a day) got to test the DeeperDive widget as a beta trial.

The plan is to roll it out more broadly if things go well, eventually expanding to all of Gannett’s 220 local news websites across America per: axios.com. In the UK, The Independent is similarly piloting DeeperDive on its site. These partnerships suggest that big publishers see potential in the tool to increase engagement – in other words, to get readers to stick around longer and read more articles.

How Is It Different from Google, Bing, or ChatGPT?

At first blush, DeeperDive might sound similar to what Google or Bing are doing with AI, or even like using ChatGPT. But there are some key differences in scope, purpose, and experience. Let’s break down a comparison:

1. Scope of Information:

• Google and Bing (with AI integrations) – Traditional search engines like Google index the entire web. When you search, they show you a list of links (and lately, both are dabbling in AI summaries at the top of results). Google’s new Search Generative Experience (SGE), for example, uses AI to generate an answer from the web and displays it above the usual links, while Microsoft’s Bing has integrated GPT-4 to have a chat mode that can answer questions with information from web searches. These AI answers pull from any site on the internet and often cite a few sources.
  
• ChatGPT (OpenAI) – ChatGPT is an AI chatbot that was trained on a vast dataset (covering a lot of the internet up to a certain point) and can generate answers in a conversational way. However, out-of-the-box it doesn’t browse live websites for each query (unless specifically augmented with plugins or browsing). It’s not a search engine per se; it’s more of an all-purpose question-answering assistant.
  
  ChatGPT might give you a fluent answer on almost anything, but it won’t automatically provide citations or direct you to the source of its information, and it might not know about very recent events if they happened after its training cut-off.
  
• Taboola’s DeeperDive – This engine is narrower in scope than Google/Bing. It doesn’t comb the whole internet; instead it focuses on content from the publisher’s own site (and possibly that publisher’s network or Taboola’s network of partners). That means if you’re on USA Today, DeeperDive will draw from USA Today Network’s articles; if you’re on The Independent, it will use The Independent’s content, and so forth.
  
  The upside is that answers come from a curated, trusted set of sources (the site you’re already on, which likely has editorial standards). The downside is it won’t bring in outside perspectives beyond that ecosystem – unlike Google which might show you multiple news sites or blogs on a topic. Essentially, DeeperDive is site-specific (or publisher-network-specific) AI search, not a web-wide search.

2. User Experience:

• Google/Bing: You type a query, and you usually get a list of blue links to websites, maybe with some snippets. With their new AI features, you might see a summary at the top. For example, Bing’s AI chat can have a conversation refining your query, and Google’s SGE might show a paragraph of info with cited sources. But these still ultimately encourage clicking out to various websites if you want detail.
  
• ChatGPT: The experience is a pure Q&A chat. You ask, it answers in a dialog format. If you ask a follow-up, it remembers the context. It’s like texting with a super knowledgeable (though sometimes hallucinating) friend. It doesn’t directly show you where it got its info (again, unless you prompt it or use a version that cites).
  
• DeeperDive: The user experience is intended to be conversational and integrated directly into your reading flow on a publisher’s site. You might be reading a news story and see a little prompt like “Have a question? Ask our AI.” It’s more proactive on the site itself. DeeperDive will answer in a conversational tone, somewhat like ChatGPT, but it will also provide links to read more on that site. Think of it as a hybrid between a search function and a chatbot: it not only tells you an answer, but also immediately suggests “here are related articles where you can verify or learn more.”
  
  It’s designed to keep you engaged with that publisher’s content, rather than sending you offsite.

Another difference is context and depth. Taboola claims DeeperDive “goes a step further” than other AI engines by surfacing additional context and stories from the same site, rather than just a single oversimplified answer. So, if a user asks a question, DeeperDive might say, “Here’s the quick answer… and by the way, USA Today has an in-depth article on this – click here to read more.”

Google’s AI might not know what site you trust or came from, it just gives generic info. DeeperDive leverages the fact you’re on a specific trusted site and tries to give you a richer answer within that universe.

3. Monetization and Purpose:

• Google earns money largely through search advertising – those sponsored results you see at the top of queries. Bing does similarly (and Bing’s integration of AI also started showing ads within the chat answers). ChatGPT doesn’t show ads in answers (OpenAI’s model is monetized by subscriptions and API usage for now, not ads to end-users).
  
• Taboola’s DeeperDive is explicitly built with monetization for publishers in mind per axios.com. We’ll cover the business model in detail later, but the gist is: by keeping users on the site, engaged and asking questions, DeeperDive can present contextual ads right alongside the answers – akin to how Google might show an ad next to search results. These could be highly “intent-driven” queries (meaning the user is actively looking for something, e.g. “best credit card for travel rewards?” – which is gold for advertisers).
  
  Taboola sees this as a way to create search-like ad revenue on publisher sites. That’s a key difference; Google wants to keep you on Google to show you ads, whereas Taboola wants to keep you on the publisher’s site and show ads there. It’s a bit like each publisher having their own mini-Google that answers questions and can show a few sponsored results or product recommendations tailored to the query, with revenue going to the publisher (and Taboola taking a cut) instead of all going to Google.
  
  Adam Singolda framed this as capturing the value of “high-intent moments” – turning a simple click worth a few cents into a potential customer action worth many dollars, right on the publisher’s site.

4. Transparency and Sources:

• Bing’s AI chat notably cites its sources with footnotes (you can usually click to see the webpages it pulled info from). Google’s SGE also lists some source links for the facts it presents. ChatGPT (freeform) does not cite unless asked. This transparency is important for trust.
  
• DeeperDive by design will highlight source articles from its publisher. It’s likely to show which USA Today article or Independent story it drew the answer from, because one of its purposes is to direct you into those articles. In that sense, it has built-in transparency – it’s essentially always citing the publisher’s own content as the source of truth.
  
  This not only builds trust with users (they can click and read the full story from which the answer was drawn), but it also addresses a major complaint about AI answers: that they often scrape content without crediting the source or driving traffic back. DeeperDive is meant to do the opposite – it cites and sends you to the source on the same site. In the next sections on ethics, we’ll see how Taboola pitches this as a more publisher-friendly approach than the typical AI search engine.

To summarize the comparison, here’s a quick table contrasting these points:

Feature	Google/Bing AI Search	OpenAI’s ChatGPT	Taboola’s DeeperDive
Scope of data	Almost entire web (billions of pages)	Vast training data (internet up to 2021-2022, etc.)	Specific publisher content (site or network)axios.com
Answer style	Short snippets or AI summary + links	Conversational paragraph answers (no default sources)	Conversational answers + links to publisher’s articlesaxios.com
User interaction	Type query → results (some AI Q&A in beta)	Chat with AI (memory of context)	Q&A on site, possibly chat-like (context is the site content)
Sources shown?	Yes (citations/links in AI answers)	Not unless prompted	Yes, links to site’s own sources (encourages clicking through)axios.com
Monetization	Search ads (Google Ads, Bing Ads)	Subscription (ChatGPT Plus)	On-site ads in answers (shared with publisher)globenewswire.com
Primary purpose	Get user the info (and keep them using engine)	Provide direct info/help	Answer questions to keep user on publisher site longerglobenewswire.com

As we can see, while all these tools aim to answer your questions, DeeperDive is unique in being publisher-centric. It’s not trying to replace Google for broad web searches; rather, it supplements your experience on a given site by offering an AI assistant that knows that site’s content inside-out. Next, let’s look at what special features DeeperDive brings and how it feels for a user to interact with it.

Unique Features and User Experience of DeeperDive

DeeperDive is more than just a search bar – Taboola is positioning it as a “Gen AI answer engine” that delivers a richer, more human-like search experience on news and content sites. Here are some of the notable features that make it stand out:

• Conversational Q&A Interface: Instead of typing keywords like in a normal site search (e.g., “climate change 2023 article”), readers can ask natural questions (“What are the latest climate change updates this year?”) and get a direct answer. The tone of the response is friendly and explanatory, similar to asking an expert or using an AI chatbot. This lowers the barrier for users who might not be great at coming up with the right keywords – they can just ask in plain language.
  
• Sources from Trusted Content: Every answer DeeperDive gives is drawn from content by professional journalists and editors that the publisher has produced. The system leverages years of high-quality content on the site, meaning it isn’t fabricating answers from thin air – it’s synthesizing what’s already been reported or written. This is important on sensitive topics: if you ask a health question on a respected news site’s DeeperDive, the answer should be based on that site’s vetted health reporting, not a random forum or an AI’s imagination.
  
  Taboola explicitly highlights that answers are “sourced from trusted journalists such as the best travel desk or top sports reporters”, depending on the topic see: globenewswire.com. For users, that means an added layer of trust – you’re essentially getting the editorial voice of the site distilled via AI.
  
• Beyond a One-Line Answer – Contextual Depth: One criticism of some AI search answers is that they can be too brief or oversimplified, leaving out nuances. DeeperDive tries to counter that by providing additional context and multiple angles. When it answers a question, it doesn’t stop at the first sentence – it often includes a couple of paragraphs covering different facets of the question, much like a mini-article. Even more, it surfaces related stories and content from the site to give depth, see: globenewswire.com.
  
  For example, if you ask “How is the real estate market doing in 2025?” on a financial news site, DeeperDive might summarize the trend (rising or falling prices, etc.) and then point you to a recent analysis piece or a data graphic that the site published. This approach acknowledges that a single AI answer might not tell the whole story, so it invites you to “dive deeper” via full articles if you wish.
  
• Real-Time Insights and Trending Topics: Thanks to Taboola’s wide view of online reading habits (remember, they see data from 600 million daily users across thousands of sites), DeeperDive can tap into what’s trending in real time. This means the suggestions or the nuance in answers might reflect very current information. If a certain topic is blowing up today, the AI is more likely to know about related content on the site and might even proactively suggest that topic. For instance, if a big sports upset happened an hour ago and you’re on a sports site, the DeeperDive interface might prompt, “Questions about the championship game tonight?
  
  Ask here!” – essentially using trends to guess what readers might want to know. This “pulse of the internet” capability is something Taboola touts as an advantage over AI models that are fixed on older data.
  
• Integrated Ads as Part of Experience: From a user perspective, this could be seen as a feature or just a reality of the tool: relevant ads might appear within the answer results. For example, if you ask a question about travel or consumer products, you might see a sponsored suggestion. Imagine asking “What’s the best laptop for graphic design?” – DeeperDive might provide a summary of advice from the site’s tech writers and include a link to a review (as context), along with a clearly labeled sponsored result like “Sponsored: Check out XYZ Laptops – on sale now”.
  
  Ideally, these ads will be highly relevant and non-intrusive, designed to feel like helpful recommendations rather than flashy banners. The idea is to maintain a “seamless reader experience” while still creating a new ad opportunity. We’ll discuss later how these are monetized, but from a pure UX standpoint, Taboola will have to balance making the answers useful and not overly ad-heavy, so users don’t feel spammed.
  
• Prompting Further Exploration: The name DeeperDive is apt because the tool actively encourages you to keep exploring. It might end an answer with a question back to you or a suggestion like, “Do you want to learn more about [related topic]?” This makes the experience a bit interactive. It’s not just Q&A and done – it tries to engage you in a little dialogue or at least in a journey through more content. In that sense, it’s leveraging some of the engagement tactics from chatbots (which invite you to continue the conversation).
  
• Publisher Branding and Control: While not a user-facing “feature” per se, it’s worth noting that DeeperDive will live within each publisher’s site and likely carry the look-and-feel (branding) of that site. You might see it labeled as “Ask USA Today” or something along those lines, powered by Taboola’s tech under the hood. The publishers have an interest in making it feel like an integrated part of their website rather than a third-party widget.
  
  Also, publishers will likely have control over some aspects – for example, perhaps they can tune which sections of their content the AI draws from (maybe they want it to use only news and feature articles, not opinion columns, depending on the question).
  
  The success of the user experience will partly depend on how well Taboola and each site train and fine-tune the AI to reflect the site’s editorial standards. A sports site might configure DeeperDive differently than a medical info site, to ensure the tone and reliability meet reader expectations.

In summary, the user experience Taboola is aiming for with DeeperDive is interactive, informative, and site-specific. It’s like having a knowledgeable guide on the website who can answer your questions and point you to the right in-house articles for more detail. If executed well, it could make reading news online feel more like a conversation rather than a one-way street. However, integrating such an AI also raises questions about how it will change user behavior and how the business side works – which we’ll get into next.

The Business Strategy: Monetization and Motivation Behind DeeperDive

Why is Taboola investing in an AI search engine for publishers? The short answer: money and survival. Let’s unpack that in a friendly way.

A New Revenue Stream – Search Ads for Publishers

Digital advertising is a tough game these days, especially for publishers. Google and Facebook (now Meta) have long dominated online ad revenues. In particular, Google Search advertising is a goldmine – when users search for things like “buy car insurance” or “best hotel in Paris”, advertisers pay big bucks to show up in those results. Publishers, on the other hand, mostly earn from display ads or sponsored content on their pages, which often yield less money per eyeball.

Taboola’s idea with DeeperDive is to bring some of that lucrative “search advertising” money to publishers’ own websites.

Here’s how that works: If readers start using DeeperDive on a news site to ask questions, those queries can reveal intent – what the user is interested in or looking for. Some of those interests have commercial value. For example, a user on a tech news site might ask “What’s the best smartphone under $500 right now?” That question signals that the person might be in the market to buy a smartphone.

In the world of advertising, that’s a high-intent query – an advertiser (like a phone manufacturer or an e-commerce store) would love to get a relevant ad or product suggestion in front of that user at that moment. Traditionally, the user might have gone to Google with that query and Google would show ads and make money.

With DeeperDive, the publisher can capture that query on their own site and display a relevant sponsored result, keeping the user (and their clicks) in-house. Taboola facilitates this by inserting those contextual, high-intent ads directly into the AI answer page.

Adam Singolda gave a striking comparison: It’s the shift from 50 cents per click to $500 per conversion, right on the publisher’s site. What does that mean? It’s an illustration of value. In the old model, a click on a Taboola recommended story might earn pennies. But if through DeeperDive a user actually finds a product or makes a decision like booking a trip or signing up for a financial service (a conversion), that could be worth hundreds of dollars.

Taboola envisions scenarios like AI-powered “travel agents” or “shopping advisors” on publisher sites in the future – where, say, a travel magazine’s AI could answer “What’s the cheapest flight to Hawaii next month?” and actually help you book it. Owning those “high-intent moments” could unlock affiliate commissions or big ad bounties that are far beyond the typical banner ad revenue.

While DeeperDive’s initial form is Q&A with links and maybe simple ads, the long-term hint is that Taboola wants to enable AI agents in categories like travel, finance, sports, and commerce that do more and directly drive revenue (for example, helping you buy tickets, find a credit card, or shop for sports gear).

This aligns with trends in e-commerce and AI: everyone is racing to have AI not just inform you, but also assist you in transactions. Taboola sees that as a natural extension for publishers with trusted content — to move from informing the user to helping the user take action, and then taking a cut of that action.

Fighting Back Against Traffic Loss

There’s also a defensive motivation here. Publishers have been worried about generative AI search engines like the new Bing and others because those can scrape content, answer users’ questions, and potentially reduce clicks to publishers’ sites. If people get answers directly on Google or Bing’s AI, they might not visit the news article at all. This means publishers lose traffic and the ad views that come with it.

Some publishers have even complained that AI bots are using their content without permission or compensation, calling it a form of “exploitation”. Taboola’s business depends on publishers thriving (if publishers suffer, there’s less content and less audience for Taboola to monetize). So, part of the strategy with DeeperDive is to give publishers a way to “fight back” or stay competitive.

By having their own AI answer tool, a publisher can keep readers engaged on their site rather than sending them off to a general search engine that might never return the favor. As Taboola puts it, DeeperDive offers publishers “a way to compete, not be replaced” by the new wave of AI search, see: globenewswire.com.

It’s also about unity against a common threat. Singolda has been vocal that the open web needs fairer treatment – that it’s “not sustainable for Gen AI engines to rely on publisher content while sending little traffic and compensating only a select few”. In one of his quotes, he said “that’s not innovation, it’s exploitation” regarding the current model of AI scraping.

With DeeperDive, Taboola aims to demonstrate an alternative model where the AI lives within the publisher ecosystem and shares value back (through increased engagement and ad revenue) rather than siphoning it away. This message is likely meant to rally publishers around Taboola’s solution and perhaps put some pressure on the big AI players to come to the table with compensation or partnerships.

Leveraging Existing Relationships and Data

Another strategic advantage Taboola has is those existing 9,000 publisher partnerships and the massive dataset of reader behavior. DeeperDive is not starting from scratch to learn what people care about – Taboola’s system already “knows what’s trending on the internet” from its content network and user interactions. Singolda noted this is the core business of the company: knowing which stories are getting traction, which topics are resonating, etc.

By integrating that into the AI, Taboola can fine-tune DeeperDive to be relevant and timely. For example, if Taboola’s network data shows that interest in “electric vehicles tax credit 2025” is spiking today, DeeperDive on a financial news site might be extra prepared to answer questions about that, or even suggest asking about EV tax credits. This gives Taboola a leg up compared to a startup that doesn’t have that real-time insight.

From a business perspective, it also means Taboola can upsell this AI service to a huge base of publishers it already works with. Many of those publishers already trust Taboola for recommendation widgets; adding an AI search tool is a logical next step in the partnership. It’s a new product in Taboola’s portfolio – likely one that can be monetized via a revenue-share (Taboola might say: we’ll power the AI for free, and we split any ad/affiliate revenue it generates) or even a fee for premium placement.

It strengthens Taboola’s position as not just an ad provider but a technology partner for publishers in the AI era.

Tying into Taboola’s Broader Vision

In recent investor presentations, Taboola has talked about moving beyond native ads and into performance advertising at large.. They even launched a platform called “Realize” to serve more advertising needs. DeeperDive fits into this narrative by addressing the lucrative search ad market (which is performance-driven) and by possibly enabling things like affiliate marketing (e.g., recommending products with kickbacks) and even subscription conversions (e.g., suggesting you subscribe for more content if you ask a lot of questions).

In the Gannett press release, Gannett’s CEO mentioned that Taboola has helped with everything from high-intent CPM advertising to enhanced affiliate and subscription growth. That indicates DeeperDive isn’t just about showing an extra banner ad; it could help identify users who are super engaged (asking lots of questions) and maybe upsell them a subscription, or provide affiliate links that convert well.

The business strategy can be summed up as: increase user engagement + capture search intent on site + monetize that intent = new revenue. And in doing so, fortify the relationship between Taboola and publishers by tackling the AI disruption together.

Of course, for this strategy to pay off, users have to actually use DeeperDive and find it valuable (so they keep coming back and asking more questions). Publishers have to see a net gain (more time on site, more revenue) without too much headache or risk. And advertisers need to see performance from any new ad formats in these AI answers. It’s early days, but Taboola clearly has big ambitions, calling the launch “a big day not just for Taboola, but for the entire industry”.

Now that we understand the “why” from a business angle, let’s discuss how all this impacts the key stakeholders – the users who consume content, the publishers who create it, and the advertisers who fund much of the web’s free content.

Potential Benefits and Risks for Users, Publishers, and Advertisers

Any new technology comes with its upsides and downsides. DeeperDive is no exception. Let’s break down what users, publishers, and advertisers stand to gain or worry about with Taboola’s AI search engine.

For Users (Readers):

Benefits:

• Quick Answers, Less Searching Elsewhere: As a reader, you get your questions answered right on the site without having to open a new tab and Google things. This convenience can be great – especially if you’re already on a trusted site and just want a quick explainer or update. It’s like having a knowledgeable assistant at your fingertips while you read.
  
• Trusted Source of Information: Because the answers come from the site’s own content, you can have more confidence in the info. For example, if you’re on a reputable health news site and ask about symptoms of an illness, the answer is drawn from that site’s expert articles, not random internet chatter. This potentially means more reliable and accurate information, assuming the site itself is reputable.
  
• Richer Learning Experience: You don’t just get an answer – you also get suggestions for further reading. So if you’re curious and have time, DeeperDive can lead you down a path of learning more about the topic from various articles. It’s a bit like a guided tour through the site’s archives, tailored to your question.
• Conversational and Easy: Not everyone is good at formulating search queries.
  
  Some people might not even use a site’s search function because they’re not sure what terms to type. Asking a question in plain English (or whatever language) is much more natural. This lowers the barrier for engagement. It also can make interacting with news more fun or engaging – almost like chatting with the site.
  
• Up-to-date responses: Since Taboola’s AI considers what’s trending and the latest content, the answers should include the latest information available on that site. If the site just published something an hour ago on a breaking story, DeeperDive could incorporate that info, giving you timely answers.

Risks/Concerns:

• Accuracy and Hallucinations: Generative AI, even when fed good sources, can sometimes produce incorrect or “hallucinated” answers (saying something confidently that isn’t true). There’s a risk that DeeperDive might mis-summarize an article or combine information in a wrong way. If users take the AI answer at face value without clicking through to verify, they could be misled. Ensuring the AI “consistently delivers accurate and unbiased information” will be a challenge.
  
• Limited Perspective: Since the answers are site-specific, you’re getting only the perspective or coverage that the one site provides. Sometimes that might not be comprehensive. For instance, if you ask a politically charged question on one outlet’s site, you might get an answer reflecting that outlet’s editorial stance. On a broad search engine like Google, you’d see multiple sources with different viewpoints. So there’s a possibility of bias or tunnel vision, depending on where you’re asking.
  
• Privacy and Data Use: When you ask questions on DeeperDive, those queries are likely being logged by Taboola and the publisher. That’s valuable data (for improving the AI and for ad targeting). Some users might be uncomfortable not knowing how their question data is used. If you ask a personal question (“What’s a good remedy for insomnia?” on a health site), that could reveal something about you. There’s an implicit trust that Taboola/publishers will handle that data responsibly and anonymize it, but it’s something to be aware of.
  
• Blurring of Ads and Answers: With ads potentially embedded in answer results, users will need to be able to tell what’s editorial content and what’s sponsored. If Taboola and publishers don’t label these clearly, it could be confusing. The last thing a user wants is to think an AI’s unbiased recommendation is telling them to buy Product X, when in fact that’s a paid placement. Ethical guidelines and clear “Sponsored” tags need to be present so the experience remains trustworthy.
  
• Dependence on One Site’s Info: If a user gets very used to using DeeperDive on one site for all answers, they might miss out on the broader context or miss better info elsewhere. It’s always good to remember this is a guided experience within a bubble. For casual queries this is fine, but for important research one should still cross-check with multiple sources.

For Publishers (Website Owners/Media):

Benefits:

• Increased Engagement (Time on Site): This is perhaps the biggest draw. If readers start asking questions and getting hooked on a chain of content, they will spend more time on the site and view more pages. Publishers love this – it’s good for ad impressions and for building loyalty. Gannett’s CEO anticipated “deeper engagement” and even reaching a broader audience through this tool. Early tests on USA Today will likely measure if users who have the AI widget spend significantly more time than those who don’t.
  
• New Ad Revenue (Search Ads on Site): We discussed how DeeperDive opens the door to search-like advertising revenue that publishers never had access to on their own sites. This could be a game changer for publisher monetization. Instead of relying only on standard banner ads or sponsored content deals, they could directly earn from high-intent queries. For example, a finance news site could show a credit card ad when someone asks about “best credit cards”, and if that yields a sign-up, the publisher gets a cut. It’s a whole new channel for income.
  
• Retention and Loyalty: If users find the AI helpful, they might stick to that site for similar queries instead of bouncing to a general search engine. That means repeat visits. If USA Today’s AI answers all your sports trivia questions well, you might habitually go to USA Today for sports queries. This can strengthen the publisher’s brand as a destination for knowledge, not just news. It reinforces their authority and relationship with the audience.
  
• Staying Competitive and Relevant: By adopting AI, publishers can show they’re innovating. It might attract a younger or more tech-savvy audience. Also, it’s partly a defensive move to mitigate the risk of losing traffic to AI answers elsewhere. Publishers who integrate something like DeeperDive early could have an edge over those that don’t, especially if the practice of on-site AI search becomes common. It’s also a signal to advertisers and investors that the publisher is forward-thinking.
  
• Insight into Reader Interests: The questions users ask can be incredibly valuable data for publishers. It’s like doing continuous focus-group research. If many people ask “What’s the latest on climate change in my city?” that might signal the publisher should create more local climate content. DeeperDive could provide analytics on trending questions, which in turn can inform editorial decisions – a nice feedback loop.

Risks/Challenges:

• Accuracy and Editorial Control: If the AI gives wrong or problematic answers, the publisher’s reputation is on the line. Users will associate the answer with the site (even if it’s the AI speaking). A news site that values accuracy might worry about the AI misrepresenting facts or not having the full context. Ensuring the AI’s output meets editorial standards likely requires oversight. Publishers might need editors or moderators to periodically review AI answers, especially on critical topics like health or finance. This is extra work and responsibility.
  
• Upkeep and Training: The AI might need training on each publisher’s content style. There could be initial heavy lifting to integrate it properly – for instance, making sure it has access to all the right content databases, filters out irrelevant sections (like maybe not drawing from opinion pieces if the question is for factual info, unless clearly indicated). Technical issues could arise, which means a dependence on Taboola’s tech support. If something goes wrong (AI goes down, or answers get weird due to a bug), the publisher has to scramble alongside Taboola to fix it.
  
• Impact on Traditional Usage: There’s a small risk that if the AI answers too well, users might not click through to read full articles as much as before. This is a bit ironic, because the whole point is to boost engagement, but it’s worth considering. For example, if DeeperDive gives a thorough answer summarizing a 1000-word article in 3 sentences and the user feels satisfied, they might not bother to click the article. That could cut pageviews. The hope is that the AI will tease enough that interested users will click. It’s a fine balance between giving a satisfying answer and not giving away the whole story.
  
• Monetization Uncertainty: While search ads on site sound great, it’s an unproven model at scale for these publishers. They’ll have to attract advertisers or route existing demand into this channel. It may take time to see significant revenue. If user uptake is slow, the ROI (return on investment) might be low initially. Publishers will need to be patient and also work with Taboola to pitch this to advertisers.
  
• Ethical and Legal Considerations: Publishers will have to consider things like: do they need to disclose that an answer is AI-generated? How to handle corrections if the AI says something wrong? Also, could there be any copyright issues if, say, the AI pulls a quote from an article – is that allowed under their own usage terms? (Probably yes, since it’s their content, but things get complicated if multiple sources are used, e.g. wires or licensed content).

For Advertisers (Brands and Marketers):

Benefits:

• New Ad Inventory in High-Intent Contexts: Advertisers always seek to get their message in front of people exactly when they’re interested in it. DeeperDive potentially creates those moments on publisher sites. For instance, a travel agency can now reach users who ask travel questions on a travel magazine site, which is a very contextually relevant and intent-rich opportunity. This is different from a random banner on a homepage – it’s tied to what the user is actively seeking.
  
• Trust Halo from Publishers: If an ad or sponsored suggestion appears within a respected publisher’s environment, it might get a trust boost. The user is in a mindset of trusting the content (compared to, say, seeing an ad on a random social feed). So an advertiser might find better engagement rates. Essentially, it’s a form of native advertising 2.0 – integrated into the Q&A flow.
  
• Performance Tracking: Since this is digital, advertisers will get data on how these AI-assisted placements perform. They could see metrics like click-through rates on suggestions from AI answers, conversions from those, etc. If it works well, it’s a new channel to allocate budget to (maybe shifting some from search engine ads to publisher AI search ads).
  
• Supporting Publishers (PR angle): On a softer note, advertisers that value journalism and the open web might like the narrative that by advertising via DeeperDive they are helping fund publishers directly, rather than contributing to Google’s dominance. There’s been chatter in the industry about supporting alternatives to the big tech ad duopoly. This could fit that ethos: “We advertise on XYZ News’s AI answers to support quality journalism and reach informed readers.”

Risks/Challenges:

• Volume and Scale: Initially, the volume of queries going through DeeperDive is going to be much smaller than Google’s search volume. Advertisers might find it too niche or low-scale to bother with at first. They might adopt a “wait and see” approach until lots of publishers have it and users are widely using it.
  
• Effectiveness Unproven: It’s a new format – will users click on an ad that appears in an AI answer? Possibly, if it’s relevant, but we don’t have history to be sure. If early campaigns don’t perform (maybe users ignore the sponsored content or don’t trust it), advertisers could be lukewarm. It will require some testing and learning to optimize ad creatives for this environment.
  
• Ad Integration Pitfalls: If not done carefully, the ads could irritate users. An annoyed user is bad for everyone – they might use the feature less or develop a negative view of the advertiser. So advertisers have to trust publishers/Taboola to integrate their ads in a user-friendly way. There’s a bit of risk in being a pioneer; if something goes awry (like an ad shows up in an inappropriate context due to AI misinterpretation), it could be a PR hiccup.
  
• Brand Safety and Context: Advertisers will want assurances that their ad won’t appear next to weird or problematic AI-generated text. For instance, if the AI answer has some negative news or tragic content and an ad pops up, it might seem tone-deaf. Managing context in generative environments is a new challenge. Taboola will likely offer tools or safeguards for this (they already deal with brand safety in content rec), but it’s something advertisers will keep an eye on.

We can sum up these pros and cons in a simple table for clarity:

Stakeholder	Potential Benefits	Potential Risks/Concerns
Users	– Quick, on-site answers (convenience)
– Info from a trusted source (site’s own content)
– Rich answers with links to learn more
– Natural language querying (easy to use)
– Up-to-date insights on trending questions	– Accuracy issues (AI could be wrong or biased)
– Limited perspectives (only one site’s view)
– Data privacy (query data collected)
– Ads mixed in answers (must be clear which is which)
– Might not encourage cross-checking other sources
Publishers	– Higher user engagement & time on site.
– New revenue from search-intent ads
– Keeps audience from leaving to Google (traffic retention)
– Modernizes site with AI features (competitive edge)
– Insights from user questions (editorial feedback)	– Need to ensure AI’s accuracy to protect reputation
– Initial setup and ongoing tuning effort
– Possible fewer clicks to full articles if AI over-answers
– Uncertain ad revenue scale initially
– Must clearly label AI content and sponsored links (transparency)
Advertisers	– Reach users at moment of intent on credible sites
– Ads appear in a contextually relevant Q&A
– Benefit from publisher’s trust/brand environment
– New metrics and data on engaged readers
– Align with supporting open-web platforms	– Limited reach at first (small query volume)
– Unknown performance, requires experimentation
– Risk of user pushback if ads feel intrusive
– Need assurances on brand safety in AI content
– Dependent on Taboola/publishers to implement well

As with any innovation, the full benefits and pitfalls will become clearer as DeeperDive is tested in the real world. Next, we’ll delve into the ethical considerations, such as AI transparency and how Taboola and its partners plan to address them.

Ethical Considerations and AI Transparency

Whenever an AI system is used to generate content or answers, especially in journalism or public information contexts, ethical questions arise. With DeeperDive, there are a few key areas to consider: transparency, accuracy, attribution, and the broader impact on journalism and information integrity.

Transparency that it’s AI: Users should ideally know that the answer they’re reading is produced by AI and not a human editor. Given the casual style of answers, one might mistake a DeeperDive response for an editor’s summary if it isn’t labeled. It’s important for publishers to clearly label the feature – e.g., calling it “AI Q&A” or having an icon or disclaimer that indicates the answer was generated by an algorithm.

This way, if something sounds off, the user understands it wasn’t an official editorial piece. It seems Taboola and Gannett are framing it as an AI tool openly. The press releases call it a “Gen AI answer engine” and a new technology on the site, so one would expect an on-screen label like “Powered by Taboola AI” or similar. Ethically, this transparency respects the user’s right to know who/what is answering them.

Accuracy and Accountability: As mentioned, AI can make mistakes. If DeeperDive gives a wrong answer, whose responsibility is it to correct it? Likely the publisher will need a mechanism for feedback or corrections. Perhaps if users spot an error, they can report it. Or the publisher’s team might monitor popular queries and double-check the outputs. There’s an ethical duty to not spread misinformation, even if unintentionally via AI.

Taboola has highlighted that answers are sourced from the publisher’s vetted content, which should minimize outright false info. However, things can be taken out of context or combined incorrectly. Publishers may need to set guidelines for what topics the AI is allowed to answer. For example, a publisher might disable or carefully monitor queries about very sensitive or life-critical info (medical advice, legal advice, etc.), or ensure the AI provides a disclaimer (“This is not medical advice; please consult a professional.”) if those come up.

We don’t know the specifics, but these are the kinds of safeguards ethically required when deploying such a tool.

Attribution and Fair Use: One big ethical win that Taboola is pushing is attribution to sources. DeeperDive is built to link to the original articles and not just regurgitate them without credit. This is in stark contrast to many AI answers that might summarize an article’s info without ever mentioning the source. By keeping the user within the publisher’s domain and giving them the source article to click, DeeperDive is respecting content creators’ work and potentially driving traffic to it (or at least giving it exposure).

In Taboola’s words, it’s about “sharing value and respecting the creators who make the internet worth exploring”.This addresses a big ethical criticism of generative AI: that it uses training data (often scraped from news sites, forums, etc.) but doesn’t give back to those sources. Taboola is trying to create a more symbiotic relationship – the AI is not a leech but rather a new interface for the publisher’s own content.

Compensation and Fairness: Following from attribution is the idea of compensation. While a typical AI search engine might cut publishers out of the revenue loop, DeeperDive keeps it all in-house. It’s essentially licensed and sanctioned use of the publisher’s content for AI purposes. Publishers aren’t just giving their articles to an AI for free; they are intentionally using their articles through Taboola’s tool to engage readers, and in return they get the engagement and ad revenue.

Singolda’s strong words about unsustainable practices and exploitation show an ethical stance that creators deserve a cut of the value that AI creates from their content. DeeperDive is a practical implementation of that principle. If it succeeds, it could be a model for others – maybe we’ll see more AI tools that are directly embedded in content sites with revenue-sharing, rather than independent AIs that just scrape everything.

Editorial Independence: Another consideration is whether having an AI widget influences editorial decisions. For example, could there be pressure to produce content specifically to feed the AI for popular questions? Or might the AI answers inadvertently reflect biases in what content exists? If, say, the publisher has less content on a certain viewpoint, the AI won’t present that viewpoint. This isn’t a new ethical issue (search engines have a similar problem surfacing info that exists versus what doesn’t exist), but it becomes something to watch: does the presence of the AI change how content is created or tagged?

Ideally, the AI should be a neutral layer that just uses what’s there. But if publishers see that certain questions are super popular, they might create more articles on those to satisfy readers and the AI – which is positive as long as it aligns with what readers need, but it should not devolve into chasing clicks in a misleading way (like writing sensational content just to feed the AI answers).

User Trust and Misuse: Publishers will need to ensure that the AI doesn’t inadvertently spread something harmful. For instance, a user could ask a provocative or malicious question. Will the AI just quote something from the site? Could it be tricked into giving an answer that seems official but is actually problematic? We’ve seen instances where AI can be prompted into giving odd responses. If DeeperDive were misused (say someone tries to get it to output hate speech by referencing something on the site or a fringe interpretation of it), there need to be guardrails.

Taboola likely will implement content filters as part of the AI, but since it’s site-specific, it might be a bit safer (most mainstream news sites won’t have outright hate content to draw from). Still, things like outdated information (e.g., an old article with medical advice that’s since changed) could be an issue if not updated.

Impact on Journalism: Ethically, we can also zoom out and ask: is it good for journalism to have AI summarizing their content on-site? Some might argue it’s great if it keeps readers engaged. Others might worry it further conditions readers to consume bite-sized summaries instead of full articles. This touches on the value of original journalism. If people just read AI-produced snippets, will they appreciate the reporting and writing that went into the actual article?

Taboola’s approach does encourage clicking through, so hopefully it complements rather than substitutes the reading of full stories. The ethical approach here is to use AI to enhance discovery of content, not replace content. From what we’ve gathered, Taboola is indeed aiming to enhance (the answer plus “here’s more if you want it” approach).

AI Bias and Unintended Consequences: All AI carries the biases of its training data. In this case, the “training data” or reference is the publisher’s content archive. If that content has blind spots or leanings, the AI’s answers will mirror those. Ethically, it’s something publishers should be aware of. For instance, if a site has mostly male experts quoted in articles, the AI might rarely mention female perspectives. Or if the site historically hasn’t covered certain communities, the AI might not have info on them when asked.

This isn’t unique to AI (any search function has the same limitation: you can only find what exists in the corpus), but because AI gives a veneer of an authoritative answer, it can be more misleading. Ethically, ensuring diversity and breadth in the underlying content will yield better AI answers.

User Education: Lastly, an ethical approach involves educating users on how to use this tool. Perhaps a brief intro or tooltip when you first use DeeperDive would explain: “This answer engine uses AI to summarize content from our site. Please click the links for full details, and remember to verify important information.” A gentle reminder that this is a guide, not gospel. In an ideal scenario, users become more savvy about AI outputs – knowing they’re convenient but not infallible.

So, in the grand scheme, Taboola’s DeeperDive is something of an ethical experiment too: Can generative AI be deployed in a way that supports journalism rather than undermining it? The explicit design choices (on-site deployment, source linking, revenue sharing) are positive signs. But the proof will be in how responsibly it’s managed day-to-day. Publishers and Taboola will have to maintain open communication and perhaps even involve editors in refining the AI’s behavior.

The broader tech community is certainly watching moves like this, which leads us into how the industry and media are reacting to Taboola’s initiative.

Tech Industry and Media Reaction

The launch of DeeperDive has sparked interest in both media circles and the tech industry, as it sits at the intersection of journalism and AI – two domains that have been colliding a lot lately. Here’s a snapshot of the reaction and commentary surrounding Taboola’s new venture:

Publishers’ Response: We know that at least two publishers, Gannett and The Independent, were part of the development as design partners and they’ve publicly lauded the move. Mike Reed of Gannett called it “an exciting win for our audience and the publishing industry at large”, highlighting that Taboola has a track record with them and that this gives readers a new way to explore trusted content.

This positive tone suggests that big publishers are eager for solutions to the AI/search dilemma and willing to try something new to keep readers and revenue. It’s likely that other publishers are watching Gannett’s trial closely. If USA Today’s experiment shows strong engagement without major hiccups, more will probably jump on the bandwagon. Taboola has thousands of partners – not all will implement this immediately, but success stories will drive adoption.

The fact that The Independent (a UK publisher) is also on board shows this isn’t just a U.S. concern; European and other international media are similarly looking for ways to harness AI to their advantage.

Media Coverage: The launch was covered by outlets like Axios (who broke the story as an exclusive), and it’s been noted in financial and tech news sites such as Seeking Alpha and GuruFocus. The tone of these pieces is generally factual, explaining what DeeperDive is and why Taboola is doing it. For example, Axios emphasized Taboola’s large network and the monetization angle, noting it could unlock new types of search advertising revenue for publishers on their own sites.

Industry newsletters and sites that follow media trends (like Digiday, Nieman Lab, etc.) have also been reporting on similar initiatives like Perplexity’s publisher program, which puts Taboola’s move in context. The narrative forming is that publishers are experimenting with AI to reclaim their audiences and revenues – Taboola’s DeeperDive is one prominent example of this trend.

Tech Industry Perspective: In the broader tech world, the idea of more specialized or vertical search engines is gaining traction. Startups like Perplexity AI and ProRata have been mentioned as trying to partner with publishers to create AI search experiences that also share revenue. Perplexity has even launched a revenue-sharing program with a handful of publishers (like Time and Der Spiegel) where it will give a portion of ad revenues when its AI uses their content, see: niemanlab.org.

ProRata is doing something similar, signing up publishers like The Boston Globe and Vox Media for an AI that respects licensing. The fact that Taboola, a relatively established player, is entering this space validates the concept further. Some tech analysts see this as part of the “next wave of search” – moving away from one-size-fits-all search engines toward more curated, domain-specific AI search tools.

SEO and Digital Marketing Folks: People in the search engine optimization (SEO) and marketing community, who keep a close eye on Google and traffic patterns, have also weighed in. There’s cautious optimism – anything that can keep users on publisher sites could be good for organic traffic retention. Some have pointed out that this is reminiscent of the old concept of internal site search but on steroids.

In the past, internal search wasn’t huge for many news sites (people would just use Google), but if you make it AI-driven and conversational, it could revive the idea of using a site’s own search bar. It will be interesting to see if SEO experts start advising sites to implement such AI tools as part of audience strategy. On social media (or X/Twitter), figures like Glenn Gabe (an SEO expert) highlighted the news, noting the scale of Gannett’s planned rollout (all 220 local sites eventually). The SEO world will likely monitor whether those sites see changes in user behavior metrics.

Comparison to Big Tech: A lot of the reaction inevitably compares Taboola’s approach to Google’s approach. Google’s relationship with news publishers has been fraught – there have been disputes over content usage (in Europe, laws about paying publishers for snippets, etc.), and now with AI answers possibly reducing clicks, tensions could rise again. Taboola’s CEO explicitly contrasting their solution with “Gen AI engines that scrape content without permission… offering no compensation” is a thinly veiled swipe at big tech practices.

Some media commentators might frame this as part of a larger pushback by the open web against tech giants. The fact that Yahoo (once a big search player itself) is a major stakeholder in Taboola and aligned on native ads is also interesting, though Yahoo’s stake is more about traditional content ads than AI search. It wouldn’t be surprising if down the line Yahoo’s properties also consider using DeeperDive in some form (Yahoo has many content sites).

Skepticism: Not all reaction is glowing. There is healthy skepticism too:

• Will users actually adopt this behavior change? Getting people to use a new feature is always tricky. Many might still instinctively go to Google or ask their voice assistant for a query rather than typing into a news site’s box. It might require prominent placement and perhaps some user education (like pop-ups saying “Got a question? Try our new AI search!”).
  
• Taboola’s brand itself has a bit of baggage. In some circles, “Taboola ads” are synonymous with clickbait. Some tech commentators might cynically joke, “Oh great, the company that brought us those bizarre sponsored links is now doing AI. Will it tell me that one weird trick to burn belly fat? 😅” This is an image issue. However, Taboola’s positioning of DeeperDive is quite different (as a quality content tool), so if executed well, it could improve Taboola’s reputation by association with serious publishers.
  
• Another question raised: How will this scale to smaller publishers or those outside Taboola’s network? If this is primarily a Taboola service, it might not be accessible to those who haven’t partnered with them. So some industry folks may view it as Taboola securing its client base with a new service so they don’t defect to something like a Perplexity. It’s a valid business move, but not necessarily an altruistic one.

Future Speculation: The media is also speculating on what this means for the future. If it works, could we see a fragmentation of search? Instead of going to Google for everything, people might go directly to a handful of trusted publishers’ AI engines for certain topics. For example, maybe you’d go to WebMD’s site to ask health questions and CNN’s site to ask about world news, etc. It’s like each reputable outlet becomes a mini search service for its domain.

This was tried before in different forms (e.g., people go to specific forums or Q&A sites for niche queries), but AI could make the experience smoother. The tech industry loves to predict disruption, and some are saying if such models catch on, Google’s monopoly on answering questions could diminish somewhat. That’s a big “if” and would take a lot, but it’s a narrative out there: “Is this the beginning of publishers taking back search from Google?”

In summary, the reaction has been a mix of hope and caution. Many see Taboola’s DeeperDive as a clever and potentially transformative idea – a way to align AI with content creators’ interests. It fits into a broader movement where AI is being integrated with established media (we also see experiments like news organizations creating their own AI chatbots using their archives). But everyone also recognizes it’s early.

As one market analyst perspective put it, DeeperDive addresses a growing demand for AI solutions in publishing and offers a competitive edge by keeping readers on their platforms, aligning with the trend of integrating AI to enhance user experience.

The financial analysts, meanwhile, note it as a strategic move to capture more ad market share and possibly boost Taboola’s revenue streams, which investors would obviously welcome given Taboola’s net losses in recent years.

All eyes will be on those initial rollouts on USA Today and The Independent. If we start hearing about positive results (like “Readers asked X thousand questions in the first month and stayed Y% longer on site”), expect press releases and conference talks about it. If issues arise, they’ll be learning experiences not just for Taboola but for any publisher pondering an AI helper on their site.

Future Outlook: Taboola and AI in the Coming Years

Taboola’s foray into generative AI with DeeperDive is likely just the first step in a larger journey of integrating AI across its services. Let’s gaze into the crystal ball and consider what the future might hold for Taboola and AI-powered search in general:

Scaling Up DeeperDive: In the near future, we can expect Taboola to roll out DeeperDive to many more of its partner sites if the initial tests go well. This could mean hundreds or thousands of sites adding that AI Q&A widget. We might see different verticals getting tailored AI treatments – for instance, a cooking site might have an AI that can give you recipe ideas from its database (“What can I make with chicken and broccoli?”) while a sports site’s AI handles sports trivia and stats questions.

Taboola might even brand these differently per site, or perhaps keep the “DeeperDive” name universally known as a Taboola product (kind of like “Intel Inside” but for AI on websites). Over time, if such widgets become common, web users might get more accustomed to staying on a site and asking the site directly, which would be a big shift from the last two decades of reflexively going to Google.

Improving AI Capabilities: Right now, DeeperDive likely works primarily by retrieving and summarizing content from the publisher’s own articles. In the future, Taboola might enhance it with more sophisticated AI models, possibly fine-tuned per vertical (like a sports-tuned AI vs a finance-tuned AI) for better accuracy. They may also incorporate multimedia – imagine asking a question and the AI can pull up a relevant chart or image from the site’s media library as part of the answer.

Or it might integrate short video answers (if the site has video content, the AI could say “Here’s a clip where our reporter explains this,” and embed it). The experience could become richer as the technology matures.

AI Agents for Transactions: Singolda mentioned “AI agents across categories like travel, finance, sports, and commerce” as a future vision, per: globenewswire.com. This hints that Taboola might evolve DeeperDive from just Q&A into something more interactive and task-oriented. For example, a travel AI agent on a publisher’s site could not only tell you the best time to visit Paris, but also help you book a flight or hotel (essentially acting like a travel agent chatbot, possibly via partnerships with travel companies).

A finance AI agent could answer questions about personal finance and then guide you to actually apply for a credit card or mortgage offer. These would take Taboola even further into the territory of affiliate marketing and lead generation – which are high-value actions online. It could blur the line between editorial content and service tool. If done transparently and helpfully, it could make publisher sites more of a one-stop-shop for info and action.

Competition and Market Landscape: Taboola won’t be alone. As noted, others like Perplexity and ProRata are working on their solutions. It’s possible that some publishers will choose different partners or build their own in-house AI solutions (large organizations like The New York Times or the BBC might experiment on their own rather than use Taboola, for instance). There might also be competitors from the traditional search side – for example, Google might counter by offering AI tools for publishers to use on their sites (Google already provides custom search engines for sites, so an AI version isn’t hard to imagine).

If Google or Microsoft start providing “publisher AI kits”, Taboola will have to stay ahead or differentiate perhaps by offering more favorable revenue share or deeper integration with content. There’s also Outbrain – Taboola’s long-time competitor. Outbrain hasn’t publicly launched an equivalent AI search as of mid-2025, but it wouldn’t be surprising if they are cooking up something similar. The two often match each other’s offerings (e.g., both do content recommendations, both do video now, etc.). So, we might soon hear about an Outbrain AI tool for publishers too.

Publisher Adoption and User Adoption: One key future factor is how widely users embrace these AI search experiences. If they catch on, we could see a notable shift in web navigation habits. It might become normal that when you’re on a site, you engage with its content more deeply via AI rather than bouncing around. This could strengthen the “direct visit” economy as opposed to the “search engine referral” economy. Publishers would love that because it means more loyal readership.

But it depends on if the quality of AI answers and the user interface really click with people. We’ll likely see continuous refinement – perhaps incentives like prompting users (“Ask us a question!” pop-ups) until it becomes second nature for a segment of the audience.

Regulatory and Policy Outlook: On the horizon, there’s also the question of whether laws or regulations might influence these AI deployments. For example, some jurisdictions might require disclosure of AI use (which good actors will do anyway). There’s also ongoing debate about training data – but since Taboola is using content it has rightful access to (through partnerships), that’s less contentious legally.

If anything, Taboola’s model might be held up as a positive example in policy discussions about fair use of content in AI: it shows a way to do it with permission and shared benefit. If regulatory frameworks push for content owner compensation from AI companies, Taboola is ahead of the curve by building that in from the start.

Impact on Taboola’s Business: If DeeperDive and follow-on AI products succeed, Taboola’s profile as a company will change. They’ll no longer be seen just as the “content recommendation ad company” but also as an AI tech provider for media. That could open new business lines – maybe offering AI solutions beyond search, like AI-assisted article writing tools for publishers (some newsrooms use AI to draft summaries or reports; Taboola could potentially expand into content creation assistance since they are already parsing all that content).

They might also extend AI to the ad side: imagine AI that helps advertisers craft better native ads or target them better using Taboola’s data. In fact, earlier in 2025 Taboola announced things like Predictive Audiences to help advertisers target users using AI, so they are certainly infusing AI into multiple parts of their platform.

User Expectations: By 2025 and beyond, people are rapidly getting used to interacting with AI in various ways (thanks to smartphones, voice assistants, GPTs, etc.). So a future where every major website has an AI helper doesn’t feel far-fetched. Taboola hopes to be a key player enabling that. If they pull it off, browsing the web in 2026 or 2027 might feel different: more interactive, more Q&A oriented on sites, and hopefully more rewarding in terms of finding what you need without wading through irrelevant stuff.

Challenges Ahead: Of course, Taboola will have to overcome challenges. Technically, integrating with thousands of sites and dealing with millions of queries (if it scales) means ensuring fast, reliable AI responses. They’ll likely use a robust cloud AI infrastructure (possibly partnering with an AI model provider or using open-source models fine-tuned to each site). They also have to maintain quality. If some site’s implementation goes haywire and, say, provides a bunch of nonsensical answers, that could make headlines and hurt the concept. So quality control, publisher training, and continuous improvement of the AI will be ongoing tasks.

The Broader Picture: The future might see a sort of renaissance for on-site search and content discovery. In the early web days, lots of sites had their own search but it was basic. Then Google became the gateway to everything. Now AI might bring some power back to the individual sites, making them more engaging destinations rather than just one-stop articles.

For Taboola, success would mean their AI engine becomes a standard component of the open web’s infrastructure, similar to how their content widgets proliferated. If they execute ethically and effectively, we might look back and say Taboola helped publishers adapt in the AI age rather than being steamrolled by it.

In conclusion, Taboola’s DeeperDive represents an innovative blend of journalism, search, and artificial intelligence. It addresses real concerns publishers have while aiming to improve user experience and open new revenue streams. For the general public, it means the way you get information from your favorite news or specialty sites could become more interactive and personalized. As with any new tech, we should keep an eye on how it develops – the promises, the pitfalls, and the outcomes.

But one thing’s clear: the search engine landscape of 2025 and beyond is not going to be “just Google and Bing”. We’re entering an era where every site could have its own AI, and Taboola is helping lead that charge on the open web. It’s a deep dive indeed into the future of search and content discovery.