Ad Tech Briefing: Google’s Pmax updates suggest it might finally listen – Digiday

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Sometimes it feels Google can’t do right for doing wrong, but let’s not feel overly sad for a company that generates hundreds of millions in daily ad revenue.

As Digiday noted on multiple occasions, April was a tumultuous month for the online advertising giant. Multiple antitrust trials placed its data firehose Chrome at risk of a forced sell-off. Then, there’s the fate of third-party cookies in the market-leading web browser, a saga that has been a central strand in its narrative arc in the 2020s.
A parallel strand to Google’s narrative throughout the 2020s has been the threat AI poses to what many consider Google’s moat: its search advertising business, which generated more than 50% of its ad revenue last year.
Google has been responding to threats posed by ChatGPT and Perplexity et al. with AI offerings of its own — a little too aggressively, according to some. Chief among these has been Performance Max, or Pmax as it is more colloquially known, an offering that has been touted as the key to delivering advertisers’ goals, but without cookies.
However, it hasn’t been without controversy. 
In a blog post entitled “Channel performance and more reporting coming to Performance Max,” published earlier this week Tal Akabas, director of product management at Google Ads, noted that the outfit was “introducing new reporting to Performance Max to give you insights into your channel performance, Search terms, and assets.”
This will be a welcome development for the million-plus advertisers who have trialed the technology since its 2021 launch, and grumbled at the opacity of the responses to their questions on how exactly it produces results.
Pmax has raised ongoing transparency concerns among advertisers, particularly those in performance-driven sectors. Launched to unify Google’s inventory — from search and YouTube to display and maps — PMax leverages AI to automate placements, creative, and bidding. 
However, this opacity is precisely the issue, despite the assurances of Google’s executives. 
Advertisers increasingly complain that PMax functions as a “black box.” Unlike traditional campaigns, it offers limited insight into which channels drive conversions, which keywords are triggered, or how budgets are allocated across formats. This makes it challenging to optimize spend or diagnose underperformance. Retailers, for example, struggle to differentiate brand from non-brand traffic, leading to concerns that PMax is capturing branded conversions that would have happened anyway.
Another flashpoint is the cannibalization of existing campaigns. Marketers report that PMax often duplicates efforts already covered by search or shopping campaigns, diminishing control and complicating attribution modeling. This makes campaign performance appear inflated while hiding true marginal gains.
Agencies and DTC brands have also voiced worries that Google’s AI disproportionately favors its platforms and gives minimal actionable feedback, forcing advertisers to rely more on Google’s interpretation of success metrics than their business goals.
Google has acknowledged some of these issues and gradually added reporting tools, such as asset group performance and search term insights. Still, many marketers feel these updates fail to offer true transparency, especially in high-spend, ROI-critical environments where accountability is paramount.
“Today, we’re excited to introduce new channel-level reporting in Performance Max — a top-requested feature,” wrote Akabas in the April 30 blog post. “We’re also adding full search terms reporting and more detailed asset reporting that shows you all the metrics for individual assets.”
The introduction of channel-level reporting is a significant enhancement. Advertisers can now see performance breakdowns across individual Google properties — including YouTube, search, Gmail, display, and on maps — to better understand where conversions occur. A new “Channel performance” page features visual summaries and a detailed channel distribution table with metrics such as clicks, conversions, and cost, which is also downloadable.
Google also expanded asset-level reporting. Advertisers can now view impressions, clicks, and cost per asset, helping them understand which creatives drive performance. This reporting is also being extended to search and display campaigns beyond Performance Max.
In addition, search term reporting is now available, matching the granularity seen in standard search campaigns. This allows advertisers to refine keyword strategies and implement negative keywords or brand exclusions when needed.
Finally, Google introduced channel-specific diagnostics to highlight performance limitations, such as missing store locations or irrelevant landing pages, and recommend fixes, including tools like final URL expansion to improve relevance and reach.
Whether such overtures will ameliorate the hawkish tendencies of the powers that be at regulators, both in Europe and within the Justice Department, remains to be seen.
Of course, Google’s assurances of transparency have given us cause to take them at face value, but with a pinch of salt, although for now, it appears as if Google might finally be listening. 
If you feel strongly about any of the issues discussed above, then feel free to get in touch – no PR pitches please.
British, Australian and EU regulators are all looking into mega agency merger.
The FTC has granted the Omnicom-IPG merger under unusual conditions with major implications for brand clients.
Much of the large announcements at last week’s Cannes Lions Festival of Creativity involved TV streaming and ad tech.
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Google Updates Unfair Advantage Policy, Advertisers React – Search Engine Journal

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Google updates its Unfair Advantage Policy, clarifying ad slot dominance rules. Here’s what it means for advertisers and how the PPC community is reacting.
On Friday, Google sent out a subtle but impactful policy update to advertisers, confirming changes to its long-standing “Unfair Advantage Policy”.
While the official enforcement date is April 14, 2025, the conversation has already started — and it’s anything but quiet.
The PPC community is buzzing with opinions, questions, and concerns. But this update didn’t come out of nowhere.
About a month ago, Google quietly laid the groundwork for this change without most people noticing.
Let’s unpack exactly what’s happening, why it matters, and how advertisers are reacting.
The core of the update is about limiting how many ads a business, app, or site can show in a single ad location. Here’s Google’s new language:
Google email to advertisers about Unfair Advantage policy update.
The new language is crucial to understand.
The focus isn’t on restricting brands from showing multiple ads across different placements—it’s about stopping advertisers from stacking multiple ads in the same slot, which would effectively block competition and inflate dominance.
It’s not a total ban on multiple ads from the same advertiser showing on a single page, but rather a limit within a specific ad location.
However, as with many Google Ads policies, the phrase “single ad location” is doing a lot of heavy lifting—and advertisers are left wondering how Google will interpret and enforce it in practice.
One notable detail: Google says violations won’t lead to instant account suspensions. Advertisers will receive a warning and at least seven days to address any violations before facing suspension.
This is important. Google seems to be trying to strike a balance between tightening policy and giving advertisers room to adapt.
Interestingly, this isn’t the first time Google has hinted at this shift.
Back in February 2025, advertisers noticed that Google updated its documentation on “How the Google Ads Auction Works”.
The update clarified that Google runs separate auctions for each ad location, meaning that the auction for the first position is distinct from the auction for the second, third, and so on.
Ginny Marvin, Google Ads Liaison, even acknowledged the change directly in LinkedIn discussions. This detail flew under the radar for many but now seems like a foundational piece for this official Unfair Advantage update.

Effectively, Google was setting the table a month ago. This policy update simply formalizes how those auctions will now prevent advertisers from “double-serving” or stacking ads in the same position.
Google’s goal here appears twofold:
Auction Fairness — Google wants to prevent scenarios where advertisers, affiliates, or large multi-account setups game the system by occupying multiple positions within a single auction.
Affiliate Abuse Control — This rule directly calls out affiliates who break affiliate program rules, a growing concern in Google’s search ecosystem.
Of course, some advertisers suspect there’s a third goal: protecting the user experience and, more directly, protecting Google’s own long-term revenue by encouraging more advertisers to compete rather than allowing the largest players to squeeze others out.
While this update was emailed to advertisers on Friday afternoon, marketers didn’t waste time sharing their takes on the update.
Andrea Atzori, who also received the email from Google, took to LinkedIn to provide his take on the update.
Atzori highlighted that this change is more about clarification than transformation, as he’d seen the same advertiser in multiple locations previously.
Navah Hopkins also took to LinkedIn with a more brief update, eager to hear thoughts from fellow marketers on the Unfair Advantage policy.
Hopkins and others noted that while the update may sound fair in theory, the proof will come in how it affects impression share, Auction Insights, and real-world campaign performance.
From the comments on Hopkin’s post, early reactions seem to lead towards skepticism and questions:
Chris Chambers commented:
This is going to be wild from a metric reporting standpoint since it seems like right now it counts as 2 impressions and also affects your impression share and position in Auction Insights (same with competitors).

But it also seems like now the advertisers with the most to spend in each niche will get even more real estate and be able to show twice, potentially cutting out smaller competitors completely from the first page.
Steve Gerencser had a similar take to Chambers:
I wonder how they are going to count people that pogo from one ad right back to the next and then back to something else? I can see a lot of wasted ad spend, or an opportunity for someone with deep pockets to dominate.
Some worry that well-funded advertisers will still find ways to dominate, while smaller brands hope this levels the playing field.
While the policy may not seem earth-shattering at first glance, it does come with a few things advertisers should actively monitor.
First, smaller and mid-sized advertisers may stand to benefit, at least in theory. By limiting how many ads a single business can show in one location, Google could slightly reduce the dominance of big-budget brands that have historically owned the top of the page through multiple placements.
This could open up space for other players to get visibility where previously they were pushed out.
But, as several PPC pros pointed out on LinkedIn, the big question is how Google defines and enforces a single ad location in practice.
Google clarified last month that each ad location runs its own auction, meaning it’s technically possible for a brand to show up in multiple places on the same page—just not in the exact same slot.
So, while the policy aims to limit dominance, it doesn’t necessarily mean fewer total appearances for advertisers with deep pockets.
This also has potential ripple effects on Auction Insights reports. If Google starts filtering or limiting how often multiple ads from the same business appear in a given location, expect impression share metrics and overlap rates to behave differently—maybe even unexpectedly.
Advertisers will need to watch Auction Insights and Impression Share trends closely post-April to see if any patterns emerge.
Additionally, affiliate marketers and businesses using aggressive multi-account or multi-site strategies should be especially careful. The updated policy makes it clear that affiliates must play by their program’s rules and can no longer try to sneak multiple ads for the same offer into the same auction.
While Google says you’ll get a warning before any suspension, it’s probably wise to get ahead of this now, rather than risk a compliance issue later.
And finally, there’s still some ambiguity about multi-brand or franchise setups. If you’re managing a brand with multiple sub-brands, sister companies, or franchisees, the question remains: will Google treat you as one business under this policy or multiple?
That detail could make a big difference, especially for large organizations or verticals like automotive, real estate, or hospitality.
Honestly? It’s hard to call this a monumental shift yet. The update feels more like a formalization of existing enforcement patterns than a radical new rulebook.
That said, the PPC community is right to question what this will look like in Auction Insights and daily performance reports. Whether this is a minor tweak or the start of stricter anti-duplication policing will become clearer as advertisers see real-world data throughout Q2 and beyond.
Either way, it’s worth watching—especially if you’ve ever benefitted from, or competed against, someone taking up too much SERP real estate.
Brooke serves as the Director of Growth Marketing at Smith Micro Software, with over 10 years of paid media experience. …
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Google Slides now uses Imagen 3 and adds other new visual tools. – Google Blog

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Today we announced new features for Google Slides, making it easier to create visually stunning presentations. Here’s what’s new:
Check out the Workspace blog for all the details.
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Google Cloud Next 2025: Gemini & agentic AI updates, new TPUs – Capacity Media

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Pichai highlighted that Gemini now powers every one of Google’s half-billion-user products — including seven with more than two billion users — and teased the arrival of Gemini 2.5 Flash, a new low-latency model optimised for fast reasoning and cost-efficiency.
Thomas Kurian, CEO of Google Cloud, expanded on this vision: “What was once a possibility is now the vibrant reality we’re collectively building.”
Kurian revealed that more than four million developers are now building with Gemini, while Vertex AI usage has grown 20x year-over-year, fuelled by the surging adoption of models like Gemini, Imagen, and Veo.
This surge in usage is backed by Google’s vast infrastructure: 42 regions, over two million miles of subsea and terrestrial fibre, and more than 200 points of presence globally — all now accessible to enterprises through the new Cloud WAN service.
Across AI models, agentic systems, networking, and security, Google Cloud’s message was clear: This isn’t just an AI platform; it’s a full-stack transformation engine for the enterprise.
Alphabet CEO Pichai took to the keynote stage to tease the next model in the hyperscaler’s AI arsenal: Gemini 2.5 Flash, a low latency reasoning model. No specific release timeframe was revealed, but the CEO said it represents an evolution of its popular workhorse model.
Google Cloud also provided an update on Veo 2, a Google DeepMind-developed video generation model, revealing it’s now “production-ready” in the Gemini API.
The model can follow both simple and complex instructions, as well as simulate real-world physics in high-quality videos spanning a wide range of visual styles.
Early adopters include Wolf Games, which is using Veo 2 to build “cinematic experiences” for its personalised interactive story game platform.

Google Cloud’s AI Hypercomputer is the workhorse behind almost every AI workload on its cloud platform. The integrated supercomputing system now features the latest iteration of its custom hardware line, Tensor Processing Units (TPUs).
Ironwood, the 7th generation TPU, offers 5x more peak compute capacity and 6x the high-bandwidth memory (HBM) capacity compared to the prior-generation, Trillium.
The new Ironwood TPUs come in two configurations: 256 chips or 9,216 chips, each available as a single scale-up pod, with the larger pod delivering a staggering 42.5 exaFLOPS of compute.
The Hypercomputer hardware is designed to be 2x more power-efficient compared to Trillium while delivering more value per watt.
Developers can now access Ironwood through Google Cloud’s optimised stack across PyTorch and JAX.
Google Cloud saw the hyperscaler double down on its agentic AI offerings, unveiling new tools to let businesses build, deploy and scale multi-agent systems.
At the heart of the updates was the new Agent Development Kit (ADK) — an open-source framework that lets developers build sophisticated AI agents in under 100 lines of code. It’s already being used by brands like Renault and Revionics to automate workflows and decision-making.
To deploy these agents in production, Google introduced Agent Engine, a fully managed runtime on Vertex AI. It supports short- and long-term memory, built-in evaluation tooling, and native integration with Google’s Agentspace platform for secure internal sharing.
The second major agentic announcement was the Agent2Agent (A2A) protocol — an open interoperability standard that allows agents to communicate and collaborate across different frameworks like ADK, LangGraph, and Crew.ai. Over 50 partners including Box, ServiceNow, UiPath, and Deloitte are already onboard.
Networking at Next 2025 was centred on scaling for AI and improving cross-cloud performance.
A new 400G Cloud Interconnect and Cross-Cloud Interconnect, arriving later this year, promises 4x the bandwidth for faster data onboarding and multi-cloud model training.
Google Cloud also introduced support for AI clusters of up to 30,000 GPUs in a non-blocking configuration — now available in preview — aimed at supercharging training and inference throughput.
Generative AI serving costs have been cut by up to 30%, with throughput improvements of up to 40%, thanks to innovations like the GKE Inference Gateway.
Google also debuted Cloud WAN, a fully managed enterprise backbone that opens up its global network infrastructure for wide area networking. Designed to simplify and secure enterprise WAN architectures, it delivers up to 40% faster performance compared to the public internet.
At the edge, Google announced enhanced programmability and performance, with Service Extensions now GA for Cloud Load Balancing. Cloud CDN support is on the way, enabling developers to customise application behaviour at the edge using open standards like WebAssembly.

Enterprise infrastructure is growing in complexity, widening the attack surface and overloading siloed security teams. Google’s answer? Google Unified Security (GUS), which is now generally available.
GUS is designed to unify threat intelligence, security operations, cloud security, and secure browsing into a single AI-powered platform, integrating expertise from the firm’s Mandiant subsidiary to deliver more scalable, efficient protection.
The new security solution creates a searchable security data fabric across the entire attack surface, offering real-time visibility, detection, and response across networks, endpoints, cloud, and apps. Security signals are then automatically enriched with Google Threat Intelligence, and every workflow is streamlined with its flagship Gemini AI models.
Google also introduced Gemini-powered security agents. Among the new agentic AI tools include an alert triage agent in Google Security Operations, which automatically investigates alerts, compiles evidence, and renders verdicts.
A new malware analysis agent in Google Threat Intelligence evaluates potentially malicious code, executes deobfuscation scripts, and delivers verdicts with full explainability. Both are previewing in Q2.
It wouldn’t be a Google Cloud Next without a series of partnerships being struck or extended, and this year was no different.
The hyperscaler expanded its partnership with Lumen to enhance cloud and network solutions. The team-up will focus on integrating Cloud WAN with Lumen’s services, providing direct fiber access to Google Cloud regions, and offering secure, air-gapped connections to Google Distributed Cloud.
Google Cloud also joined forces with Nvidia to bring its Gemini family of AI models to the chipmaker’s Blackwell systems. The move sees Gemini models become available on-prem, enabling customers to lock down sensitive information, such as patient records, financial transactions and classified government information.
“By bringing our Gemini models on premises with Nvidia Blackwell’s breakthrough performance and confidential computing capabilities, we’re enabling enterprises to unlock the full potential of agentic AI,” said Sachin Gupta, VP and general manager of infrastructure and solutions at Google Cloud.
Its Gemini models are also coming to SAP’s generative AI hub on its Business Technology Platform. The hyperscale also added its video and speech intelligence capabilities to support multimodal retrieval-augmented generation (RAG) for video-based learning and knowledge discovery in SAP products.
Also announced was a collaboration with Juniper Networks to accelerate new enterprise campus and branch deployments. Customers will be able to use Google’s Cloud WAN solution alongside Juniper Mist wired, wireless, NAC, firewalls and secure SD-WAN solutions, enabling them to connect critical applications and AI workloads whether on the internet, across clouds or within data centres.
The hyperscaler partnered with Oracle to unveil a partner programme designed to enable Oracle and Google Cloud partners to offer Oracle Database@Google Cloud to their customers.
Data storage firm DataDirect Networks (DDN) also joined up with Google Cloud on its Managed Lustre parallel file system service, which provides up to 1 TB/s of throughput for fast access services for enterprises and startups building AI and High-performance computing (HPC) applications.
Accenture also widened its strategic partnership with Google Cloud, with the pair pledging to work together to develop industry-specific AI solutions.
These latest partnerships add to the ones penned earlier this year, like with Deutsche Telekom, with the pair working together on AI advancement and cloud integration across the operator’s network infrastructure.
Google Cloud to drive Deutsche Telekom’s network modernisation with AI, cloud
Google Cloud, Infovista join forces on RF network planning
Google Cloud supports DT and Vodafone Italy with AI-driven RAN and data overhaul
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Google Issues Emergency Update For All 3 Billion Chrome Users – Forbes

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ByZak Doffman

ByZak Doffman,
Contributor.
Update all browsers now.
Republished on June 5 with new 21-day emergency update deadline for Chrome users.
Google released an emergency Chrome update Tuesday, warning that a vulnerability discovered by its Threat Analysis Group has been used in attacks. Such is the severity of the risk that Google also confirmed that ahead of this update, the issue “was mitigated on 2025-05-28 by a configuration change” pushed out to all platforms.
Google says it “is aware that an exploit for CVE-2025-5419 exists in the wild,” and that full access to details on the vulnerability will “be be kept restricted until a majority of users are updated with a fix. We will also retain restrictions if the bug exists in a third party library that other projects similarly depend on, but haven’t yet fixed.”
CVE-2025-5419 is an out-of-bounds read and write in V8, the type of dangerous memory flaw typically found and fixed on the world’s most popular browser. While it’s only marked as high severity, the fact attacks have been confirmed underway means applying the fix is critical — you do not want to leave your browser at risk.
There is already a U.S. government mandate for federal staff to update Chrome by Thursday or stop using the browser, after a separate attack warning. And there has been another release since then, with two high-severity fixes. It is inevitable that this latest warning and update will also prompt CISA to issue a 21-day update mandate.
There is a second fix included in this emergency update — CVE-2025-5068 is another memory issue, a “use after free in Blink,” that was disclosed by an external researcher.
NIST warns that CVE-2025-5419 “allows a remote attacker to potentially exploit heap corruption via a crafted HTML page,” and that it applies across Chromium, suggesting other browsers will also issue emergency patches.
America’s cyber defense agency has now issued a 21-day deadline for federal staff to update or stop using browsers. This was issued on June 5 and runs to June 26. While the deadline is only mandatory for federal staff, CISA’s remit is to help “every organization better manage vulnerabilities and keep pace with threat activity.”
CISA says “Google Chromium V8 contains an out-of-bounds read and write vulnerability that could allow a remote attacker to potentially exploit heap corruption via a crafted HTML page.” Users should “apply mitigations per vendor instructions,” or “discontinue use of the product if mitigations are unavailable.”
While Google’s warning and most headlines have focused on Chrome itself, CISA reminds users that “this vulnerability could affect multiple web browsers that utilize Chromium, including, but not limited to, Google Chrome, Microsoft Edge, and Opera. Microsoft has updated Edge, warning this latest update “contains a fix for CVE-2025-5419 which has been reported by the Chromium team as having an exploit in the wild.”
As usual, you should see a flag on your browser that the update has downloaded. You need to restart Chrome to ensure it takes full effect. All your normal tabs will then reopen — unless you elect not to do that. But your Incognito tabs will not reopen, so make sure you save any work or copy down any URLs you want to revisit.

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The Post-Traffic SEO Shift – Practical Ecommerce

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Google’s new AI Mode highlights the dramatic changes in organic search. AI answers often eliminate the need to click, though users wanting more details must search unlinked brand names separately.
The result is massive shifts in optimizing for search engines:
Business owners are understandably concerned and unsure how to adjust SEO.
Here’s my overview.
Generative AI platforms use external sources to recommend products and brands. Unless they encounter the benefits of a product or company, the platforms are unlikely to include or recommend them.
Thus an AI-driven SEO strategy includes creating and marketing “brand knowledge content,” which explains:
The goal is to supply info to large language models about your business to increase its chances of being surfaced in AI answers for related consumer questions.
The example below is a chart from Google’s AI Mode comparing Zoho and HubSpot, two popular customer management platforms, in response to a query.
Table from AI Mode comparing Zoho CRM to HubSpot. Click image to enlarge.
Brand mentions are as important as backlinks for genAI algorithms. ChatGPT, Gemini, and others rely on “similarity” and co-occurrence, i.e., where a brand name appears in a relevant context of a query.
Yet backlinks remain important for traditional organic search rankings, and genAI platforms also rely on those engines: Google, Bing, others.
Hence optimizing for AI search should include link building and brand marketing. The following tactics will help with both:
Generative AI search engines use a so-called “query fan-out” technique. Google introduced the term, but other LLMs use similar methods.
This technique goes beyond direct answers. It includes related and follow-up concepts to provide a more detailed explanation and solve users’ problems more efficiently.
Keyword research remains essential for understanding shoppers’ journeys, but optimizing for those terms is more than including them in titles, headings, and body text. Think about the problems driving each keyword and address them with additional info on your page.
My GPT, “SEO: Search Query Analyzer,” can assist, as can ChatGPT and Gemini via this prompt:
My target keyword is [KEYWORD]. What follow-up questions and additional information would help my target audience searching on this query?
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10 "Best" AI Writing Generators (June 2025) – Unite.AI

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Unite.AI is committed to rigorous editorial standards. We may receive compensation when you click on links to products we review. Please view our affiliate disclosure.
Artificial intelligence (AI) technologies have come a long way in a short amount of time. These technologies were traditionally limited to tasks that were clearly laid out with guidelines. However, they are now capable of carrying out creative tasks like writing. 
There are many options when it comes to AI writing software, which can be used to generate long-form content, create engaging headlines, reduce writing errors, and increase production time. 
Here is a look at the 10 best AI writing software tools:
Sudowrite is a unique writing tool that is designed specifically for creative writing including short stories, novels, and screenplays.
Some of the challenges that Sudowrite is designed for are issues that face most creative writers, for example.
Writing – This is like autocomplete on steroids. It analyzes your characters, tone, and plot arc and generates the next 300 words in your voice. It even gives you options!
Canvas – This will generate alternate plot points, character secrets, and plot twists with you. Hoard all your inspiration and references in one place.
Pacing – No matter how much time you spend planning, you’ll end up with some sections that feel rushed. Expand magically builds out your scenes so the pacing doesn’t take readers out of the story.
Visualize – If you need to add art to your words, this brings your character sheets and worldbuilding documents to life with art generated from your descriptions.
Read Review →
Visit Sudowrite →
Many recognize Jasper as the best overall AI writing assistant, leading the market with its impressive features and quality. You first provide it with seed words, which Jasper then analyzes before creating phrases, paragraphs, or documents based on the subject matter and tone of voice. It is capable of producing a 1,500-word article in seconds.
The platform has more than 50 AI content generation templates, including blog posts, emails, marketing copy, Facebook ad generator, Google ad generator, SEO meta title and description, press release, and much more. 
Here is a look at some of the best features of Jasper:
We also Compare Jasper Vs. Copy AI & Jasper Vs. Scalenut.
Read Review →
Visit Jasper →
Scalenut is essentially an all in one marketing tool and is designed to scale. It enables you to quickly and get the entire keyword plan for your niche and to generate a content management strategy to dominate these terms. The software is divided into 4 sections:
Research – Uncover insights and build a strategy that works by getting all the insights and semantic key terms you need to outpace your competition.
Create – Write SEO content that ranks by using the most advanced versions of NLP and NLU (Natural Language Processing & Natural Language Understanding). It offers real-time optimization based on SERP statistics, and offers content that can deliver.
Optimize – Get real-time feedback on where your content stands with a dynamic SEO score. Improve on the go, no more revisions!
Marketing Copy – Write persuasive copy that brings conversions with 40+ AI copywriting templates. This includes the following:
Claim a 20% discount off the monthly subscription fee. Discount Code: FOREVER20 
We also Compare Scalenut Vs. Jasper.
Read Review →
Visit Scalenut →
Surfer is primarily a tool for generating SEO content, some of the core functionalities include:
Outline Builder – Use the built-in Outline Builder to structure your content into a detailed outline complete with unique potential headings and questions.
Topic Discovery – Discover dozens of relevant topic clusters in a matter of minutes, this enables a strategy to target different keywords.
Keywords Volume & Search Intent – Check search intent for your target audience and evaluate monthly search volume and keyword difficulty at a glance. While Google does offer this functionality for free via the Google Keyword Planner, this tool is easier and less frustrating to use.
Internal content structure – This is seamlessly optimized by using real-time metrics for structure, and word count.
AI Writing – Utilize the full power of Surfer to write well-researched and high-quality articles.
AI Content & Plagiarism – While some affiliates may choose to rely on AI generated content, this could result in a Google penalty, this is why the built-in plagiarism and AI content checker is an important tool if you want to avoid penalties.
Read Review →
Visit Surfer SEO →
If you want to generate high-quality website copy and marketing text, Writesonic’s AI-powered content generation technology is the way to go. The tool enables you to generate blog posts, product descriptions, and marketing headlines automatically. Writesonic also allows you to create many variations of Google and Facebook ads in just seconds. 
Here is a look at some of Writesonic’s top features: 
Read Review →
Visit Writesonic →
Designed for SEO, and for websites that need to scale content, the generative AI model is designed to generate humanlike content and passes even the strongest and most accurate AI detectors.
Users can create long-form blog posts in minutes from a keyword, YouTube video, podcast, existing blog, PDF or document, or custom audio file – all with your own unique voice and writing style. For SEO-focused content publishers who need long-form content, and with the ability to product content quickly it is a solid option.
Read Review →
Visit Content at Scale →
Wordtune is one of the most advanced AI writing software tools on the market. Instead of only performing tasks like grammar checking and rephrasing, it works to understand the actual context and semantics of the words it’s fed. The technology enables you to make more compelling and engaging content through advanced, neural-net-based NLP technology. 
After you provide Wordtune with words, it paraphrases the content and rewrites it while improving the text’s readability. 
Here is a look at some of Wordtune’s most impressive features:
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Copy.ai is designed for SEO professionals, when creating a post you can simply choose your title, keywords, the desired tone of the writing, and the goal of the article (such as teaching).
Once this is complete you can choose to review the outline of the article, before the article is completed, this enables you to verify that the article optimization t best matches your use case. It takes seconds for the article to work magic to produce full-length and high-quality posts. You can have it rewrite paragraphs and polish up sentences. Then, just copy and paste the work into your CMS for publishing.
Choose from 90 tools and templates to quickly leap into content creation. Use cases includes blog content, listicles, and social media posts.
We also Compare Copy.ai Vs. Jasper.
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Copy Shark is a new entrant that offers AI powered software that generates ad copy, product descriptions, sales copy, blog paragraphs, video scripts more. It allows users to automatically generate unique and human-like copy in seconds, and best of all it supports over 100 languages.
Some of the tools that are offered include:
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Anyword is a data-driven copywriting tool that is designed for marketers.  It enables the generation of effective copy for ads, emails, landing pages, and content for different platforms.
When it comes to creating adverts it is easy to do so for Facebook ads, Google Adwords, LinkedIn Ads, and Twitter Ads.
Of course for longer form content they also make it easy to generate blog posts, product descriptions, YouTube descriptions, and much more.
Anyword empowers creative marketers to add data to their toolbox by providing predictive metrics and insights into which part of the message works and for whom.
Best of all Anyword’s Performance Boost AI trains ChatGPT, Notion AI, and Canva on your brand, audience & performance data for more engagement, clicks, and conversions. See predictive analytics, get performance scores, and improve copy instantly.
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Artificial intelligence (AI) technologies have rapidly advanced, now capable of performing creative tasks such as writing. AI writing software offers a range of functionalities including generating long-form content, crafting engaging headlines, minimizing writing errors, and boosting productivity. This article explores the top 10 AI writing software tools, highlighting their unique features and benefits. These tools are invaluable for professionals seeking to enhance their writing processes, improve content quality, and streamline operations. As AI continues to evolve, these writing assistants are set to become even more integral to various business and creative applications, driving efficiency and innovation.
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Alex McFarland is an AI journalist and writer exploring the latest developments in artificial intelligence. He has collaborated with numerous AI startups and publications worldwide.
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