AI in Marketing

Google is integrating its NotebookLM tool with the Gemini chatbot, allowing users to attach entire notebooks directly within Gemini chats. This feature, initially found in code during an APK teardown, is now available to a limited number of users. When activated, the Gemini chat interface includes a NotebookLM option in the attachment menu, enabling users to attach existing notebooks for more comprehensive responses. Users can ask Gemini to summarize, compare, brainstorm, or reason over the notebook content using Google's reasoning models without leaving the app. The integration also allows users to return to the NotebookLM interface via a "Sources" button to access original documents. Currently, access is limited, with reports indicating that the feature is not available on all accounts, suggesting an early-stage experiment. A broader rollout and official announcement from Google are anticipated in the future.

Following Google's integration update, we look at Resemble AI's funding efforts.

Resemble AI, a cybersecurity firm focused on artificial intelligence, has secured $13 million in funding to combat the growing threat of deepfake cyberattacks. The company highlights the significant financial impact of deepfake-related fraud, which resulted in $1.56 billion in losses in 2025 and could lead to $40 billion in U.S. fraud losses by 2027. Resemble AI's platform includes two key solutions: DETECT-3B Omni, which identifies deepfakes across various media, and Intelligence, an AI model that provides context to generative content. The funding arrives as AI tools become more accessible to criminals, lowering the barrier to entry for large-scale fraud. Research indicates identity gaps cost businesses over 3% of revenue globally, emphasizing the need for frequent updates to security measures.

While Resemble AI addresses deepfake threats, AI's role in influencer marketing expands.

Artificial intelligence (AI) is increasingly integral to influencer and key opinion leader (KOL) marketing, particularly for B2B growth teams. The focus has shifted from questioning the efficacy of influencer marketing to enhancing its execution, measurement, and scalability. AI addresses persistent operational and performance challenges by analyzing large data sets efficiently, identifying patterns, automating repetitive tasks, and evaluating performance with precision. Key issues in influencer marketing include reliance on manual workflows, superficial evaluation, fake followers, and limited attribution. As campaigns expand across platforms like LinkedIn, YouTube, Instagram, and TikTok, these challenges intensify, leading to wasted budgets and unreliable reporting. AI aids in creator discovery, engagement authenticity analysis, audience quality review, performance forecasting, and automated reporting, resulting in faster campaign planning, improved creator selection, reduced fraud risk, and better campaign visibility. However, successful influencer marketing still requires human coordination for tasks like creator outreach, contract management, and compliance oversight. Execution-focused agencies play a crucial role by integrating AI insights into actionable campaign plans, ensuring that data informs execution rather than remaining unused.

Regarding AI-generated text indicators, the focus shifts to Google's AI Mode impact.

Reddit users have identified several indicators that a text might be generated by AI, with the em dash being a prominent example, often referred to as the "ChatGPT dash." AI models, trained on vast amounts of human writing, frequently incorporate em dashes to mimic natural writing styles. This punctuation mark became more prevalent as AI tools gained popularity. Other signs include the use of phrases like “and honestly?” which AI often employs to add emphasis but can seem awkward in casual conversation. The phrase “no fluff” is another indicator, suggesting a direct approach but ironically adding unnecessary filler. AI-generated texts also tend to feature short, fragmented sentences intended to convey emotional weight, though their overuse can be a giveaway. The structure “it’s not X, it’s Y” is similarly overused by AI, often appearing alongside fragmented sentences. Signposting, or guiding readers with phrases like “the key point is,” is another technique AI relies on heavily, more so than typical human writers. Lastly, generic engagement prompts such as “curious what others think” are common in AI-generated content, especially on social media, where AI may ask for engagement but not interact further, highlighting its non-human nature.

Moving from Google's AI Mode to Klarna's Agentic Product Protocol development.

Google's AI Mode, which generates recipes by merging elements from various sources, is negatively impacting the livelihoods of recipe writers. These AI-generated recipes often lack accuracy and originality, sometimes even incorporating elements from satirical sites like the Onion. Recipe creators, who rely on ad revenue, are seeing significant declines in traffic as users opt for AI-generated content that appears in search results without needing to visit the original sites. This trend is particularly concerning as recipes are not protected by copyright, leaving creators with little legal recourse. Some bloggers, like Jim Delmage and Karen Tedesco, have maintained steady traffic by focusing on building a loyal audience rather than optimizing for search engines. However, others have experienced drastic drops in viewership. The rise of AI-generated content is prompting some bloggers to consider subscription models or a return to traditional cookbooks, though these options present their own challenges.

While Klarna enhances product discoverability, AI transforms email marketing strategies.

Klarna has introduced the Agentic Product Protocol, an open standard designed to enhance product discoverability by AI agents. This protocol offers a structured feed of 100 million products and 400 million prices across 12 markets, enabling AI systems to efficiently find, compare, and recommend products. The API supports formats like Google Merchant, Shopify, and Facebook Catalog, making products accessible to AI platforms. Klarna's Chief Commercial Officer, David Sykes, emphasized the importance of a common language for exchanging product data among AI systems, merchants, and platforms. Additionally, Klarna has expanded its partnership with Google to support the Agent Payments Protocol, aiming to establish a secure, AI-driven payment architecture. This collaboration reflects a commitment to intelligent commerce and automation.

Following AI-driven email advancements, we examine semiconductor market stabilization.

AI-powered email content suggestions are revolutionizing marketing by enabling teams to create, test, and scale campaigns more effectively. These tools analyze data to generate personalized content that boosts engagement and conversion rates. By integrating AI with CRM systems, marketers can produce subject lines, copy, and CTAs that align with customer behavior. Tools like HubSpot’s Breeze Copilot and Writesonic’s Email Generator streamline content creation, while Seventh Sense optimizes send times. AI-generated emails require robust QA processes to ensure compliance and brand consistency. Effective prompts and guardrails enhance personalization and performance, transforming AI into a powerful marketing asset. A strong measurement plan distinguishes effective strategies from those that merely sound appealing. By employing a test-and-learn approach, marketers can refine email strategies, prove ROI, and understand what works. The process involves defining a test matrix aligned with lifecycle stages, changing one variable at a time, and attributing results through CRM and campaign analytics. Expanding insights beyond email and building a shared performance dashboard are crucial steps. Common pitfalls include generic outputs and brand drift, which can be avoided with proper context and standardized tone rules. HubSpot tools facilitate AI-driven email content creation and measurement, ensuring brand consistency and improved performance.

Regarding semiconductor stocks, the focus shifts to AI-driven market dynamics.

Semiconductor stocks are stabilizing after last week's AI-driven volatility. Nvidia and Micron are gaining, with Nvidia unveiling its Nemotron AI models and benefiting from strong demand for its H200 chips in China. Semiconductor equipment makers like KLA and Applied Materials are rising on optimistic 2026 forecasts. In contrast, Broadcom, Arm, and Texas Instruments are under pressure due to margin concerns and downgrades. Analysts are focusing on AI-linked growth, with Micron's upcoming earnings report being crucial for insights into AI memory demand. Intel is in the spotlight for potential acquisition talks with SambaNova Systems. The market is cautious about AI profitability, with a focus on equipment as a reliable investment in the semiconductor sector.