In the News: July 13, 2026
AI, social, and advertising platforms are becoming more focused on trust, measurement, and meaningful engagement as AI adoption accelerates. From authenticity requirements in live commerce to AI brand governance, visibility tracking, and data-driven optimization, success now depends on balancing automation with credibility, consistency, and human connection.
Click or tap on a story below to learn more.
LinkedIn Launches Brand Kit for AI-Generated Ads
LinkedIn has introduced a new Brand Kit feature within Campaign Manager that allows marketers to define key brand elements, including colors, fonts, logos, and voice guidelines, in one centralized location. LinkedIn’s AI can then use these parameters when generating ad creative and copy, helping ensure content remains aligned with established brand standards. The platform can also automatically create an initial brand profile by analyzing content from a company’s existing posts and Company Page.
This update reflects LinkedIn’s growing focus on helping marketers scale content creation with AI while maintaining consistency, control, and alignment across campaigns. Rather than simply accelerating content production, the platform is giving brands new tools to influence how AI represents them at every stage of the creative process.
What This Means Right Now
As AI-generated content becomes more prevalent, maintaining brand consistency is becoming just as important as creating content efficiently. LinkedIn’s Brand Kit signals a broader shift from using AI solely for content generation to using AI for brand governance. Marketers are increasingly focused on ensuring that automated creative outputs reflect their brand identity, messaging, and standards, making control and consistency critical differentiators in an AI-powered marketing environment.
How to Put This to Work
1.) Establish clear brand guidelines for AI
Define brand voice, visual standards, and messaging principles so AI-generated content remains consistent and recognizable.
2.) Scale content without sacrificing quality
Use AI-powered creative tools to increase production efficiency while maintaining strong brand alignment.
3.) Audit how AI represents your brand
Regularly review AI-generated content to ensure it accurately reflects your positioning, tone, and customer experience.
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SEMrush Study Highlights AI Visibility Measurement Gap
SEMrush has expanded its 2026 AI Visibility Index by analyzing 126 million U.S. AI search prompts across leading AI platforms. The study found that 45% of marketing leaders cannot accurately measure their brand’s visibility within AI-generated responses, while only 9% have tools in place to track performance across AI platforms. The research also uncovered notable differences in how AI engines source information, with platforms like ChatGPT frequently drawing from community-driven content while Gemini tends to rely on a narrower range of sources.
This research highlights the growing complexity of AI-driven discovery, where visibility is no longer determined by rankings alone but by how different AI systems interpret, select, and reference information when generating responses.
What This Means Right Now
AI search is creating an entirely new visibility challenge for marketers. Unlike traditional search, where rankings can be tracked and optimized with relative clarity, AI-generated answers vary by platform, source preferences, and response formats. As a result, brands may be influencing AI-generated conversations without realizing it or missing valuable opportunities to appear altogether. This shift requires marketers to think beyond SEO performance and begin evaluating how their brand is represented across multiple AI ecosystems.
How to Put This to Work
1.) Expand your definition of visibility
Look beyond traditional search rankings and consider how your brand appears across AI-powered search and answer platforms.
2.) Monitor content sources that influence AI
Invest in content strategies that build authority across websites, communities, and other sources commonly referenced by AI systems.
3.) Prepare for platform-specific optimization
Recognize that different AI engines surface information differently and adapt your visibility strategy accordingly.
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Instagram Tests Captions for Individual Carousel Slides
Instagram is testing a new feature that allows users to add unique captions to individual slides within a carousel post. Instead of relying on a single caption to support an entire carousel, creators can provide context, commentary, and calls to action for each image or video. This gives users more flexibility to build richer, more structured narratives and guide audiences through one slide at a time.
The update reflects Instagram’s continued investment in carousels as a storytelling and educational format, providing creators with new tools to deliver more context and create deeper engagement within a single post.
What This Means Right Now
Carousels are evolving from simple multi-image posts into more interactive, guided content experiences. By enabling slide-specific captions, Instagram makes it easier for creators and brands to break down complex topics, tell more compelling stories, and keep users engaged throughout an entire carousel. This shift rewards content that delivers value progressively, encouraging audiences to spend more time engaging with each slide instead of quickly scrolling past.
How to Put This to Work
1.) Create step-by-step educational content
Use individual slide captions to explain concepts, share processes, or break down complex topics into digestible pieces.
2.) Build stronger storytelling sequences
Guide viewers through a narrative by using each slide’s caption to add context and maintain momentum.
3.) Add targeted calls to action throughout the carousel
Incorporate slide-specific prompts that encourage users to continue swiping, engage with the content, or take action.
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Reddit Launches Split Testing for Advertisers
Reddit has introduced a new Split Testing tool within Ads Manager that allows advertisers to run controlled A/B tests by dividing audiences at the user level and testing a single variable at a time. The platform automatically measures results and identifies a winning variation once statistical confidence is reached, helping marketers make more informed decisions around creative, targeting, and overall campaign performance.
This update reflects Reddit’s continued investment in advertiser tools and measurement capabilities, making it easier for brands to understand what drives results and optimize campaigns based on real user behavior rather than assumptions.
What This Means Right Now
As advertising platforms become increasingly automated, it can be more difficult to understand which specific factors are driving performance. Reddit’s new testing capabilities help address this challenge by giving marketers a structured way to validate strategies, isolate variables, and make decisions backed by data. The result is greater confidence in optimization efforts and a clearer understanding of what resonates with target audiences.
How to Put This to Work
1.) Test one variable at a time
Evaluate creative, targeting, messaging, or offers individually to clearly identify what is influencing performance.
2.) Use data to guide optimization
Rely on statistically validated results rather than assumptions when making campaign adjustments.
3.) Build a culture of continuous experimentation
Make structured testing a regular part of your advertising strategy to improve efficiency and uncover new growth opportunities.
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TikTok Bans AI-Generated Voices in Shopping Livestreams
TikTok has updated its Live Shopping policies to prohibit AI-generated voices and prerecorded audio in shopping livestreams, requiring hosts to engage with viewers through real-time human interaction. The change is intended to create a more authentic shopping experience, improve transparency, and ensure consumers can interact directly with real people when asking questions, evaluating products, and making purchasing decisions.
This policy update reflects TikTok’s growing focus on trust within commerce experiences, recognizing that while AI can enhance content creation and efficiency, certain moments in the customer journey still benefit from genuine human engagement.
What This Means Right Now
This isn’t a signal that platforms are moving away from AI; it’s a sign they are becoming more deliberate about where AI belongs. As AI-generated content becomes increasingly common, trust and authenticity are emerging as key differentiators. TikTok’s decision suggests a future where AI handles more of the content creation process behind the scenes. At the same time, high-trust interactions, particularly those involving purchases, recommendations, and decision-making, continue to rely on human presence. This creates a growing distinction between AI-scaled content and human-led experiences, making authenticity an asset in an increasingly automated digital landscape.
How to Put This to Work
1.) Prioritize human connection in high-trust moments
Use real people for live interactions, product demonstrations, and customer engagement where credibility and trust matter most.
2.) Balance AI efficiency with authenticity
Leverage AI to support content creation and operations, while ensuring key customer touchpoints remain personal and relationship driven.
3.) Build trust as a competitive advantage
Highlight expertise, transparency, and genuine engagement to differentiate your brand in an increasingly AI-generated environment.
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