TLDR:
A new global report from MiQ reveals that while 72% of marketers plan to increase their AI usage, only 45% feel confident in their ability to apply it successfully—a 27-point gap driven by lack of training, data limitations, and measurement challenges.

Details:

The "AI Confidence Curve" report surveyed 3,169 marketers across 16 countries to benchmark the state of AI adoption in advertising. The findings reveal a stark disconnect between enthusiasm and capability. While adoption is rising fast, marketers are signaling uneasiness in how best to put AI to work. The report identifies several key barriers holding back marketer confidence. A significant 40% of respondents feel their organization lacks a sufficient understanding of AI and large language models (LLMs). Other major hurdles include a lack of proper training (38%), limitations on data sharing with AI tools (42%), and an inability to track results against the right business goals (44%). The data shows that even as marketers experiment with generative AI for tasks like social media management (40%), marketing automation (39%), and customer engagement (38%), the foundational systems and skills required for strategic implementation are lagging. Perhaps most concerning, 38% of both junior and senior marketers report they haven't received proper training on the tools they already have.

Why It Matters:

This report quantifies the unease many in the industry are feeling. The "move fast and break things" approach to AI adoption is creating a significant capabilities debt. Without a concerted effort to invest in training, data infrastructure, and measurement frameworks, the majority of AI's value will remain locked away. The 27-point gap is a clear signal that the industry needs to shift its focus from mere adoption to deep, strategic enablement. As MiQ's Chief Marketing Officer Jordan Bitterman notes, "Usage currently outpaces readiness by 27 percentage points, and we see that as pure opportunity. To close the gap, industry leaders must tap into tools and training."

Read More:
https://www.wearemiq.com/ca/resources/news/confidence-report-launch-2025

TLDR:
The EY 2025 Work Reimagined Survey finds that companies are missing out on up to 40% of potential AI productivity gains due to talent strategy gaps, with 88% of employees using AI but only 12% receiving sufficient training.

Details:

The survey, which polled 15,000 employees and 1,500 employers across 29 countries, reveals a critical disconnect between artificial intelligence adoption and human readiness. Despite 88% of employees reporting that they use AI at work, most are limited to basic tasks like search and summarization. The survey reveals deep-seated anxieties, with 37% of employees worried that over-reliance on AI will erode their skills and expertise, while 64% perceive an increase in their workloads due to pressure to perform. Yet only 12% are receiving sufficient AI training to unlock the full productivity benefits. The research also uncovered a significant retention risk: employees who receive extensive AI training (over 81 hours annually) report an average productivity gain of 14 hours per week—well above the median of eight hours—but these employees are also 55% more likely to leave their organizations, as AI talent is highly sought after and external opportunities outweigh internal promotion cycles. Furthermore, between 23% and 58% of employees across various sectors globally are bringing their own AI solutions to work (shadow AI), despite attempts by employers to offer internal tools.

Why It Matters:

The EY report provides a clear C-suite mandate: investing in AI without a parallel investment in people is a recipe for diminished returns. The 40% productivity loss is a powerful metric that frames talent development not as a cost center, but as a critical driver of ROI. The findings also suggest that companies must rethink their retention strategies for AI-skilled talent, offering not just compensation but also clear career paths and opportunities to apply their expertise. As Kim Billeter, EY Global and EY Americas People Consulting Leader, states, "AI is everywhere—but companies seem to be missing out on its full potential, held back by a gap between adoption and human readiness."

Read More:
https://www.ey.com/en_gl/newsroom/2025/11/ey-survey-reveals-companies-are-missing-out-on-up-to-40-percent-of-ai-productivity-gains-due-to-gaps-in-talent-strategy

TLDR:
Google debuted two new autonomous AI agents—Ads Advisor and Analytics Advisor—powered by Gemini, capable of analyzing marketer data, building entire campaigns autonomously, and providing personalized optimization recommendations in real time.

Details:

Google announced the full availability of two Gemini-powered AI agents designed to help marketers optimize their advertising in real time and more easily track campaign performance. Ads Advisor is embedded directly within the Google Ads console and can analyze a marketer's unique datasets, business goals, landing pages, and campaign performance to provide personalized recommendations. The agent can even build entire campaigns autonomously, acting as what Dan Taylor, Google's VP of Global Ads, describes as "partners that learn from an advertiser's unique datasets." For example, a marketer can ask, "How can I optimize my campaign for back-to-school season?" and receive specific, actionable tips tailored to their business. Analytics Advisor provides similar capabilities for tracking and measurement. This launch follows Google's earlier integration of an AI agent within Chrome to automate marketing tasks, signaling the company's broader push into agentic AI systems.

Why It Matters:

These launches represent a significant step-change in marketing technology, moving from assistive tools to autonomous partners. The rise of agentic systems will force marketers to move up the strategic ladder, focusing less on the "how" of campaign execution and more on the "why" of business strategy. It also raises the stakes on the confidence gap; as platforms become more powerful and autonomous, the need for skilled marketers who can effectively direct, govern, and validate these AI systems becomes even more critical. Google's move signals that the era of AI-assisted marketing is giving way to AI-led marketing.

Read More:
https://www.adweek.com/media/google-ai-agent-ads-analytics-advisor/

TLDR:
At its UnBoxed event, Amazon launched Ads Agent, an AI-powered tool that can draft campaigns, optimize bids, manage targeting across channels, and translate plain-language requests into SQL queries through a conversational interface.

Details:

Amazon is bringing AI to the advertising frontlines with the unveiling of Ads Agent, an AI-powered tool designed to carry out tasks on behalf of humans. The agent works through a conversational chat interface, letting marketers upload media plans, draft campaigns and ad groups, and scale targeting strategies—all without juggling multiple tabs or spreadsheets. For users of Amazon Marketing Cloud, the AI agent can translate plain-language requests into ready-to-run SQL queries, removing the need for a data scientist, according to Kelly MacLean, vice president of Amazon's demand-side platform (DSP). The launch was part of Amazon's broader announcement of new AI advertising tools and a centralized hub called Campaign Manager, signaling the company's commitment to making advertising more accessible and autonomous.

Why It Matters:

Amazon's Ads Agent represents a democratization of sophisticated advertising capabilities. By removing technical barriers like SQL query writing and complex campaign setup, Amazon is making advanced advertising accessible to a broader range of marketers. This is particularly significant given Amazon's dominance in e-commerce and retail media. The conversational interface also signals a broader trend: the future of marketing technology will be less about learning complex software and more about effectively communicating strategic intent to AI systems. For marketers, this means the ability to articulate clear business objectives and validate AI-generated strategies becomes paramount.

Read More:
https://www.adweek.com/media/amazon-ai-ads-agent-campaign-manager/

TLDR:
Unilever shared detailed metrics from its Personal Care division, including 700 million impressions for Dove's AI-powered campaign, 58% time-savings in marketing briefs, and 8% increase in manufacturing efficiency through AI implementation.

Details:

Unilever pulled back the curtain on how AI is transforming its Personal Care business across the entire value chain, from innovation to supply chain optimization. The company's Dove brand used AI to rapidly analyze consumer responses for its 'Change the Compliment' campaign, achieving 700 million impressions and an outstanding 94% positive sentiment in under 30 days across 25 markets with more than 100 pieces of content. The campaign went from insight to execution in just six months. On the operational side, over 75% of office-based Personal Care employees are now regular users of personal AI productivity tools. A Smart Briefing pilot tested by the Closeup marketing teams showed a 14% improvement in brief quality, a 26% boost in satisfaction, and up to 58% time-savings. In manufacturing, AI has contributed to a 12% improvement in identifying potential safety risks at the Aguaí, Brazil factory, while the Hefei, China factory has seen an 8% increase in overall equipment effectiveness (OEE), a 15% reduction in batch cycle time, and up to 20% reduction in wastage.

Why It Matters:

The Unilever case study provides a much-needed roadmap for navigating the confidence gap. Their success is rooted in a holistic approach that goes beyond simply deploying tools. They are building internal capabilities, fostering a culture of experimentation, and relentlessly focusing on measurable business outcomes. The breadth of their implementation—from marketing and R&D to manufacturing and in-store execution—demonstrates that AI's value extends far beyond content creation and campaign optimization. This is enterprise AI at scale, and it's delivering tangible results.

Read More:
https://www.unilever.com/news/news-search/2025/how-ai-is-transforming-unilevers-personal-care-business/

TLDR:
Coca-Cola's VP of generative AI reveals the company's strategy of securing early access to AI tools, running 20+ incubator projects, and building a global creator ecosystem, resulting in campaigns like Create Real Magic and an 8-minute average engagement with their AI-powered Santa experience.

Details:

At the AI Deciphered conference in New York, Pratik Thakar, Coca-Cola's VP and global head of generative AI, outlined how the 139-year-old beverage giant is using AI to fuel creativity, efficiency, and consumer connection. Thakar's philosophy is simple: "We cannot be ahead of the curve if we wait for the solution." To maintain that edge, Coca-Cola secures early alpha and beta access to tools from tech firms worldwide, allowing them to experiment while tools are still being built. The company has built a global creator-researcher ecosystem made up of independent PhDs, artists, and entrepreneurs, and runs more than 20 incubator projects at any given time with the understanding that "some of them are going to fail, and some are going to take us ahead." Only two people at Coke hold AI titles, with Thakar's role positioned under the CEO's office in the marketing transformation group. Hundreds of associates participate in strategic 6-to-12-month AI assignments. This approach has led to successful campaigns like "Create Real Magic," an AI platform that allowed anyone to generate original Coke-themed artwork, and a "talk to Santa" experience that engaged users for an average of 8 minutes and 20 seconds.

Why It Matters:

Coca-Cola's approach offers a powerful alternative to the traditional corporate AI strategy. Rather than building a large, siloed AI department, they've embedded AI capabilities across the organization and created a culture of experimentation. Their willingness to secure early access to emerging tools and partner with unconventional creators gives them a sustained competitive advantage. The quote from former Coca-Cola CEO Robert Woodruff that Thakar invokes—"The future belongs to the discontented"—captures the mindset required to navigate the AI transformation: a willingness to question the status quo and push for what's next.

Read More:
https://www.campaignlive.com/article/the-future-belongs-discontented-inside-coca-colas-ai-playbook/1939857

TLDR:
A BBC investigation explores the emerging debate around AI-powered ad personalization, highlighting how companies are using LLMs to analyze digital footprints and create hyper-personalized ads, while critics warn of crossing the line from helpful to intrusive.

Details:

The BBC report captures a critical tension in the industry: as AI-powered personalization becomes more sophisticated, will it lead to better, more relevant advertising or simply a new wave of what critics call "creepy slop"? The article highlights the work of companies like Cheil UK, which is partnering with startup Spotlight to use large language models to understand people's online activity and adapt content based on what the AI interprets an individual's personality to be. The technology can mirror how someone talks in terms of tone, phrase, and pace to change the text of an ad accordingly, and insert music and colors to match personality traits. The AI reads what people post on public platforms like Facebook, Instagram, and Reddit, as well as search history and ChatGPT inputs. Brands in retail, consumer electronics, packaged goods, automotive, insurance, and banking are already using the technology. A Northwestern University study found that personalized ChatGPT text was more persuasive than non-personalized ads. However, critics are raising red flags. Alex Calder of AI consultancy Jagged Edge warns that "creepy slop that brags about knowing your intimate details is still slop," while Ivan Mato of brand consultancy Elmwood questions the reliance on a data economy that makes many consumers uncomfortable.

Why It Matters:

This debate gets to the heart of the trust and confidence issue, but from the consumer's perspective. The industry's pursuit of hyper-personalization could easily backfire if it crosses the line from helpful to intrusive. As Cheil UK's CEO Chris Camacho acknowledges, there is a real danger of AI being used to "persuade, influence, and guide people down paths" in unethical ways, particularly in areas like elections and political canvassing. This conversation is a crucial reminder that a successful AI strategy requires not just technical proficiency but also a strong ethical compass and a deep respect for the consumer. The "creepy slop" critique should serve as a warning: personalization without permission and transparency is a recipe for backlash.

Read More:
https://www.bbc.com/news/articles/ckg4y4z169go

TLDR:
Agency holding company Stagwell is partnering with Palantir Technologies to roll out an AI-powered marketing platform called ACOS that uses differential privacy to help enterprises analyze tens of millions of records for audience segmentation, with CEO Mark Penn expecting it to generate "potentially hundreds of millions of dollars in revenue."

Details:

Stagwell announced a broader rollout of its AI-powered marketing platform developed in partnership with Palantir Technologies. The platform, called the "Audience Creative and Optimization System" (ACOS), is already available to select Stagwell clients through its Assembly media arm and will be rolled out to the broader network and clients on an opt-in basis over the next few months. The platform's goal is to enable large enterprises to sift through tens of millions of records to identify, segment, and understand audiences. A key differentiator is its use of differential privacy technology to protect data. The platform will be sold as a standalone offering and could be applied to other business areas including supply chain analysis and regionalization. CEO Mark Penn expects it to become a "significant business" generating "potentially hundreds of millions of dollars in revenue." The announcement comes as Stagwell reported Q3 2025 revenue of $615 million, a 6% increase year-over-year, with $122 million in net new business in Q3 and $472 million over the last 12 months.

Why It Matters:

The Stagwell-Palantir partnership represents a significant bet on the convergence of enterprise data analytics and marketing technology. By leveraging Palantir's sophisticated data analysis capabilities and wrapping them in differential privacy protections, Stagwell is addressing two of the biggest barriers to AI adoption: data complexity and data security. The fact that this is being positioned as a standalone business with revenue expectations in the hundreds of millions signals that agencies see AI platforms not just as service enhancements but as new revenue streams. This could reshape the agency business model, moving from labor-intensive services to technology-enabled solutions.

Read More:
https://www.marketingdive.com/news/stagwell-palantir-ready-broader-rollout-of-ai-powered-marketing-platform/805081/

TLDR:
Alembic, an AI marketing firm that uses causal AI to help companies align brand marketing with sales objectives, raised $145 million in Series B funding at a $645 million valuation, led by Prysm Capital and Accenture, with participation from Jeffrey Katzenberg's WndrCo.

Details:

Alembic announced a $145 million Series B funding round, bringing its valuation to $645 million. The round was led by Prysm Capital and Accenture, with participation from WndrCo (co-founded by Jeffrey Katzenberg) and SLW venture capital. Alembic uses AI to analyze data, helping companies align brand marketing initiatives with sales and business objectives. The company has positioned itself around "causal AI," which goes beyond correlation to understand cause-and-effect relationships in marketing data. WndrCo was also part of Alembic's Series A round and helped secure major clients including Delta and Mars. The funding announcement was earlier reported by the Wall Street Journal and signals strong investor confidence in AI-powered marketing analytics platforms.

Why It Matters:

The $145 million raise and $645 million valuation demonstrate that investors see significant value in AI platforms that can bridge the gap between brand marketing and business outcomes. The involvement of Accenture as both an investor and likely implementation partner suggests that Alembic's technology is being positioned for enterprise deployment at scale. The focus on "causal AI" is particularly noteworthy, as it addresses one of the biggest criticisms of AI in marketing: the tendency to confuse correlation with causation. If Alembic can deliver on the promise of truly understanding what drives business results, it could reshape how marketers allocate budgets and measure success.

Read More:
https://www.adweek.com/media/alembic-series-b-145-million-jeffrey-katzenberg-wndrco-prysm-accenture/

TLDR:
billups, the world's largest independent OOH technology company, launched audrai, the first AI-powered agentic system for out-of-home advertising, delivering 50% workflow acceleration and reducing complex geospatial mapping from 1-2 days to under 2 minutes.

Details:

billups announced the launch of audrai, described as the first AI-powered agentic system built to optimize planning and performance for out-of-home (OOH) advertising. Early deployment results have been impressive: up to a 50% increase in workflow acceleration, complex geospatial mapping reduced from 1-2 days to under 2 minutes, campaign planning cycles compressed from days to hours, and instant market, audience, and client strategy generation. Unlike generic AI tools, audrai is built to understand OOH from the ground up, bringing together automated audience planning, creative performance, A/B testing, and predictive insights. The company's technology-first approach has fueled expansion across more than 20 countries, with particularly strong momentum in the UK and EMEA markets. The UK team grew 40% year-over-year in 2025, adding 78 new hires, while the company added more than 20 new clients including Oatly, Just Eat, and Revolut, and won 21 major industry awards for client campaigns. Looking ahead, billups plans to expand its platform capabilities throughout 2026 with enhanced predictive modeling, expanded integration with digital marketing ecosystems, advanced creative optimization, and real-time audience measurement.

Why It Matters:

The billups announcement is significant for two reasons. First, it demonstrates that AI's impact on marketing extends far beyond digital channels. OOH has historically been one of the most difficult channels to measure and optimize, and audrai's ability to compress planning cycles and enable real-time optimization could fundamentally change how brands approach outdoor advertising. Second, the concrete performance metrics—50% workflow acceleration, mapping tasks reduced from days to minutes—provide a tangible benchmark for what "agentic AI" can deliver in a specific vertical. This is not incremental improvement; it's a step-change in capability.

Read More:
https://www.businesswire.com/news/home/20251114408797/en/billups-Launches-AI-Powered-Agentic-System-for-Out-of-Home-Advertising

TLDR:
Harvard Business Review explores how generative AI is enabling the creation of "synthetic personas" and "digital twins" for market research, with Columbia Business School achieving 88% relative accuracy but only replicating about half of experimental effects, leading researchers to conclude the technology is "not fully ready for prime time yet."

Details:

A new Harvard Business Review article examines how generative AI is rapidly reshaping market research by enabling the creation of "synthetic personas" and "digital twins"—AI-generated proxies that simulate real consumer responses to questions and surveys. The article outlines two approaches: top-down (creating a composite persona for a segment) and bottom-up (creating a "silicon sample" of varied personas). The Columbia Business School Digital Twins Initiative created over 2,000 digital twins and achieved 88% relative accuracy in replicating survey responses. However, when tested across 17 behavioral economics experiments, the digital twins only replicated about half of the experimental effects. The technology shows limitations in political domains, tends to provide more socially desirable answers, and exhibits pro-human and pro-technology bias. It performs more accurately for educated, higher-income, and ideologically moderate participants. Despite these limitations, major venture capital firms including Andreessen Horowitz and Foundation Capital have published investment theses on how generative AI will transform the $140 billion market research industry. The Columbia Business School team's conclusion: the technology is "not fully ready for prime time yet."

Why It Matters:

This article provides a much-needed dose of realism in the AI hype cycle. While the promise of synthetic personas and digital twins is compelling—imagine being able to test concepts and messages instantly without recruiting participants—the current limitations are significant. The 88% accuracy rate sounds impressive until you realize that digital twins only replicated half of experimental effects, meaning they could lead to fundamentally wrong conclusions about consumer behavior. The biases identified (pro-human, pro-technology, more socially desirable answers) are particularly concerning for marketers, as they could systematically skew research findings. This is a reminder that AI is a powerful tool, but it's not a replacement for human insight and real-world validation.

Read More:
https://hbr.org/2025/11/the-ai-tools-that-are-transforming-market-research