72% of marketers plan more AI use but only 45% feel ready

Programmatic media partner MiQ released findings on November 11, 2025, showing a substantial disconnect between artificial intelligence adoption intentions and actual implementation confidence across the advertising industry. The global survey reveals 72% of marketers plan to apply AI in more ways over the next 12 months, yet only 45% feel confident in their ability to apply it successfully.

The first edition of "The AI Confidence Curve" report surveyed 3,169 marketers across 16 countries in September 2025, according to MiQ. The research examined usage and readiness levels around different aspects of AI in advertising, painting a picture of an industry eager to advance while still developing the skills and systems needed to achieve AI's potential.

"We discovered that most marketers are bunched together at the early stages of a confidence curve," said Jordan Bitterman, Chief Marketing Officer at MiQ. The 27-percentage-point gap between usage and readiness represents what the company characterizes as "pure opportunity" requiring investment in tools and training.

Current AI applications reveal adoption patterns

Marketers currently apply AI most comfortably to social media management at 40%, marketing automation at 39%, and customer engagement at 38%, according to the survey. These areas align with tasks where generative AI tools like ChatGPT prove most useful. The data shows 66% of respondents currently use AI tools on most or all projects.

Ad campaign management reached 35% adoption, while content creation and ad creative design/optimization each hit 32%. Visual design applications stood at 37%, with SEO and content optimization at 33%. The relatively high adoption rates across multiple functions demonstrate AI integration into various marketing workflows.

Geographic variations in confidence levels show Canada, Australia, and Japan leading in positive sentiment toward AI solutions. China, Mexico, and Thailand showed lower confidence levels, attributed to factors including cultural prevalence of AI and available tools.

Knowledge gaps impede confident implementation

Among marketers reporting low confidence, 40% cite their organization's insufficient understanding of AI or large language models. This knowledge deficit stems from inadequate training and understanding that pushes marketers toward simplified, general AI tools rather than powerful bespoke solutions designed for specific advertising applications.

The research identifies three primary factors constraining marketer confidence. First, 38% cite lack of training on AI tools. Second, 42% mention limitations on sharing data with their chosen tools. Third, 44% list inability to track results against appropriate goals as a significant barrier.

Many marketers rely on proxy metrics like clicks or web traffic that fail to capture AI's broader business impact, according to the findings. Nearly two in five senior marketing professionals admit they're still building the education, measurement, and workflow systems needed to use AI confidently and consistently. That same percentage of both junior and senior marketers report not receiving proper training on tools they already have.

Measurement confidence shows mixed results

The survey reveals 49% of marketers feel confident in their knowledge of AI technology. However, only 45% express full confidence in their ability to use AI solutions to achieve operational efficiencies, demonstrating that understanding technology doesn't necessarily translate to effective application.

For specific tasks, confidence levels vary. Marketers show 49% confidence in their team's ability to use AI to create useful insights and intelligence, while 43% feel confident about using AI to optimize channel selection. Confidence in using AI to optimize performance against marketing KPIs stands at 40%, with the same percentage reporting confidence in their company's internal AI-based solutions.

Nearly half of marketers find AI makes measuring cookieless environments manageable, while 44% feel confident knowing how targeting and creative drive performance. The research shows 43% of marketers believe they have effective measurement in place for every part of the funnel.

Senior marketers demonstrate higher confidence than junior professionals. Some 47% of senior marketers feel confident in their teams' ability to optimize performance, compared to 36% of junior professionals. This pattern extends to confidence in internal and external solutions.

Data access emerges as critical challenge

The inability to share client or brand data with AI tools represents a fundamental challenge affecting over 40% of respondents. When AI cannot ingest brand-specific data, it cannot deliver customized optimization and insights. This limitation forces marketers toward generic tools rather than specialized solutions designed for advertising applications.

Among the 37% who report struggling to use AI for creating insights and intelligence, data access restrictions rank as the primary concern. Without first-party data integration, generic AI tools produce generic recommendations that fail to account for specific business contexts, campaign histories, or unique audience characteristics.

The research suggests reliable third-party data sources can partially address first-party data limitations. However, the quality gap between generic recommendations and data-driven customization remains significant.

Amazon launched AI agent capabilities earlier in November for automated campaign management across Amazon Marketing Cloud and Multimedia Solutions with Amazon DSP. StackAdapt introduced its Ivy AI assistant in July 2025, processing natural language queries for programmatic advertising. These developments demonstrate the industry's movement toward accessible AI interfaces.

Adoption plans reveal confident optimism

Looking forward to the next 12 months, 75% of marketers who feel confident achieving results plan to increase AI usage. Half of this group report having appropriate goals in place to track performance. For the 41% confident in their team's ability to optimize against results, data sharing remains the top concern with training following closely.

Primary success metrics show 49% of marketers use engagement metrics including click-through rates, engagement, and email opens. Web traffic follows at 46%, with conversions at 30%. Financial metrics like ROI, ROAS, and CPA reach 44% adoption. Customer retention stands at 36%, while brand sentiment reaches 34%.

The survey reveals marketers tracking different metrics show similar confidence levels about driving results. Whether focusing on click-through rates or brand sentiment, marketers demonstrate comparable capability optimization. This suggests AI-powered measurement tools are beginning to make traditionally difficult metrics more accessible.

Marketers who view consumers through the lens of a purchase journey rather than channels find it easier to generate meaningful insights with AI, according to the findings. Some 73% of respondents now plan for the consumer journey rather than organizing strategies around channels.

Training deficits limit AI effectiveness

Even marketers fully confident in their team's ability to drive marketing outcomes and optimize performance identify training as a concern. More than one in ten from this confident group cite lack of training as a key barrier to increased effectiveness.

The speed of AI development creates ongoing challenges as marketers must track new models, new tools, and constant changes. Custom-built internal tools often lack formal training programs, leaving teams to develop expertise through trial and error. This approach proves inefficient and prevents teams from accessing AI's full capabilities.

The research indicates 44% of marketers feel their organization doesn't understand AI or LLMs well enough, directly contributing to low confidence with insights and intelligence applications. Better general understanding of AI enables more effective specific applications across advertising functions.

IAB Europe reported in September that 60% of companies provide AI education to marketing personnel, with two-thirds expressing interest in industry association guidelines. DoubleVerify found in August that marketers spend 10 hours weekly on manual campaign optimization tasks including bid modifications and budget allocations.

Platform fragmentation complicates adoption

AI solutions that don't quickly integrate into existing businesses, match current workflows, and ingest brand data face rejection from marketers overwhelmed by technical complexity. The gap between AI capability and practical implementation remains substantial for many organizations.

Generic tools like ChatGPT offer accessibility but lack the specialized features required for sophisticated advertising applications. Bespoke solutions built for advertising provide advanced capabilities but require technical expertise and data integration that many marketing teams cannot provide.

The research methodology partnered with Censuswide to survey marketers from agencies and brands across every level of job title and seniority. Countries included the United States, United Kingdom, Canada, Mexico, Brazil, Colombia, France, Germany, Spain, Italy, Switzerland, United Arab Emirates, Saudi Arabia, China, India, Japan, Thailand, Australia, and Singapore.

Industry implications for marketing operations

The 27-point confidence gap carries significant implications for advertising technology adoption and marketing effectiveness. Organizations face decisions about training investments, tool selection, and workflow redesign as AI becomes increasingly central to campaign management.

The path forward requires multiple coordinated efforts, according to the report. First, adopting partner-agnostic solutions that integrate multiple platforms eliminates data silos and delivers more accurate insights. Second, integrating AI into performance measurement by tying systems directly to campaign KPIs enables real-time evaluation and links adoption to business impact.

Third, investing in AI literacy across teams through ongoing training builds competence that drives confidence. With 44% citing internal knowledge gaps, embedding AI education into everyday marketing practice becomes essential. Fourth, preserving human expertise ensures experienced marketers apply judgment, maintain accountability, and validate recommendations before implementation.

"Every marketer is trying to find the balance between learning and leading with AI," Bitterman stated. "The ones who advance fastest will treat confidence as a capability, something built every day through connection, curiosity, and collaboration."

McKinsey analysis in July showed $1.1 billion in equity investment flowed into agentic AI during 2024, with job postings related to the technology increasing 985% from 2023 to 2024. The investment patterns highlight complex relationships between technology maturity and market adoption as organizations face scaling challenges from compute-intensive workloads.

The findings arrive as major platforms accelerate AI integration. Google unveiled comprehensive AI advertising capabilities at Think Week in September, including agentic advisors for Google Ads, Analytics, and cross-platform marketing. Amazon added AI agent capabilities for Marketing Cloud analytics queries, translating business questions into executable database queries through conversational prompts.

The advertising technology landscape continues shifting toward intelligent automation and natural language interfaces. However, the MiQ research demonstrates that technological capability alone cannot drive adoption. Confidence built through training, data access, appropriate measurement frameworks, and human expertise determines whether AI delivers on its potential or remains an underutilized tool.

Organizations treating confidence as a capability requiring deliberate investment in education, systems, and processes position themselves to capture AI's benefits. Those that deploy tools without corresponding investments in enablement risk joining the organizations reporting zero returns on substantial AI expenditures.

Timeline

• September 2025: MiQ partnered with Censuswide to survey 3,169 marketers across 16 countries about AI usage and confidence levels
• September 2025: IAB Europe revealed 85% AI adoption rate across digital advertising with 60% providing AI education
• November 11, 2025: MiQ released first edition of "The AI Confidence Curve" report showing 27-point gap between usage and readiness
• November 11, 2025: Amazon announced AI agent for automated campaign management across Marketing Cloud and DSP
• November 2025: Industry leaders discussed AI's role in making programmatic platforms more accessible through natural language interfaces

Summary

Who: MiQ, a global programmatic media partner headquartered in London with 21 offices across North America, Europe, APAC, and Latin America, conducted the research with Chief Marketing Officer Jordan Bitterman leading the analysis. Respondents included 3,169 marketers from agencies and brands across all seniority levels in 16 countries.

What: The research reveals a 27-percentage-point gap between AI adoption intentions (72% planning increased usage) and implementation confidence (45% feeling capable of successful application). Primary barriers include insufficient training (38%), data sharing restrictions (42%), and inability to track appropriate goals (44%). Current AI applications focus on social media management (40%), marketing automation (39%), and customer engagement (38%).

When: The survey occurred in September 2025 through partnership with Censuswide, with results released November 11, 2025, as the first edition of "The AI Confidence Curve" report examining the advertising industry's current position in AI adoption.

Where: The global survey spanned 16 countries including the United States, United Kingdom, Canada, Mexico, Brazil, Colombia, France, Germany, Spain, Italy, Switzerland, United Arab Emirates, Saudi Arabia, China, India, Japan, Thailand, Australia, and Singapore, representing diverse geographic markets and cultural contexts.

Why: The research matters because it quantifies the disconnect between AI investment momentum and practical implementation capability across advertising. With 44% of marketers citing organizational knowledge gaps and 42% unable to share data with AI tools, the findings identify specific barriers preventing the industry from realizing AI's potential despite widespread recognition of its importance and substantial planned investments.