On November 11, 2025, programmatic media partner MiQ released significant findings that highlight a pronounced disparity in the advertising industry regarding the intentions and confidence surrounding the adoption of artificial intelligence (AI). According to the survey, which involved 3,169 marketers across 16 countries, a substantial 72% of respondents expressed plans to increase their use of AI in the coming year. However, only 45% reported feeling confident in their ability to implement AI solutions effectively.
Current AI Applications and Adoption Trends
The inaugural edition of “The AI Confidence Curve” report, conducted in September 2025, paints a picture of an eager industry still grappling with the necessary skills and systems to harness AI fully. Notably, the survey revealed that marketers are most comfortable applying AI to social media management (40%), followed closely by marketing automation (39%) and customer engagement (38%). Overall, 66% of respondents indicated that they use AI tools in most or all of their projects.
However, areas such as ad campaign management (35%) and content creation (32%) demonstrate a slower adoption rate. Geographic variations surfaced in the survey, with Canada, Australia, and Japan showing the highest confidence in AI solutions, while countries like China, Mexico, and Thailand lagged behind, largely due to cultural factors and the availability of advanced tools.
Challenges to Implementation Confidence
Among those marketers who reported low confidence, significant barriers emerged. Notably, 40% attributed their lack of confidence to insufficient organizational knowledge of AI and large language models. This gap is exacerbated by inadequate training, leading many marketers to rely on simplified, generic AI tools rather than bespoke solutions tailored for specific advertising applications. The research identified three primary constraints: a lack of training on AI tools (38%), limitations on data-sharing capabilities (42%), and difficulties in tracking performance against relevant goals (44%).
As a result, nearly two in five marketing professionals admitted they were still developing the necessary education, measurement, and workflow systems to deploy AI effectively. Many are still relying on proxy metrics, such as clicks or web traffic, that do not capture AI’s broader business impact.
Mixed Results in Measurement Confidence
While 49% of marketers expressed confidence in their understanding of AI technology, only 45% felt assured in using AI solutions to achieve operational efficiencies. Confidence levels varied for specific tasks, with 49% feeling capable of generating useful insights and 43% confident about optimizing channel selection. Interestingly, 40% reported confidence in using AI to optimize performance against marketing KPIs, with an equal percentage expressing confidence in their company’s internal AI solutions.
Senior marketers demonstrated higher confidence levels than their junior counterparts. For example, 47% of senior marketers felt confident in their teams’ ability to optimize performance, compared to 36% of junior professionals.
Data Access as a Critical Challenge
The inability to share client or brand data with AI tools represents a significant challenge, affecting over 40% of respondents. This restriction hampers AI’s capability to deliver customized insights and optimizations, pushing marketers toward generic solutions that fail to consider specific business contexts. Among the 37% of marketers who struggled to use AI for generating insights, data access restrictions were identified as the primary concern.
Despite these challenges, advancements in AI are evident, with companies like Amazon launching new AI agent capabilities for automated campaign management earlier this month, and StackAdapt introducing its Ivy AI assistant. These developments reflect a shift toward more accessible AI interfaces in the marketing landscape.
Looking Ahead: Optimism Coupled with Training Deficits
As marketers contemplate the next 12 months, 75% of those confident in achieving results plan to amplify their AI usage. Half of this group reports having established performance goals, while data-sharing concerns and training deficits remain top priorities. Metrics such as engagement rates, web traffic, and conversions are being tracked, indicating a diversified approach to measuring AI effectiveness.
However, even among confident marketers, training deficits persist as a barrier to maximizing AI effectiveness. The swift pace of AI development further complicates matters, necessitating ongoing education and adaptation to new tools and models. The survey underscores a pressing need for organizations to invest in AI literacy to foster an environment where teams can confidently apply AI innovations.
In summary, the findings from MiQ underline a crucial opportunity for the advertising industry: bridging the gap between AI adoption intentions and practical implementation. The journey toward effective AI integration requires focused investments in training, data access, and robust measurement frameworks—essential steps to ensure that AI becomes a powerful asset rather than an underutilized tool.
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