Knotch Study: Embracing Agentic AI 

Current State: AI Adoption is High, But Commitment is Shallow

Knotch surveyed 302 marketers across industries in Spring 2025 and found that while 82% are using AI, most brands are still stuck in a strategic limbo—experimenting with tools but a little hesitant to embrace full Agentic AI systems that can make decisions autonomously.

Agentic AI refers to artificial intelligence systems that can autonomously perceive, decide, and act on behalf of users or organizations to achieve specified goals without constant human intervention, unlike chatbots, which primarily serve as reactive interfaces that require constant prompting and user direction.

Key Findings:

• Efficiency rules: 60%+ cite time savings and strategic uplift as AI’s biggest value.
• Content is king: Most AI use is in text and content optimization; only ~40% use it for creative generation.
• Agentic AI pain points align with familiar challenges: scaling content, synthesizing insights, and performance tracking.
• Trust is the choke point: 60% of marketers don’t trust Agentic AI’s accuracy or decision-making.

Strategic Stalemate: Stuck Between Legacy Systems and Autonomous Potential

57% believe they have the right mix of tools and talent.  Only 30% need better AI capabilities and an almost matching 28% need more human expertise.  This reflects the transitional moment that we live in.  Organizations are caught in a strategic ambiguity between relying on legacy human systems and not yet fully embracing AI.

Over 60% of Respondents agree that the primary benefit of AI creates time savings and efficiencies, allowing them to be more strategic.

The Work AI Actually Does: Content Optimization and Efficiency Gains

Use cases for AI in the content arena are primarily in the written text arena - 58% using AI for content optimization, and over 40% creating more quality and targeted content.    37% are using AI for image generation.

Respondents believe this allows more targeted content to be created. Both quality and quantity of content rises.

The agentic opportunities appear to align with known painpoints of creating content at scale, keeping track of performance and consolidating analytics across multiple platforms and sources.

Respondents are specifically seeking Agentic AI support for:

• Creating quality content at scale
• SEO keyword research
• Integrated marketing performance dashboards
• Audience and competitive research

The Trust Factor: What’s Holding Back Agentic AI Adoption

Agentic AI has a nagging trust issue.  60% of respondents do not trust its accuracy and 54% are concerned about the accuracy of its decision making. 

Knotch’s extensive conversations with a wide range of industry stakeholders point to the opaque, black-box nature of agentic AI systems as the likely cause of the lack of trust. 

Many systems operate with minimal transparency, making it difficult for users to understand how decisions are being made, what data is being prioritized, or which objectives are driving their behavior.  The systems that address this and offer clarity on how they work will likely have a strategic advantage.

The Agentic Shift: From Tool to Colleague

The path forward towards Agentic AI suggests a remarkable change in approach to finding success.

Marketing becomes orchestration, not execution.  Marketers will set high-level goals (“increase Gen Z brand affinity in LATAM”) and agents will handle the grunt work — from research to creative development to media buying to reporting. Execution becomes near-instantaneous, iterative, and deeply contextual.

Campaigns become continuous, adaptive flows.  Agentic AI doesn’t think in quarters or campaigns. It’s always-on, always-optimizing. Marketing becomes a living system rather than a series of bursts.

Individualization becomes the norm.  Agents can operate at massive scale but think locally — personalizing messaging not just by segment, but by individual, moment, and mood. 

New layers of intelligence emerge. Agentic systems can monitor competitors, detect weak signals in culture, test and learn in real time — giving marketers strategic foresight that was previously impossible.

Performance measurement and funding needs to be re-imagined in a move away from lagging indicators to always-on measurement: Performance becomes real-time, adaptive, and responsive to micro-signals (audience behavior, cultural trends, competitive shifts).  The measurement system becomes a learning system.

‍Big brands are uniquely vulnerable in an agentic AI world because the very things that made them dominant — scale, consistency, control, and process — become liabilities when the game changes.  Big brands have resisted hyper personalization because of the risk to brand consistency.  

The mandate is clear for the marketers to create a roadmap to move beyond experimentation to proactive design with Agentic AI as its new colleague:

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Published May 29, 2025