Observed Signal · Aug 18, 2026 · Podcast Episode · Source: Digiday · Impact: 2/5 · Sentiment: Neutral
Marketers Adopt AI; Guardrails and Job Concerns Persist
Marketers and agencies are increasingly using AI across marketing workflows to speed brainstorms, scale creative ideas and support business wins, but formal guardrails remain fluid. Agencies are pushing company-wide AI adoption without universal rules separating machine output from human creativity. 72andSunny’s global CEO Evin Shutt discussed the agency’s evolving, conversational approach on the Digiday Podcast. The rise of AI-created roles — such as AI art director, prompt engineer and chief AI officer — coexists with concerns about AI replacing entry-level positions, a point raised by recent graduate Isaiah Clay. The piece is published as a Digiday podcast article and reflects industry adoption trends and workforce implications.
Reports on widespread AI adoption and workforce impacts in marketing and agencies—useful trend information but not a major platform policy change or technical release.
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Key Takeaways & Evidence Grounding
- Article published on August 18, 2026 by Kimeko McCoy on Digiday.
- Marketers are increasingly handing over parts of the marketing process to AI tools and pushing company-wide AI adoption.
- Evin Shutt, global CEO at 72andSunny, discussed the agency’s approach to AI on the Digiday Podcast.
- New roles such as AI art director, prompt engineer and chief AI officer have appeared, while concerns exist that AI may replace some entry-level marketing jobs (raised by Isaiah Clay).
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Marketers Embrace AI, Avoid AI for Media Buying
A Digiday survey of more than 100 marketers shows widespread adoption of AI for low-stakes tasks—data analysis and content creation—while few marketers trust AI to make media-buying decisions. Among marketers using AI for social campaigns, about two-thirds use it for data analysis, 57% for content creation, and only 32% to buy ad placements. The roundup also highlights agency M&A activity aimed at creator and youth marketing: Havas acquired Archrival (folding it into Havas Play) and Accenture Song bought creator-focused agency Whalar. LinkedIn is planning creator monetization tools in its 2027 fiscal year roadmap. Separately, OpenAI announced a data partnership with LiveRamp around LiveRamp’s conversion API hub and is reported to be in talks with NVIDIA about a very large Ohio data center. Disney promoted Brette Lipari to VP of advertising sales.
Agencies Say AI Adoption Outpaces Advertisers
Agency leaders at Cannes Lions told Digiday that agencies are further advanced in AI adoption than their brand clients. Executives described agencies building sophisticated internal AI tooling and platforms while many CMOs remain constrained by governance, procurement, legal sign-off and static marketing budgets. One agency executive said an agency AI platform has grown revenue triple digits for five consecutive quarters, but clients fall into four camps—from active builders to outright dismissers—leaving a widening gap. Analysts say advertisers are demanding transparency about where AI is used. The reporting highlights tension between agency capability and advertiser readiness, with debate over whether agencies are genuinely ahead or using the narrative to justify fees.
Marketers Increase AI Use; Technical Skills Lag
Digiday+ Research, based on a survey of 142 brand and agency professionals and interviews with marketing and tech executives, finds marketers’ adoption of AI has climbed sharply (from 44% in 2022 to 86% in 2025) but organizational tech skills, upskilling and strategic use lag behind tool adoption. The report notes many companies favor out-of-the-box AI tools (85% of respondents), while fewer build on existing LLMs (40%) or train proprietary LLMs (19%). Firms have appointed chief AI officers (brands such as General Motors, Mastercard and ZocDoc; agencies including Golin, Luckie & Co. and Horizon Media). Interviewees flagged economic concerns about GPU/TPU infrastructure costs, gaps between baseline user familiarity and advanced internal usage, and growing platform interoperability (e.g., Adobe integrating Google models and Google Vertex AI).
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