Observed Signal · Jun 18, 2026 · Survey / Market Research · Source: persoenlich.com News · Impact: 2/5 · Sentiment: Positive
AI Now Embedded in Everyday Marketing Work
A non-representative survey of 114 German‑Swiss marketing professionals conducted by Zurich consultant Monika Liechti (15 May–11 June 2026) finds AI broadly established in marketing workflows. Only one respondent reported deliberately not using AI. Top use cases are text generation (92%), strategy and concept development (80%) and image generation (71%); 88% of users cite time savings for routine tasks as the main benefit. The biggest obstacles to deeper adoption are security concerns (43%) and data‑protection worries (39%), ahead of missing know‑how (31%) and limited budgets (12%). Mid‑sized companies (50–249 employees) show particularly high security concerns (65%) and very low use of campaign automation (6%). The sample skews to larger firms (54% with 250+ employees) and industry affiliation could not be analysed due to a technical error. Liechti & Co provides AI consulting for marketing teams.
Shows widespread AI adoption among marketing professionals and flags security/privacy as primary barriers—useful directional insight for MarTech vendors and agencies but limited by non‑representative sample and regional scope.
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Key Takeaways & Evidence Grounding
- Monika Liechti surveyed 114 German‑Swiss marketing professionals between 15 May and 11 June 2026.
- Only 1 of 114 respondents stated they consciously do not use AI.
- Most common AI applications: text creation 92%, strategy/conception 80%, image generation 71%.
- Primary benefit reported: 88% of users cite time savings on routine tasks.
- Biggest barriers: security concerns 43% and data‑protection concerns 39%; in mid‑sized companies (50–249 employees) security concerns reach 65% and campaign automation use is 6%.
Connected Companies & Entities
1 Entity mappedRelated Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
85% of Marketing AI Projects Fail — Not Due to Tech
A Marketing Tech Monitor 2026 survey of roughly 1,600 decision-makers in Germany, Austria and Switzerland shows strong interest in AI—many CMOs and digital leaders call it a strategic priority though only 30% rank it first. Common use cases are content management (87%), customer-communication analysis (77%) and conversational AI/chatbots (71%). External research (Stanford Digital Economy Lab, Harvard) and the DACH survey estimate 70–85% of AI projects miss goals, implying over €21 billion in sunk IT costs in 2026. Root causes include insufficient functional/domain understanding (56%), weak process foundations, fragmented pilots and a focus on automation rather than transformation. About 45% of firms remain in reactive pilot mode and ~11% are high maturity; the report recommends end-to-end processes, robust data/context architectures and organizational change to scale AI.
AI in Marketing: Germany Stuck in Pilot Mode?
An article published on July 8, 2026 on HORIZONT by Helmut van Rinsum reviews recent reports and surveys showing that German marketers are investing heavily in artificial intelligence but frequently fail to capture the expected business value. The piece cites studies such as the Marketing Tech Monitor and points to an "investment paradox" where high spending on AI tools does not automatically translate into measurable value, suggesting gaps in governance, operational adoption and strategic integration of AI within marketing organizations.
Marketers See AI Benefits; Trust Limits Agentic AI
Digiday+ Research (excerpt) summarizes a survey of 142 brand and agency professionals (conducted Q4 2025) showing widespread embedding of AI across marketing workflows but persistent barriers to broader adoption. Generative AI has higher adoption than predictive AI, with generative tools most used for creative production (82%), marketing (81%) and external/internal communications (75%/56%). Predictive AI is most commonly applied to measurement and KPI analysis (48%). More than half of respondents (54%) said their companies do not use agentic AI; interviewees and case studies (Unilever, Kroger, Monks) illustrate benefits but highlight trust, governance, data access and technical complexity as obstacles to agentic AI adoption.
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