Market research has long required specialized skills, from questionnaire design and sampling to data interpretation. aytm (Ask Your Target Market) is trying to remove much of that complexity with the launch of the Bridge, an AI-native insights operating system designed to let marketers, product teams and executives move from a business question to research-backed recommendations through a conversational workflow.

The Bridge, unveiled in Denver on October 4 ahead of TMRE and Content Marketing World 2026, is built around a straightforward proposition: organizations should be able to use their consumer-insights infrastructure without every employee needing to understand market-research methodology.

At the center of the platform is Skipper, an AI agent that interprets questions, searches an organization's existing research and determines whether new consumer research is necessary. aytm describes the system as a way to connect a business question with an answer that teams can act on, rather than simply providing another generative-AI interface for summarizing documents.

That distinction matters. Enterprise organizations often have years of research distributed across presentation decks, databases and other systems. Finding an existing answer can be almost as difficult as commissioning a new study. The Bridge attempts to make that accumulated research an active knowledge base.

When relevant evidence already exists, Skipper can surface it using the organization's previous research and respondent-backed data. If the platform determines that a new study is required, it can develop the research plan, including objectives, audience, sample size and quality controls. Users see expected pricing and timing before launching the study, while human review remains part of the process.

aytm also says its data-quality systems identify questionable respondents and automatically top up samples when necessary. Once fieldwork ends, the platform produces recommendations connected to the underlying findings and feeds the resulting knowledge back into the organization's research history.

In practical terms, the Bridge is attempting to collapse several traditionally separate stages of market research automation into one workflow: question formulation, research discovery, survey design, sample management, data collection, analysis and recommendation generation.

The approach places aytm in an increasingly crowded category of AI-assisted research tools. Competitors and adjacent platforms are using generative AI for survey creation, qualitative analysis, synthetic research assistance and insight summarization. The Bridge's more distinctive proposition is the combination of an AI research agent with an existing consumer-research platform and respondent network.

That could make the system more useful than a general-purpose AI chatbot for questions that require primary research. A model such as ChatGPT can synthesize available information, but it cannot by itself recruit a representative audience for a new survey or establish whether an organization's proprietary research already answers a question.

The human-review component is equally important. Research decisions involving sampling, methodology and interpretation can have material consequences for product launches and marketing strategy. Automating the workflow without removing accountability could therefore be more commercially viable than positioning AI as a completely autonomous researcher.

The timing also reflects broader enterprise adoption of AI. McKinsey estimates that 71% of organizations surveyed were regularly using generative AI in at least one business function in 2025, with marketing and sales among the areas seeing particularly broad adoption.

Gartner's research points to another reason research platforms need to prioritize reliability. Its 2026 survey found that 61% of consumers frequently question whether information used for everyday decisions is reliable, while 68% frequently question whether the content they encounter is real.

For marketing teams, that makes the provenance of insights increasingly important. AI-generated recommendations are useful only when teams can understand what evidence supports them.

The Bridge is currently in early access. Its larger test will come as aytm expands availability and organizations determine whether an AI-native research workflow can deliver faster answers without sacrificing methodological rigor.

Market Landscape

The market-research industry is moving from AI-assisted analysis toward agentic research workflows. Instead of using AI only after data has been collected, emerging platforms are putting AI earlier in the process—interpreting research questions, selecting methodologies and coordinating data collection.

That aligns with a broader enterprise shift toward AI agents. Gartner forecasts that the market for standalone AI agents and assistants across consumer and enterprise use cases will grow 13-fold between 2025 and 2030.

The competitive question for aytm is therefore not simply whether Skipper can automate research tasks. It is whether the combination of proprietary research data, respondent access, quality controls and AI orchestration produces more dependable insights than general-purpose AI tools or point solutions for survey creation and analysis.

That distinction could become important as Salesforce, Microsoft, Google and Adobe continue embedding AI into broader customer, marketing and analytics ecosystems. Research platforms will increasingly compete not only with specialist market-research vendors but also with AI capabilities embedded throughout the enterprise MarTech stack.

Strategic Outlook

The Bridge represents a shift in the role of consumer-insights technology—from a tool used primarily by researchers to an organizational intelligence layer accessible to non-research specialists.

If the model works, a brand manager could ask a question in natural language, discover what the company already knows, commission new research when necessary and receive an evidence-linked recommendation without navigating several specialist systems.

That does not eliminate the need for researchers. Instead, it could change where their expertise is applied: methodology oversight, interpretation, strategic framing and quality assurance rather than repetitive operational work.

The bigger opportunity is turning research from an occasional project into an always-available enterprise capability.

Top Insights

• aytm's Bridge turns market research into a conversational workflow, potentially giving marketers and executives faster access to respondent-backed insights without specialized research training.
• Skipper connects existing research with new studies, addressing a common enterprise problem: valuable consumer knowledge remains fragmented across decks, databases and research systems.
• Human review remains central to the workflow, giving enterprises a control layer as AI begins automating sampling, study design, analysis and recommendations.
• The platform competes beyond traditional research software, facing pressure from AI survey tools, analytics platforms and increasingly intelligent enterprise MarTech ecosystems.
• AI-native research could broaden insight access, allowing product, marketing and executive teams to use consumer intelligence without turning every business question into a formal research project.

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