Building an artificial society is a purposeful process of constructing a synthetic population that accurately represents the real-world stakeholders relevant to a specific decision. Each society — a network of 300 to over 5,000 interconnected AI personas — is custom-built for every engagement, ensuring that the personas, their belief systems, and their social dynamics reflect the actual audience the organisation needs to understand. Artificial Societies has built a scalable automated system that handles this process efficiently, incorporating demographic data, organisational targeting, and first-party data without months of heavy lifting from the customer's side.
Organisations can define their artificial society in several ways, which can be combined. Through demographic specifications — age, gender, location, income, education — similar to how a traditional panel would be recruited. Through organisational and professional targeting — specifying lists of companies, industries, and job titles to construct a society of, for example, technology executives or Washington D.C. policymakers. Through first-party data — incorporating the organisation's own CRM records, existing qualitative research, quantitative survey data, or proprietary audience intelligence. This flexibility enables access to high-value audiences and stakeholders that matter most to the decision at hand.
Each persona is constructed from real-world social behavior data — publicly available expressions, engagement patterns, and interpersonal dynamics that reveal how real people think, feel, and influence each other. This data is anonymized and processed through a proprietary behavioral analysis system that creates an internally coherent belief system and personality for each persona. Where clients provide first-party qualitative or quantitative data, this is incorporated to further calibrate personas to the specific audience. The result is not a demographic archetype but a nuanced individual with consistent attitudes across topics — a persona that responds to questions in ways that reflect a unified worldview grounded in real human behavior.
Once individual personas are constructed, they are organised within a social graph that models influence relationships, community structures, and opinion dynamics. A proprietary multi-agent orchestration system simulates how opinions form and spread through social influence — the conformity pressures, network effects, and community dynamics that shape real human societies. This social network simulation is what allows artificial societies to capture the full diversity of opinion distributions, including emergent consensus patterns and minority viewpoints that would be missed by treating personas as isolated individuals.
The scalable automated system allows artificial societies to be constructed efficiently. Organisations provide their audience definition and the platform handles persona construction, social graph modelling, and calibration. Simple demographic-based societies can be built rapidly. Complex multi-stakeholder populations — such as the three distinct societies built for Teneo's engagement (1,364 policymakers, 1,526 tech leaders, 2,381 general population) — are delivered within days. Once a society is constructed, research can be run and results delivered within hours. The entire process is designed to eliminate the months of setup and recruitment that traditional research requires.
Yes. Artificial Societies can incorporate your first-party data — including CRM records, existing qualitative research, quantitative survey data, and proprietary audience intelligence — to construct a synthetic population that represents your actual customers, prospects, or stakeholders.
Artificial societies typically contain between 300 and over 5,000 interconnected personas, with a total database of over 2.5 million persona profiles available. The size is determined by the research objectives — a focused study on a specific professional community may require fewer personas than a broad multi-stakeholder population simulation.
Yes. Once constructed, an artificial society can be reused across multiple research engagements, allowing organisations to track how the same synthetic audience responds to evolving strategies over time.
Minimal. Artificial Societies has built a scalable automated system that handles persona construction, social graph modelling, and calibration. Customers provide their audience definition (demographics, target organisations, job titles, or first-party data) and the platform does the rest — without months of heavy lifting on the customer's side.