Building an Artificial Society is a purposeful process of constructing a network of AI personas that accurately represents the real-world stakeholders relevant to a specific decision. Each society — a network of 200 to 3,500 interconnected 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. The process follows three stages — persona construction, society creation, and a simulation engine — described in full on our Method & Evaluation page.
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 Behavioural Analysis Engine that psychometrically triangulates observations into an internally coherent belief system and personality for each persona. Where clients provide first-party qualitative or quantitative data, it 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 in ways that reflect a unified worldview grounded in real human behavior.
Once individual personas are constructed, they are organised within a network that captures real-world social influence — connected from observed interactions and historical associations. Network science models how opinions form and spread: the conformity pressures, network effects, and community dynamics that shape real human societies. This network modelling 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.
With belief systems and network systems in place, a question or stimulus is posed within a specific context. Each persona reasons from its own beliefs, and the social-influence models calibrate that response against the network around it. Responses emerge at every level — individuals, subgroups, and whole populations — so a single simulation yields both top-line opinion distributions and thousands of individual-level explanations. Our Method & Evaluation page details how this pipeline performs against human panels and simple synthetic personas.
The scalable automated system allows Artificial Societies to be constructed efficiently. Organisations provide their audience definition and the platform handles persona construction, network modelling, and calibration. Simple demographic-based societies can be built rapidly. Complex multi-stakeholder engagements — such as the three distinct societies built for Teneo (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 network of AI personas that represents your actual customers, prospects, or stakeholders.
Each Artificial Society typically contains between 200 and 3,500 interconnected personas, drawn from a database of over 2.5 million persona profiles. The size is determined by the research objectives, and larger engagements can combine several societies — a focused study on a specific professional community may need fewer personas than a broad multi-stakeholder engagement.
Yes. Once constructed, an Artificial Society can be reused across multiple research engagements, allowing organisations to track how the same audience responds to evolving strategies over time.
Minimal. Artificial Societies has built a scalable automated system that handles persona construction, network 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.