Social Science is the New Business Science
When we founded Gemic nearly twenty years ago, we built on a simple belief: firms grow when they build better relationships with the people they serve. At their best, firms create shareholder value and human progress at once. Finding that balance has never been just a question of economics or technology. To build and grow a company, you must understand how people see the world, how they make sense of value, and what they find worth sticking with over time.
That is why, from day one, we placed social scientists alongside MBAs and technologists. Not to humanize business at the margins, but to meet a structural need at its core. Knowing where to compete and how to win meant understanding the social and political systems that either welcome or reject what firms offer. That was true then. Today, we are betting the firm on a stronger claim: social science is becoming the essential capability of the emerging economy, and the method by which firms will learn to act inside markets they no longer control.
Here is why.
Markets are social systems, not bounded categories
Much of strategy still assumes a world that has gone - one of shared futures, coherent publics, stable institutions, and shared faith in a better tomorrow. In that world, optimizing the business made sense. Small gains added up year after year, and you could assume trust until something went wrong.
That world is over. Stable markets and categories have given way to social systems that judge offerings and the firms behind them. Executives now move between strategic communications, government affairs, brand marketing, trust repair, and innovation. Along the way, they grow an uneasy feeling that markets do not have clean edges. Markets now are constellations of people, technologies, and narratives - living ecologies in which value, desire, and reputation are socially defined.
Consider the global running market, which my firm knows well.
On paper, it is simple to define. Research firms segment it by footwear category, price tier, demographic, and geography. Executives track share within “performance running shoes,” “lifestyle running,” or “technical apparel.” Dashboards record growth, penetration, and competitive position.
But no serious executive in a sportswear firm believes value comes from dropping products into bounded categories. Running is not just a product category. It is a social practice with an evolving system of definitions, tastes, technologies, norms, and narratives. Value in that system comes not only from raw performance or price but from cultural legitimacy: who is credible, what feels extractive, who fits with how runners themselves define their practice. A brand can grow share while losing standing inside passionate amateur running culture. It happens when marketing outpaces community presence, when elite athletes get visibility, but everyday runners feel unseen. The spreadsheets can show gains while the brand’s position in the social system slowly erodes. This has happened to more than one sportswear giant.
Good executives know this in their bones. The real contest is not the shoe aisle but the running world -the ecosystem of runners, coaches, technologies, media, medical advice, social platforms, and informal norms through which legitimacy is negotiated. Markets, in this sense, are not containers. They are arenas of social judgment with ever-shifting boundaries that escape simple category definitions.
For strategy as a practice, the shift runs deep. As the cost and skill of traditional market analysis collapse toward zero, value moves to shaping these systems. Strategy becomes creative and analytical at once. Social science, the discipline that understands how such systems work, moves from the margins of strategy to its center.
The future takes shape inside these social systems
The running world is one such system. There are lots of others, and they no longer share a common future. The promise of universal progress - economic, technical, moral - has thinned. This is not because people have stopped caring about the future, they just no longer agree on what a good one looks like.
In that vacuum, trust drifts into cultural worlds with distinct values, identities, and ideas of what counts as improvement. These worlds work as ecosystems. They shape aspiration, define legitimacy, and govern belonging. As a result, growth no longer depends mainly on awareness or simple differentiation. It depends on whether an offering fits the moral economy of the social ecosystem it enters. Firms can no longer design offerings for abstract individuals. They must design them for the social worlds that will shape, interpret, contest, and authorize them.
AI shapes social systems
Artificial intelligence marks a deep shift in how people and machines work together. It is often framed as a productivity wave. In practice, it is the most important social technology of the century, and it plays two roles at once.
As a subject, AI is the biggest legitimacy challenge facing large firms today and the reason is structural. Every earlier technology had social costs or side-effects, but AI is made of social life itself. It is trained on human language, built from human judgement, and deployed on the raw material of coordination: how people assign blame, confer authority, decide what counts as true. Optimising AI without social science fails differently than, say, a badly designed supply chain fails. A faulty supply chain gets inefficient whereas a badly tuned AI gets refused.
For corporate leaders investing in AI this matters a great deal. Most firms fund AI the way they fund software. The CTO owns the line-item and treats the social response as someone else’s problem. That works for software, but it does not work for a technology whose performance is its social acceptance. The failure mode is not a system that underperforms, but rather a system that performs and is refused. Niklas Luhmann argued that modern systems fail not when they stop working, but when they lose legitimacy in the eyes of the systems around them. AI can break on both axes at once and its social legitimacy must be built into the investment, not bolted on after it.
As a tool, AI is the lever that makes social intervention affordable at scales once impossible. Synthetic publics, multi-agent simulation, rapid cultural stress-testing, continuous feedback monitoring: these were research methods once reserved for well-funded studies that took months or even years. AI collapses the cost and time of each. For the first time, firms can model how a product, policy, or narrative will behave inside a social system before committing to it at scale. Doing this well demands a real social-science capability. After all, launching a product is itself a social intervention. The only question is whether the firm knows it.
This double role is why AI probably is not a threat to human strategic judgment, but the condition for a new kind of it. The firms that will matter in the next decade are the ones that do both at once: put AI to work with social legitimacy and use AI to practice social science at speed and scale.
Social science holds answers to the consulting industry’s challenges
For decades, management consulting made its name by helping firms do things better, faster, cheaper and more efficient. Those skills remain necessary, but they are no longer decisive.
Today’s firms sit where multiple forces meet: technological upheaval, cultural mistrust, geopolitical instability, and blurring categories of competition. These forces do not arrive in sequence. They collide and create a state of permanent ambiguity. That territory belongs to social scientists, and to engineers and business leaders who think like social scientists. Anthropologists and sociologists are unusually good at framing problems in context, reading many signals and turning them into a thesis for growth. Understanding how growth happens through social system’s acceptance will be among the scarcest business skills of the next decade.
Strategy is becoming the ongoing back-and-forth between a firm and the social systems it depends on, designed not only to explain those systems but to act within them, learn as they respond, and shape them. This is strategy as meaningful social intervention. Traditional strategy competes inside categories that market research and statisticians have already drawn. Social intervention treats those boundaries as provisional and asks: what is the real system of value here, and what line around it can only my firm see?
To see what this looks like, return to the running market.
A sportswear firm that understood its position as a social one would not commission another segmentation study. It would go inside the ecosystem to map its boundaries and ground rules and create a market definition no competitor can see. Historians would carefully map the forces that shaped the present. Ethnographers would spend time in run clubs, physiotherapy clinics, and online communities to learn what legitimacy means there and who has the standing to grant it. AI-powered simulations of synthetic publics would model how coaches, elite amateurs, and informal tastemakers might interpret a new product line before a single unit is made. The firm would test narrative prototypes inside the cultures that set the category’s taste and watch the community’s real response in live conditions rather than survey it after the fact. When the firm finally acts, it acts with a testable forecast of how a specific ecosystem will respond to specific choices.
The strategic question shifts from “what is the market telling us?” to two new ones: “how do we define this market in a way no competitor can see?” and “what will it do when we move?”
This is the evolving shape of strategic practice. It combines five capabilities that rarely sit under one roof: deep understanding of the past and the forces that shaped the present; ethnographic fieldwork inside the cultural worlds that grant legitimacy; simulation of how those worlds respond to stimuli, accelerated by AI; rapid prototyping of offerings, narratives, and incentives inside real communities; and feedback loops that catch legitimacy drift before backlash makes it public.
Almost no firm runs these capabilities together. Elinor Ostrom, the Nobel-winning political economist, spent a career showing that lasting institutions emerge not from perfect plans but from repeated engagement with real communities and real constraints. Social intervention brings Ostrom’s logic into commercial work, at commercial pace. It also changes the economics of strategic work itself. Intervention is iterative and living systems must be engaged over time.
We double down on applied social science
I like social science because it is humane and intellectually elegant. But we run a business. We have been building this capability for years; we are betting that the next decade will prove us right.
We double down because traditional consulting built its margin on analytical work - market sizing, competitive synthesis, trend analysis, framework application - that AI now does in hours at a fraction of the cost. As that kind of analysis becomes cheap, what becomes more valuable is the interpretive and interventional work that social scientists, working with AI and technologists, can do exceptionally well.
Social science is becoming the precondition for strategy itself, and the method by which strategy learns. Those who treat it as optional will keep optimizing answers to questions the world is no longer asking.