The Authenticity Lab

An ESSEC EMBA module replaced the comfortable case-study ritual with a live research sprint. Executives audited their own sustainability claims using social data, secondary research, and AI. What they found challenges how the insights industry thinks about trust, evidence, and the tools we sell.

Most executive education still follows a familiar script. Leaders gather at a business school, debate a case, admire a framework, and return to work intellectually stimulated but operationally unchanged. The case protagonist always seems bolder, clearer, and more decisive than anyone ever feels back at the office.

That model assumes insight automatically converts into action. For today's executives, it rarely does.

In a world shaped by AI, public scrutiny, and real-time accountability, leadership credibility no longer depends on how confidently a story is told. It depends on whether a claim can survive exposure to data, scepticism, and comparison. Authenticity has ceased to be a communication challenge. It has become an evidence problem.

This is the premise behind The Authenticity Lab, a collaboration between Isentia and the ESSEC-Mannheim EMBA Program. Rather than treating the classroom as a forum for discussion, the Lab treats it as a pressure test. Not a branding workshop. Not a focus group. A controlled environment where corporate claims are examined against live data, AI-assisted analysis, and disciplined questioning.

From classroom to lab

The Lab begins with a constraint many executives rarely face. Uncomfortable input.

Participants worked with the Isentia Sustainability Dataset, comprising more than 200,000 organic conversations from the previous month across over 20 global sources, including TikTok, Instagram, Reddit, Facebook, reviews, and X. At that scale, it becomes difficult to hide behind a single viral anecdote or a carefully selected data point. Patterns assert themselves.

Executives from aviation, finance, luxury, consulting, tourism, mobility, gaming, and manufacturing were asked to interrogate not a hypothetical case, but the credibility of sustainability claims in their own industries. They combined social narrative analysis, credible secondary research, and AI-driven pattern recognition.

Then came the most important step. Challenging the AI.

Modern AI tools reward speed, fluency, and plausible confidence. They also reward weak questions. When prompts are soft or leading, outputs can sound insightful while quietly reinforcing existing assumptions. By making this failure mode visible, the Lab surfaced a risk that the research industry needs to take seriously. Synthetic confidence produced at scale.

Each participant translated findings into a simple structure. What. So What. Now What. No more than ten slides. The constraint was deliberate. It forced decisions about what evidence mattered and which claims could not be defended. Discussions were conducted under the Chatham House Rule. When reputational performance is removed from the room, honesty improves. So does learning.

What authenticity really requires

Across industries, a consistent pattern emerged. It has immediate research design implications, and we think it deserves precise naming.

Audiences grant authenticity only when three elements work together. A concrete benefit for a clearly defined community. Cultural resonance with how that community understands value. And operational proof, where the system behind the claim is visible and credible.

Absent any one of these, trust erodes quickly. We observed this across four sectors. The consistency suggests something structural rather than situational, though four cases constitute a pattern worth testing at scale, not proof.

Four places where authenticity breaks

Tourism and the label trap. Drawing on prior experience in the tourism sector, Sebastian Blattler, Managing Director APAC at Boschung Group, examined the credibility of Swiss sustainability certifications. The base assumption was straightforward. A national Swiss label would, on its own, signal trust. Social media narratives challenged this quickly. Trust increased only when the label was linked to tangible benefits for local communities and visible respect for local heritage. The environmental promise mattered, but it was not sufficient in isolation. This is not a labelling problem. It is an evidence architecture problem. Authentic sustainability communication cannot expect the label alone to do the work. Local impact, cultural relevance, and relatable data must be part of the claim. For researchers, the implication is that any tracker treating "certified" as a single trust signal is averaging away the scepticism.

Consulting and the advice footprint. Giovanna Vivoli, a Senior Consultant with Kantar Consulting, reframed sustainability authenticity in a way that runs counter to conventional consulting narratives. In professional services, the meaningful sustainability footprint is not office recycling or internal pledges. It is whether the advice delivered measurably improves a client's real-world sustainability outcomes. If influence is the product, then authenticity resides in results. This creates a distinct burden of proof, sharply separating credible consulting from generic, AI-generated outputs and "restech" solutions that sound responsible but change little. The research industry faces the same mirror, and it is worth being honest about that. Is the value of a research project in the methodology or in what the client does with the findings?

Mobility and the system gap. Thomas Vacher, Regional Sales Manager at Thales Asia Solutions, identified a critical mismatch between consumer narratives and expert definitions of sustainability. Public social conversations frame electric vehicles as a product story, focused on the car, the badge, and the promise of clean travel. Industry experts define sustainability as a system story involving battery lifecycle, charging infrastructure, grid composition, and policy. This gap creates risk. Sustainability messaging often sounds like a product capability, while proof depends on an invisible system that specialists can readily interrogate. When that system-level reality surfaces, credibility can unravel quickly. Social listening needs to track consumer language and expert discourse simultaneously. The perception-reality gap between those two conversations is where crisis signals live.

Luxury and the permission to be unfinished. Minyoung Seo, Logistics Manager at LVMH Fragrances and Cosmetics Singapore, mapped Gen Z expectations within the luxury sector and surfaced a paradox that is both demanding and forgiving. Perfection is not required, but honesty is non-negotiable. Narratives around repair, reuse, resale, and explicit acknowledgement of what remains unsolved resonated more strongly than polished claims of completeness. The implication is counterintuitive for luxury brands. Trust may be rebuilt not by promising more, but by showing the work in progress and openly admitting what is unfinished. For researchers, this inverts a longstanding assumption. Among younger demographics, disclosing imperfection appears to function as a trust signal. We think this is right, though the longitudinal evidence is still thin.

The structural pattern

Place these four cases side by side and something becomes visible that no single industry sees from inside its own silo. In every case, marketing operates at the visible surface while proof operates at the invisible infrastructure. Tourism markets the label, proof lives in community outcomes. Mobility markets the product, proof lives in systems. Consulting markets methodology, proof lives in client results. Luxury markets aspiration, proof lives in admitted imperfection. The gap between those layers is where trust erodes, and it erodes the same way across radically different sectors.

The real lesson was not sustainability

Sustainability served as the stress test because it is where audiences are most alert and most exhausted. The deeper lesson was about AI and the discipline of questioning.

AI can compress weeks of scanning into minutes. It can surface patterns worth testing. It can also turn a comfortable assumption into a polished conclusion when questions lack rigour. This is not a technology problem. It is a discipline problem. If our tools produce plausible analysis from vague briefs without structured scepticism, we become the mechanism that launders weak questions into confident recommendations. We become the sustainability label without the external audit. We keep circling back to this because it seems to be where the real value sits.

The Authenticity Lab does not teach executives what to think about authenticity. It teaches them how to audit a claim in a world where fluent answers are cheap and confidence can be synthetic.

What the insights community should build next

Sustainability was only the beginning. Innovation claims, customer-centricity promises, diversity commitments, and digital transformation narratives can all be subjected to the same pressure test.

Three implications for the research community. Claim auditing is a research product waiting to happen, positioned between a brand tracker and a crisis simulation, telling clients what they can claim, what to soften, and what needs proof first. Social listening and secondary research belong together, because the triangulation between what people feel and whether those feelings are grounded is where insight actually lives. And AI scepticism needs to become a demonstrable skill, not a disclaimer, shown by making the gap between a lazy prompt and a rigorous one visible to the client.

Authenticity is not a marketing tone. It is a standard of evidence. And the next wave of demand will not be for more data or faster dashboards. It will be for structured methods that help organisations figure out what they can honestly claim, and what they should stay quiet about until the proof catches up.