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EnglishWhich industries and topics does The Decision Lab cover?
Updated
The Decision Lab works across a defined set of industries—financial services, HR technology, banking, digital wellness, and mental-health AI—and applies behavioral science and AI to recurring topics such as AI adoption and trust, consumer insights, digital nudging ethics, and misinformation. If your organization operates in one of these sectors or faces one of these problems, the site's case studies and research pages are the fastest way to judge relevance.
Industries with demonstrated work
The site's case studies are the clearest evidence of sector experience. Each pairs an industry context with a specific problem:
| Industry | Problem addressed | What the work shows |
|---|---|---|
| Financial services | Preventing debt repayment dropouts | Predictive modeling applied to consumer financial behavior |
| HR technology (Fortune 500) | Getting 20,000 employees to actually use AI | Building AI trust and driving adoption across a large workforce |
| Banking | Defining a bank's next decade of AI | Long-range AI strategy grounded in behavioral science |
| Digital wellness | Measuring a platform's real influence on what people buy | Assessing platform influence on consumer decisions |
| Mental-health AI | Cultural fit and safety in mental-health LLMs | Research on the adaptation dilemma in AI care tools |
The site also references work on personalizing care for 25 million members with a digital wellness platform, and simulated environments for measuring platform influence. These examples suggest the firm is comfortable with both large-scale consumer problems and internal workforce challenges.
Recurring topics across sectors
Beyond industry labels, several themes recur in the firm's insights and research:
- AI adoption and trust — how organizations move employees from awareness to actual use, and how trust is built at scale.
- Consumer insights — how people really decide, including the ethics of persuasive algorithms.
- Digital nudging ethics — where personalization and motivation cross into manipulation.
- Misinformation and deepfakes — behavioral defenses and taxonomies for countering AI-amplified false information.
- Decision intelligence — using AI to personalize services while keeping human decision-making central.
How to check fit for your own case
- Open the case studies section and scan for your sector or a closely adjacent problem.
- Read the featured insights for the topics you care about—nudging ethics, misinformation, or AI trust—to see whether the framing matches your needs.
- If a case study describes a problem similar to yours, note the scale (workforce size, member base) and the method used; that is the strongest signal of relevant experience.
- Use the contact form on the site, describing what you are trying to solve, to confirm whether your industry is in scope.
A practical caveat: the published case studies skew toward large organizations and AI-adjacent problems. If your issue is outside these sectors—or much smaller in scale—the insights pages may still be useful, but direct sector experience is less evident from the site alone.