# Four key takeaways from IIEX North America

- URL: https://www.askattest.com/blog/attest-news/four-key-takeaways-from-iiex-north-america
- Published: 2025-05-28
- Updated: 2026-05-02
- Description: The Attest team touched down in Washington for a jam-packed two days at IIEX this month. Amongst keynotes, breakout sessions and a busy show floor, we’ve unpacked four key themes that are top of mind for researchers in 2025. AI…

---
The Attest team touched down in Washington for a jam-packed two days at IIEX this month. Amongst keynotes, breakout sessions and a busy show floor, we’ve unpacked four key themes that are top of mind for researchers in 2025.

##  **AI is hot – but trust and use cases matter**

There’s no two ways about it – AI is dominating the conversation. But there’s growing skepticism around concepts like synthetic audiences. Being able to boost an audience by inferring new respondents was better received. There’s also a buzz around **AI-moderated qual** tools and **persona-based AI agents**, but trust and data accuracy remain critical factors in adoption.

![](https://emx2zzfzxax.exactdn.com/wp-content/uploads/2026/05/AI-adoption-report-cover_landscape.jpg?strip=all&w=1920)

Consumer Adoption of AI Report

How are consumers using AI in 2025? Learn how technology is reshaping the consumer experience.

[Download now!](https://www.askattest.com/our-research/consumer-adoption-of-ai-report-2025)

![Close banner](https://emx2zzfzxax.exactdn.com/wp-content/themes/attest/images/icons/icon-close--white.svg)

##  **Data quality is in crisis**

Bots are gaming the system. 3% of devices are responsible for a whopping 19% of survey responses! Quality is the number-one concern for in-house researchers, whether you’re surveying your own audience or using an external panel.

##  **Privacy is paramount**

Customers are ever more wary of their data being used to train AI models. Compliance and communication are key to staying ahead of the curve. For larger companies, navigating internal controls on this is also key

##  **Manual analysis is a bottleneck**

Despite the self-serve boom, teams are frustrated with the lack of automation in analysis.

## **Bottom line**

Researchers are hungry for better tools, cleaner data, and real AI value—not hype.