Bob Pulver chats with Ainesh Ravi and Victoria Sakal from Wonder, a startup that combines human expertise with AI to provide market research solutions. They discuss the evolution of Wonder, the challenges and benefits of incorporating AI into their workflow, and the importance of human expertise in the research process. They also touch on the potential risks and advantages of using AI tools and the need for a strong moat in the market. The speakers discuss the importance of adaptability, investing in people, and leveraging AI tools to enhance productivity. They also touch on the challenges of bias in AI output and the need for cognitive diversity in decision-making. The conversation concludes with discussions on the future of research, the role of strategic insights, and advice on how individuals can incorporate AI tools into their daily lives.
Keywords
market research, AI, human expertise, workflow, moat, strategic insights, AI, future of work, adaptability, investing in people, AI tools, productivity, bias, cognitive diversity, AI literacy
Takeaways
- Wonder combines human expertise with AI to provide market research solutions.
- The incorporation of AI into the research process requires a behavioral change in how the company thinks about and structures its teams.
- Prompt engineering and understanding the limitations of AI models are crucial for delivering high-quality research.
- Wonder focuses on serving both large companies and smaller clients, offering a simpler and more cost-effective alternative to traditional research firms.
- The combination of strategic value, IP, and process expertise creates a strong moat for Wonder in the market.
- The future of research lies in the integration of AI tools and human expertise, allowing for higher-quality insights and more strategic decision-making.
- Adaptability is key in the future of work, and individuals should invest in developing their skills and staying relevant.
- AI tools can enhance productivity and efficiency in various tasks, but it's important to choose the right tools and understand their limitations.
- Bias in AI output is a concern, and organizations should strive for cognitive diversity in decision-making to mitigate potential biases.
- A culture of curiosity and a mindset of continuous learning are essential for navigating the evolving landscape of AI and the future of work.
Sound Bites
- "The incorporation of AI into the research process requires a behavioral change in how the company thinks about and structures its teams."
- "Prompt engineering and understanding the limitations of AI models are crucial for delivering high-quality research."
- "There's a bunch of different ways to think about it as your prompts might be recipes and you've got to, not everyone who uses the same ingredients, the output's not going to be the same."
Chapters
00:00 Introduction and Background of Wonder
08:07 The Behavioral Change in Incorporating AI into Research
13:10 The Importance of Prompt Engineering and Understanding AI Limitations
23:29 Serving Both Large Companies and Smaller Clients
26:00 Building a Strong Moat with Strategic Value, IP, and Process Expertise
28:40 Adaptability and Investing in People in the Future of Work
35:05 Enhancing Productivity with AI Tools
46:15 Addressing Bias and Promoting Cognitive Diversity
54:53 Elevating AI Literacy: Starting Small and Embracing Curiosity
Ainesh Ravi: https://www.linkedin.com/in/aineshravi/
Victoria Sakal: https://www.linkedin.com/in/victoriasakal/
Wonder: askwonder.com
Wonder workshop on how to apply AI to your workflows (recording & resources): https://askwonder.com/insights-hub/tap-genai-to-accelerate-your-work
Wonder’s thought leadership, research and POVs (subscribe for more): https://askwonder.com/insights-hub
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