In this section I review one AI-powered application and demonstrate how it can be used to create value. I include concrete examples and lessons learned from actual use, and only recommend tools that I have used extensively myself.
Research that earns trust through transparency
When we talk about AI earning trust - as we explored in this issue's leadership principle - few tools demonstrate the principle as clearly as Perplexity. While most AI assistants generate responses from their training data and leave you wondering "where did this come from?", Perplexity builds its entire experience around showing its work.
Perplexity is an AI-powered research and answer engine that combines large language models with real-time web search. What makes it distinctive is its commitment to citation: every claim links back to its source. You can verify, you can dig deeper, you can be vocally self-critical of the results - because you can see exactly where the information originated.
Why this matters for business leaders
The challenge with using general-purpose AI for business research is the trust gap. When an LLM tells you something about market trends, competitor moves, or industry regulations, you face a choice: accept it at face value, or spend time independently verifying. Perplexity shifts that dynamic. The citations are built into the response, making verification immediate rather than additional work.
This matters especially for:
Competitive intelligence: When researching competitors' recent moves, product launches, or strategic shifts, you need current information with clear provenance. Perplexity's real-time search means you're not relying on training data that might be months old.
Market research: For understanding industry trends, market sizing, or emerging technologies, having sources you can trace - and share with colleagues - transforms AI output from "interesting if true" to "here's what we found and where."
Due diligence: When evaluating potential partners, vendors, or acquisition targets, the ability to verify claims matters. Perplexity's approach supports the kind of rigorous investigation these decisions require.
How I use Perplexity
I've integrated Perplexity into my research workflow for newsletter content, client work, and staying current on AI developments. Here's what I've found most valuable:
Daily intelligence briefing: I ask Perplexity specific questions about recent developments in areas I'm tracking. Unlike setting up news alerts, I can ask nuanced questions: "What have the major consulting firms published about AI governance in the past two weeks?" The responses come with links I can bookmark for deeper reading.
Client preparation: Before client meetings, I use Perplexity to get current on their industry, recent company news, and competitive landscape. The cited sources give me confidence to reference specific information in conversations - I know where it came from and can share the source if asked.
Fact-checking AI outputs: Ironically, I sometimes use Perplexity to verify claims from other AI tools. When ChatGPT or Claude makes a specific claim about market data or recent events, I'll cross-reference with Perplexity to see if current sources support it.
Practical considerations
Perplexity offers a free tier that's sufficient for getting started, with Pro plans ($20/month) that provide more queries, access to more powerful models, and file upload capabilities. For enterprise users, Perplexity Enterprise Pro adds features like SOC2 compliance, data privacy guarantees, and team management.
Try Perplexity at perplexity.ai