John Farrall, publisher of the influential Alternative Data Weekly newsletter on Substack, has spent the past thirty years working in the investment research and alternative data industries. Over the years John has held senior positions for a number of well-known firms including ModuleQ, 90 West Data, Cleveland Research and FTN Midwest Securities.
The amount of data currently available is beyond human comprehension. Knowledge workers rely on information to do their jobs. AI is impacting this right now, and the source of advantage is shifting in real time. The following table outlines the development of the information economy over the past twenty-five years and into the future.
Pre-2000: Limited Information World
- Context: Knowing what information was out there was key.
- Example: The old company “First Call” (now, many years later, owned by LSEG) was literally a nod to brokers making their highest-paying client their first call so that client would have an information advantage.
- Moat: Awareness & access. Knowing the data existed, & how to most efficiently access it.
- Key Skills: Digging & discovery. Knowing what information was out there and how to get it (and get it first).
2000 – 2025: Information Overload World
- Context: There is an explosion of relevant information. Knowing how to access the right information was the key.
- Example: Knowledge workers made themselves necessary by being the only ones who knew the different keystrokes needed to quickly find the right information inside the terminal. Excel and PowerPoint jockeys in high demand.
- Moat: The ability to access and organize information; telling a good story.
- Key Skills: Sifting & storytelling. Knowing where the relevant information resides, filtering out the noise, pulling everything together, & presenting the story.
2025 – Future: Impossibly Too Much Information World
- Context: There is too much information. Systems will, eventually, deliver to you the right information at the right time, based on your questions & workflow, plus everything else it knows about you (the context).
- Moat: Perfecting your workflow to include only the necessary and avoid the unnecessary. Asking the right questions.
- Key Skills: Questioning & domain expertise. Understanding the right questions to ask for your business at that moment. Being the trusted source for clients, colleagues, and stakeholders.
The future belongs to those who can ask better, faster, sharper questions. Everyone else will be stuck sifting through answers to questions they never should have asked in the first place.
So how does this future state look in real terms?
Solutions coming from big players in the market intelligence space involve using AI interviewers to query the expert. While creating convenience for the interviewee, this is outsourcing the most important part of the interaction, the line of questioning.
The value will be found using AI to create synthetic audiences that will bolster the eventual human engagement. With the right calibration, AI can recreate an audience that can be peppered with limitless questions.
Interviewing AI-generated audiences does not completely replace talking to humans. Synthetic audiences can help with interview preparation or allow the questioner to dig into markets that would be otherwise too small to justify the expense of human engagements. All with the backdrop that there is no limit to the interrogation.
Firms with long histories of surveys or expert interviews will be at a huge advantage when it comes to audience creation and calibration. Using a proprietary history of real human engagements to inform synthetic audiences will help dial in the responses that most closely reflect the “real” world.
The business model may look like a license for access to specific, highly calibrated audiences that have been proven to generate responses like a human audience.
When the real value comes from asking the right question, the limitless ability to generate an answer can open a world of opportunity.
Any feedback or questions about the above article should be directed to John Farrall at jfarrall@icloud.com.