Startups Will Likely Replace Data Analysts With AI in Next 5 Years

The idea of a startup founder is always nice to ponder on. Fast paced environments where something exciting happens every day. A small group of people hustling their way to success. A few years of relentless work and then the glorious exit - a.k.a. sailing into the sunset.

For many, this idea is nicer than startup reality. The discrepancy between the two will often come with a strong reality check, if not with burnouts. And the reason is simple: Startup teams are small and lean so they can move fast, but this also mean that each member has to wear multiple hats, and thus learn how to compartmentalize their work life between several roles. In the pre-launch days this is exciting, and welcome. Brainstorming requires everyone, and important decisions are a group thing. Post-launch however, things change.

The actual grind starts after your product goes live. Finding the first few users, getting them to test the product, give feedback, and actually iterating that feedback to make your product better. EVERYTHING you do from here on out has to do with data. And thus, data interaction and data analysis becomes an important task of marketers, product folk, as well as sales teams.

The problem is that most (business) roles do not have SQL experience. And to interact with a database - where the data lives - you need to actually know SQL. To go around this problem, most teams, including our team in the past, relied on the dev(s). You briefly explain what data you need, the dev creates the SQL, pulls the data for you, and sends you the raw data to analyse. But if this happens too often, the dominoes start falling. The workload of the devs increases, and thus productivity stalls. And it is at this stage that teams will usually onboard more devs, or data analysts that can handle database interactions alone.

In an ideal world, this would of course be great. After all, distributing the work between people seems like a better idea for long-term healthy work environments. But our success stretches to the length of our runway, and for most, this runway is small. What is more important is to build systems that extend that runway effectivelly.

This is why I am writing this article. Today, the bottleneck of hiring data analysts shortly after launch creates runway problems. It is unsustainable for team performance and for the money that startups have available.

But AI solves this. And in 5 years I expect that people will only rely on AI for getting access to data. Let me explain...

Over the past couple of years, we went from using LLMs to generate SQL, to building interfaces that remove the need for SQL, to platforms that do that + data visualization. Data analysts at early stage startups are now quickly becoming irrelevant, and as these tools continue to improve, startups will be less likely to look for people to take over this role. Instead, business users will use tools and "chat" with their databases like they did with an LLM all along.

We recently launched TalkBI, a tool that does exactly that. We built a simple interface that sits between the user and the database, allowing them to write in natural language, and pull the exact data they need from their database. But the data is not simply presented in its raw form. It is, instead, displayed in beautiful dashboards that teams can use for reporting, or to share with each other. Founders can explore the demo on our website, afterwhich they can use the free version first - it should be sufficient at the early stages of your product launch. We invite you to have a look and contact me directly for any feedback, questions, or concerns you may have. Happy testing everyone! :)