Asking questions is one of the fundamental activities for modern knowledge workers. They can be analysts, researchers, architects, managers, or leaders across teams in product, sales, marketing, finance, business development, etc., and their jobs require high-level thinking and information processing. Finding answers quickly and with facts is crucial for the knowledge worker function.

Unfortunately, asking questions has been traditionally categorized as business intelligence (BI), and it has been defaulted to building dashboards—a slow and painful process that still doesn’t answer the question. Building dashboards is also a highly technical activity, making it especially difficult for the vast majority of non-technical users who could easily outnumber their technical peers by 100x or more.

Generational Productivity

Interestingly, we are in the midst of an AI transformation that promises a generational step up in worker productivity, similar to what happened back in the industrial age, or more recently with computers, the internet, and the cloud. AI can now provide intelligence for laborious, repetitive work while the workers can focus on their net new value addition. This means that knowledge workers should focus on their questions and analysis rather than on figuring out the data, queries, or dashboards. All these are supposed to be the laborious and repetitive implementation details that AI will take care.

AI adoption is already picking up the pace. The recent memo from the CEO of Shopify underlines the fundamental expectation that employees should be using AI in their everyday work. However, Shopify is not the only one; companies of all sizes are thinking about how to leverage AI for their business. The goal is to do far more with far less, i.e., ambitious targets of boosting productivity by multiple orders of magnitude.

AI-powered Querying

So, how do knowledge workers turbocharge themselves in the AI age? How do they become 100x? They need to ask way more questions and get answers way faster using AI, i.e., AI-powered querying. The goal should be to focus on high-level thinking, such as what new questions to ask, what new analyses to do, and what new interpretations to draw, while leaving all low-level mechanics to the AI. Tursio is building such an AI capability, and talk to us to learn more.

Now, one may wonder, what does AI mean for the good old world of BI? In all likelihood, the BI as we know it is going to be dead. Hammering the daily questions using tedious dashboards is too unproductive for the modern workforce, and this entire process is long overdue for transformation, one that makes knowledge workers truly productive.

Human productivity has come a long way, but it is fascinating to see that it still has so much room to grow. Possibly, it could even trigger a natural selection in our workplaces — intriguing, but only time will tell.