Lie #3 — You’re ready for the AI + ML deep end

The data lies (and truths)

Last Updated: December 21, 2023

You’ve hired pedigreed data scientists and engineers, invested in shiny new software, and perhaps even reorganized your entire business, all in the hopes of becoming an artificial intelligence-driven enterprise. But your efforts continue to fail.

Why? Because you’re tackling the problem backwards.

Businesses should seek out talent that can help manage increasingly complex IT operations and aid the company in figuring out how best to deploy next-generation AI and machine learning applications.

But such efforts often result in companies thinking they need to hire the best and brightest engineers and scientists coming out of MIT or Stanford, and quickly purchase the new shiny AI + ML tech so they can be productive. It’s one of the biggest mistakes an organization can make.

Many businesses are simply trying to do too much, too fast, without taking the time to create a foundation for success. They want to jump in the deep end without learning how to swim first. This is why Data Scientists become Data Janitors, ultimately becoming highly unproductive for what they were hired to do.

If you don’t take the time to get your data strategy right, your AI efforts will continue to fail.

In AI and machine learning, the results are only as good as the data that’s backing it up. Simply trying to throw technology at the problem won’t work.

The pandemic is a prime example. Many companies were caught flat-footed when, almost overnight, their standard operating protocols no longer sufficed. Critical tasks, like accurately predicting customer demand, were suddenly impossible because the historical data they were working off of was suddenly worthless. Many didn’t have the infrastructure in place to support real-time analytics. As a result, ML models quickly drifted and became inaccurate predictors.

The answer to that problem is not through HR. It’s through better data management. The demand for skilled data wizards is off-the-charts. It’s foolish for a company to think they can simply hire the talent needed to succeed at AI. Not only will that not help you become data-driven, the costs will balloon.

In fact, many organizations are not even close to being at the point where the investment in those roles would produce a justifiable return.

Take the money you would spend on high-priced talent and put it towards creating the proper footing to ensure long-term success.

AI has the potential to be very powerful, able to increase revenue, reduce costs, and improve product experiences.  Yet, your AI and machine learning investments are only as good as the data you have access to.  Access to high quality data, often from multiple data sources, is the prerequisite to an AI strategy.  Without it, you’re just lighting money on fire.

Starburst is designed to serve as the foundation for your AI efforts. We make it easy for you to get all of the data you need from every corner of your business to ensure you’re getting the best results possible. We significantly reduce the time Data Scientists spend searching for and copying data, placing their time and energy on what you hired them for – building and training models.

Transforming your company to be able to not only survive, but thrive in the ongoing AI metamorphoses is paramount. Investments now could significantly alter the course of your company’s IT journey for the next decade.

Don’t let the desire to move as fast as possible lead you to bypass the critical task of setting a foundation of data access.

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