Artificial intelligence (AI) and its “cousin” technology, machine learning, find themselves being utilized in a variety of circumstances and organizations. Though they cannot completely replace the human brain, scientists are still working to train them to think and feel like humans in more and more lifelike ways.

Machine learning has especially become the “teacher’s pet” of technology. Research in this area over the past decade has resulted in bringing automated systems to the white-collar professions. The growth of robotics, digital assistants, smart machines, automated bots, and apps has appeared in every industry sector from manufacturing to marketing.

Even with this growth, there is plenty of room to grow for machine learning. A recent survey by MIT Sloan has shown that less than a third (23 per cent) of businesses have adopted any level of machine learning automation, and of those who have, only five percent are using it extensively.

However, things already look to be changing, with sectors such as cybersecurity, healthcare, retail and oil and gas pushing ahead with implementations. And of course financial applications. Globally, banks and financial institutions are using AI-based system to prevent fraud and money-laundering. Most of the customer-facing units in worldwide financial organizations use chat bots and robot customer service representatives to handle the routine customer management tasks.

What does this mean for business analysts? Are data scientists going to eliminate the need for them? Organizations have been utilizing a data science team for years. They typically consist of statisticians, technologists and business subject matter experts to collectively solve problems and provide solutions. No longer being hid in the backroom, data scientists are now the superstars in the business world.

Big data can be thanked for this paradigm shift. It has made their role an imperative in today’s corporate organization. The demand for data scientists who possess a deep understanding of advanced mathematics, system engineering, data engineering and domain expertise, has never been higher.

What can business analysts do? It is important for business analysts to remain relevant to remain an integral part of shaping and growing the future of a company. They will need to either adapt their skills or choose another career path. A shift is occurring in which companies are no longer using business analysts to determine what the future of a business looks like, but looking to data scientists to use machine learning and data mining techniques to discover new product trends and patterns that will create a more accurate picture of what the future holds and where the business is going.

The way the business world operated a decade ago is much different than the way it does today and even more change is on the horizon.

Melody K. Smith

Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.