Where Will Data Science Be In The Next Ten Years?

Technology is an ever-changing field. As a greater percentage of businesses and industries turn toward science and data to streamline and innovate their processes, the need for data science will only increase simultaneously.

But there is concern that this innovation, particularly the rise of AI, threatens the future of data science as a profession. So, will AI replace the need for data science completely? And will the trend of using data scientists to implement the methodology end?

Is AI a threat to data science?

The question of whether AI will reduce the need for jobs is not limited to the world of data science. As technology becomes a larger part of everyday life, there has been an increase in the use of AI to streamline the way people access and interact with information. Note the appearance of automated systems appearing in nearly every avenue of business.?

What many are missing when considering the increasing use of AI in our lives, is the parallel increase in the need for human interaction with these systems, whether for maintenance, interpretation, or implementation of results.

How will data science survive the rise of AI?

Let's look at a few reasons data science will continue to be necessary and possibly in higher demand over the next ten years.

Creation and Maintenance of AI systems

The use of automation in industry has already proved beneficial in many aspects, and there's no reason to believe that will change anytime soon. However, who is driving the targeted creation and maintenance of these automated systems and models? Data scientists.

Analyzing and interpreting the data

Having the ability to analyze data is helpful for industries and businesses of all kinds. They use this information for numerous reasons, from streamlining productivity to analyzing consumer trends. AI helps compile this data and uses machine learning to predict outcomes based on created models. But who analyzes this information and best directs it toward the needs of a particular industry or business? Who looks at the results of these models and identifies anomalies? Data scientists.

?Understanding and communicating results

The use of AI to organize and evaluate ideas and methodologies in industry will continue. But who will compile and rework that data into a useable block of information for business owners and industry leaders? Who will analyze, understand, and communicate results to those who will use them? Data scientists.

Will data science still be in demand in ten years?

There's no doubt that the future of data science is inextricably linked to advancing automation. But rather than seeing this as a threat to the field, it's more likely that data scientists will be able to use AI beneficially. The need for data science is growing, not shrinking. A greater number of industries, and even smaller businesses, recognize a need for someone to analyze the wealth of data created every day, and more importantly, find ways to use that data for their benefit.

There is an increasing need for data scientists with specialized skills targeted to a specific sector. And labor statistics show the number of skilled data scientists in the field is not keeping up with the growth and need for these jobs, even today. There's no reason to believe it will be any different in the next ten years. If the field of data science learns to adapt and grow along with technology, the use of data scientists will increase in both volume and value.