eLearning Operators Should Prioritize Artificial Intelligence In Course Catalogs

eLearning Operators Should Prioritize Artificial Intelligence In Course Catalogs
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Summary: There's another technology that's developing and which may eliminate much of the demand for data analytics skills if current trends hold up. Here's what's happening, and what to expect.

Artificial Intelligence In Course Catalogs: Reasons Why This Should Be A Matter Of Priority

In the education industry, the last few years have seen an explosion in the type and number of data analytics courses on offer to students all around the globe. It's very easy to understand why: experts predict that demand for skills in that field will continue to skyrocket for the foreseeable future, which guarantees a steady stream of students signing up for courses. The problem, however, is that there's another technology that's developing that may eliminate much of that demand if current trends hold up.

This technology is Artificial Intelligence (AI), and like most other disruptive technologies, it has the potential to upend the current status quo in a number of industries. That's especially true in the field of data analytics. Some industry observers are already predicting a steep decline in the need for human data analysts in the coming decades. For those in the eLearning industry, that means the time is coming to shift focus away from data science coursework and towards programming and AI development. Here's what's happening and what to expect.

Where AI Stands Today

Believe it or not, AI development is much further along than many people realize. At the time of this writing, the technology has already become commonplace across a variety of industries and use cases. For example, AI is already able to reduce the complex task of pricing diamonds to a trivial matter that takes mere moments. It's also being used to detect signs of heart disease, and it already has a higher success rate than human doctors. If that's not enough, it's even helping chefs create tastier cuisine. The bottom line is that AI has already spread far and wide, and what we've seen so far is just the tip of the iceberg. The most recent estimates predict that almost one-third of the US workforce could be replaced by AI as soon as 2030, so the clock is already ticking.

Where To Focus Coursework

The good news for eLearning platform operators is that there is some significant overlap between today's data analytics skills, and the skills that will be needed to support the next phase of the AI revolution. That means operators won't have to overhaul their whole catalog to make the transition towards AI-related education going forward, and can gradually introduce more AI-specific courses as successors to deprecated data analysis courses. The topics that overlap the two areas of study include:

  • Machine Learning
  • Neural Networks
  • Mathematics: Linear Algebra, Statistics, Multivariate Calculus
  • Python Programming
  • Algorithm Development

In addition to the courses that overlap, it will also be necessary to begin expanding courses that are more specific to the latest in AI developments. Those courses include:

  • Natural Language Processing
  • Probability
  • Deep Learning
  • Reinforcement Learning
  • Bayesian Methods

Predicting The Shift

As we move forward, eLearning platform operators should begin to notice a pronounced shift in demand for coursework away from data analysis and towards AI beginning to take hold within the next two years. That's the period during which the first wave of purpose-built AI data analysis solutions should reach maturity and see adoption in real-world applications. It's impossible to tell how quickly AI will begin to displace human workers in the field, but even before it does, companies everywhere will begin to revise their hiring projections in their data operations to reflect their anticipated reduced need for human workers.

There's some evidence that we're already beginning to see a softening in demand for data analysis skills, especially for entry-level workers. While hiring for such positions remains robust, the average salary in the field has started to decline for the first time since the Big Data revolution began in earnest over five years ago. That points towards both a growing saturation in the market, as well as the beginnings of automation through AI starting to have an effect. In short, given the current climate, it's reasonable to believe that the shift towards AI and away from data analysis is already underway and that it will continue to gather steam in the near term.

Prepare To Transition

All eLearning platform operators should consider themselves on notice that the rapid advancements in AI technology have already begun to reduce the demand for data analysts, and they should begin to adjust their strategic plans and course offerings to reflect it. Those that don't, may miss the opportunity to secure a solid share of the market, which is sure to be a lucrative one. Fortunately, doing so won't require a radical realignment of resources or even a total platform overhaul, so it should be a relatively painless transition for those that undertake it in the near term.

Originally published on December 23, 2018