AI education is broken, how do we solve it? Individuals end up learning a specific tool or tactic in a vacuum. They are missing the real-world applicability and collaboration that is critical to building impactful AI solutions in line with the organization’s strategy.
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It’s an exciting time to be involved with analytics and AI. Much like the software boom of the early 90s, many organizations are approaching a new generation of technical capabilities, empowering teams and driving digital transformation in ways only previously imagined.
While there’s a handful of mature AI-centric companies in the market, most organizations seem to be lagging behind. The good news is that with this gap comes an influx of online educational opportunities for learning the necessary technical skills to build AI solutions. Options range from free educational content on video platforms like YouTube to massive open online courses (MOOCs) like Udemy or Coursera, which require a monthly fee. There are even long-term online bootcamps designed to help individuals change jobs and advance their data & analytics careers.
Although these options may refine the technical skills of individuals in data-centric roles, most miss the mark in teaching the skills necessary to successfully enable and scale AI across a broader organization.
AI education is broken. You may be thinking this claim is pretty bold, especially since there are hundreds of free options available for data, analytics and AI education online. But when you take a closer look, it becomes obvious that the training being offered has a few concerning limitations.
On top of that, without a motivating factor to complete a course and make a change in a certain timeframe, the priority to sit down and learn is just not there. When leaders expect their students to find the time outside of work, training eventually gets deprioritized and teams don’t end up seeing an impact from their investment in training.
How do these limitations impact a team looking to implement and scale AI? Individuals end up learning a specific tool or tactic in a vacuum. They are missing the real-world applicability and collaboration that is critical to building impactful AI solutions in line with the organization’s strategy.
With all the options available for analytics and AI training today, don’t forget the necessary skills outside of specific tools and lines of code. Technical skills are important, yes, but so much more is needed to successfully enable and scale AI across your organization.
Rehgan Avon is the co-founder & CEO of AlignAI, an AI adoption platform that helps organizations mature their AI capabilities faster through process-oriented education. With a background in integrated systems engineering and a strong focus on building technology to support analytics and ML, Rehgan has worked on architecting solutions and products around operationalizing machine learning models at scale within the large enterprise.
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