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Back in 2012, the learn-to-code movement arrived. The demand for complementary skills in many industries promised alternative sources of income together with a comprehensive experience, including soft skills like creative thinking, problem-solving, and critical judgment.
As some of you probably remember, the don't-learn-to-code movement came soon after. The backlash from experienced programmers and educators might have seemed malicious, but, emotions aside, their points were quite reasonable:
I have worked with some excellent managers, people who were not only good at what they did, but also had great leadership potential. Sadly though, these managers didn’t invest in their own growth. They were so busy attending to the daily demands of the management job — putting out fires, resolving production issues, solving for customer escalation, moving from one delivery timeline to another — that they failed to build the skills required to become a great leader someday.
Like many managers in their position, they kind of assumed that by doing their job fairly well and staying in it for too long, they will automatically earn the leadership title. And I don’t blame them for this kind of thinking. For years, we have seen leaders rise through the ranks of the corporate ladder who had no business to be in those positions. When you see examples of bad leadership all around you, it’s kind of easy to assume you can be a leader too — after all, you consider yourself better than them. If they can be in those positions, you can be too. If they can jump through a fire hoop, you can jump too.
Most businesses are now very familiar with technologies like big data analytics, artificial intelligence, and machine learning. Executives have poured over case studies and performance statistics to better understand how these technologies can improve their products and services as well as improve efficiencies and reduce costs associated with their own internal processes and operations.
It is true that there are companies using these technologies, but not as many as you might think based on the benefits that these technologies can bring. A recent survey by RELX asked 1,000 senior executives with companies across the United States for their thoughts and plans regarding AI/ML and data analytics. 88 percent of the executives responding to the survey agreed that AI, ML, and data analytics would help their businesses be more competitive. However, when asked how many had actually implemented these technologies, only 56 percent said they had. As for future plans for increasing the use of AI, ML, and data analytics, only 18 percent said they planned to increase spending on these technologies moving forward.
When HackerRank released its Student Developer Report last year, there probably weren’t too many devs out there surprised by the fact that more than half of all developers are largely self-taught, with almost 30 percent being entirely so. As the report explains, “computer science programs lag behind the pace at which technology evolves, [so] for skills that are growing in the industry today, students have to rely on self-teaching to learn.”
And as this piece from CIO explains, machine learning skills are among the most coveted by today’s tech companies. Unfortunately, however, “demand continues to outpace the supply of qualified talent for these emerging skills.”