AI education isn’t just for those who want a career in tech

Key points:

• More employers require job candidates with some AI proficiency
• Neglecting to learn about AI is a major misstep in an AI-driven economy
• See related article: Colleges must intentionally teach critical-thinking skills
• For more news on AI in education, visit eCN’s Teaching & Learning page

AI literacy is becoming an increasingly pressing requirement in an AI-dependent world. The mandate for AI education extends not only to those in technical roles—programmers, engineers, and data scientists—but also to creatives and non-technical professionals who wish to remain competitive in the job market. LinkedIn data predicts a 65 percent shift in the skills employers will require by 2030 due to AI.

Prompt engineering is the number-one “job of the future,” according to the World Economic Forum. While AI-related, this role doesn’t involve fine-tuning machine learning algorithms or basic coding. Instead, prompt engineers develop, refine, and optimize text-based AI prompts for a business use case.

Despite the buzz surrounding this new profession, some experts predict it will soon go from a full-time role to a key competency required of all professionals—or what Harvard Business Review calls “problem formation.”

In other words, professionals must be able to:

1. Identify business objectives that can be solved using generative AI.
2. Break down complex problems into manageable bite sizes.
3. Interpret a problem from multiple perspectives.
4. Define the constraints of the problem.

Non-technical professionals are expected to use AI tools to boost productivity

Human-AI collaboration is increasingly commonplace at work, and the potential for generative AI-related automation touches nearly every industry. McKinsey research suggests that in 2023, 60-70 percent of worker activities can be automated by AI, up from 50 percent in 2018.

Already, customer service reps query massive knowledge bases using natural language to find answers to customer questions. Business intelligence analysts generate visualizations of sales data using AI-powered analytics software. Marketing specialists use email marketing software to automate end-to-end campaigns, and content creators save time with generative AI tools like OpenAI’s ChatGPT to generate rough drafts of emails, white papers, and social media posts. Other non-technical tasks that can be automated with AI include:

• Research and text summarization
• Language translation
• Customer service, through chatbots
• Basic data analysis
• Talent sourcing
• Marketing automation

Some 97 million new roles are estimated to emerge from the shift in the division of labor between humans and machines, according to data gathered by LinkedIn, Coursera, and the Forum in the Future of Jobs Report 2020.

Certain non-technical jobs already require AI knowledge

A growing number of employers require job candidates with some AI proficiency—likely because they will need to use it or at least understand its role in day-to-day business operations. For example, inventory managers use predictive analytics software to anticipate inventory requirements and evaluate supplier performance, even though their role isn’t “technical.”

Job postings on LinkedIn mentioning AI or generative AI more than doubled from 2021 to 2023, including positions like digital product manager and cybersecurity consultant. The report also found that 89 percent of global professionals were excited to use AI.

Meanwhile, enterprises are clamoring for increased AI adoption to maximize efficiency gains from process automation to data-driven decision-making. Over 75 percent of companies plan to adopt big data, cloud computing, and AI technologies within the next five years. However, AI implementation isn’t just about maximizing profits. From healthcare to transportation, AI has the power to save lives and solve critical global issues, such as cutting carbon emissions through fleet optimization and reducing errors in medical diagnostics. 

AI startups need non-technical talent

AI’s share of U.S. startup funding doubled in 2023 as investors sought to cash in on the generative AI craze fueled by the launch of OpenAI’s GPT-3 in November 2022. The AI boom creates opportunities for technical and non-technical roles. For example, conversation designers map pathways for user interactions with chatbots, while technical writers generate documentation for AI systems. Like any other industry, AI companies need project managers, accountants, sales reps, marketing specialists, and HR professionals. A background knowledge of AI and a deep understanding of the product is imperative to secure one of these coveted roles.

We must be aware of the AI algorithms that make decisions for us

While not everyone aspires to become a prompt engineer, the fact remains that neglecting to learn about AI—at least enough to understand its functions—leaves one ignorant of the “black box” algorithms that make major life decisions on our behalf. For example, AI software determines which candidates are selected for job interviews, who gets approved for a mortgage, and even the length of a prison sentence.

Researchers at the University of Georgia discovered that people are more likely to trust answers generated by an algorithm than those from their fellow humans. This is likely due to a general lack of awareness regarding AI bias and statistical uncertainty in AI-assisted decision-making. Understanding AI’s inner workings and how its inherent biases can seriously impact people’s lives is a complicated subject requiring constant academic inquiry, exploration, and training as the legal and ethical landscape evolves.

Digital upskilling requires an education curriculum that evolves with the technology

AI development is progressing so rapidly that higher education institutions are struggling to update their curricula to reflect the skills that employers need. In a recent survey by Salesforce, 70 percent of business leaders don’t believe their teams possess the skills to use generative AI effectively.

Students are equally eager to learn about AI: a recent survey found nearly half of students have heard of generative AI but don’t know much about it. Nearly all (96 percent) think learning how to use AI in the field they’re studying is important.

A modular approach to upskilling enables learners to acquire new competencies as demand emerges and stay ahead of new technologies. More importantly, it means learning from an agile education provider with an up-to-date curriculum informed by the latest industry trends, receiving mentorship from a seasoned industry professional, and emerging with a job-ready portfolio. While domain expertise is desirable, skillset diversification is critical in a world where the average number of skills required for an individual job has increased by 10 percent annually since 2017.

Finally, AI literacy concerns more than just data structures, algorithms, and statistical modeling. Education providers must teach the ethical and societal implications of AI–from job displacement to accessibility and privacy concerns. By providing a cutting-edge curriculum that moves at the speed of AI development, institutions empower the next generation of non-technical professionals to become AI-literate, with versatile skill sets and an “always be learning” mindset needed to thrive in any industry.

About the Author:

Colin Lumsden is an ed tech and higher ed executive with a 25-year track record of success in private companies and public universities. He is the VP of business development at Springboard, an online learning platform that prepares students for tech careers and partners with universities, including the University of California San Diego, University of Massachusetts, and University of Maryland.