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Writer's pictureSophia Stone

Beyond Design: Why Instructional Engineers Are the Future of AI-Driven Learning

Updated: Sep 18


Do you remember your first time using ChatGPT? Mine was a simple request: help me write a speech. The first draft came up several pages too short. When I asked ChatGPT to expand, it produced a longer second draft, but it lacked substance. We were getting closer to a final product but still had a lot of work ahead of us. What we needed in our human-AI partnership was direction: someone to prompt the tool with prescriptive commands that it could understand and respond to.

 

In the years since, I've seen organizations and clients respond to the rise of AI in various ways—from developing in-house tools to shifting entirely to AI-driven content creation to banning generative AI completely. But it's clear that the future is coming, and that future is going to see unprecedented growth in AI-powered L&D. To meet this demand, we need instructional engineers.


 

 The Dual Potential of AI

I'm not the first (or the second or the third) to write about how AI is reshaping the landscape of L&D. Its impact can be felt in two primary areas: the speed and quality of content creation, and the design of intelligent, personalized learning experiences.

 

1. Faster, better, more content creation


With the help of AI, instructional designers can generate content faster, produce more of it, and create higher-quality content. Here are some ways that I leverage AI as an instructional designer:


2. Intelligent learning experiences

 

Beyond content creation, AI is also transforming how learners interact with learning experiences. Here are some examples:



 

Challenges of AI Integration

Embracing new technology has redefined the landscape of L&D time and again, making learning more accessible, user-friendly, engaging, cost-effective, and scalable than ever before. The integration of AI is the most exciting development I've seen in my own career. However, it's also fraught with ethical questions, data privacy issues, technical challenges, and the risk of low-quality AI-generated content flooding the market.

 

To ensure AI benefits learners, the next generation of instructional designers needs to use it responsibly, understand its capabilities and limitations, and keep learning principles central to design. What we need are instructional engineers.


 

 

Instructional Engineering

The future of instructional engineering is in skilled prompt engineering and quality assurance, leveraging and partnering with AI to generate high-quality content. Prompt engineering can be thought of a sophisticated form of automation that involves crafting precise instructions to guide AI in generating the desired content.

 

Much like software engineers, instructional engineers:

  • Rely on clear specifications to develop the product

  • Use a structured approach that breaks down complex tasks into smaller components

  • Use precise language and syntax to communicate their instructions

  • Identify and correct errors or inconsistencies in their instructions

  • Prioritize user-friendly and intuitive experience design

 

Feature

Instructional Engineer

Software Engineer

Relying on clear specifications

Defines learning objectives and outcomes, outlines course structure, and defines assessment criteria

Defines software requirements, creates functional specifications, and outlines system architecture

Using a structured approach

Breaks down learning content into smaller, manageable units

Divides software development into phases

Using precise language and syntax

Crafts effective prompts to guide AI in generating content

Uses programming languages, syntax, and coding conventions to write software code

Identifying and correcting errors

Reviews and refines AI-generated content to ensure accuracy, relevance, and alignment with learning objectives

Tests software for bugs, errors, and performance issues

Prioritizing user-friendly experience

Designs engaging and effective learning experiences that leverage AI to meet the needs of learners

Creates intuitive and user-friendly interfaces that are easy to navigate and use

 

Instructional engineers combine the skills of instructional designers with a deep understanding of AI. While AI literacy and technical chops are increasingly important, soft—or human—skills are in the highest demand for L&D professionals.


 

Human skills with the highest growth rates from October 2022 to October 2023 among L&D professionals globally (LinkedIn Workplace Learning Report 2024)

 


As AI automates more routine tasks, soft skills like empathy, communication, and creativity become more valuable in the workforce. These skills help us build relationships with stakeholders, empathize with learners' needs, develop innovative ideas, communicate effectively on a team, and adapt to changing priorities.

 

The AI revolution in L&D is still in its infancy. While it's hard to say what advances are on the horizon, for now I'm going to continue experimenting with AI, staying savvy with my data, and talking to humans to keep my soft skills . . . soft.

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