Manual vs. AI: We Timed How Long It Takes to Create a Course (The Results Will Shock You)

The race between human expertise and artificial intelligence is no longer theoretical. In the world of eLearning, speed can be a decisive factor, especially for organizations under tight deadlines. But speed is not the only metric that matters. We conducted a time trial between manual and AI-assisted course creation to see how long each method takes, and the results were surprising in more ways than one. Understanding the Stakes Course creation is a complex process. It involves instructional design, content research, writing, multimedia integration, and quality assurance. Traditionally, this work is done manually by instructional designers, subject matter experts, and multimedia specialists. With the arrival of AI tools that promise to generate entire courses in minutes, the temptation to automate has grown. The stakes are high. A faster development cycle could mean quicker onboarding for employees, faster product training for customers, and more competitive offerings in the eLearning market. But the wrong approach could lead to poor engagement, misinformation, or compliance failures. The Experiment We set out to measure how long it would take to create a 60-minute online course using two different approaches:

1. Manual creation: A professional instructional designer working with standard tools such as Microsoft PowerPoint, Articulate Storyline, and Adobe Creative Suite. Research and writing were done from scratch using trusted sources.

1. AI-assisted creation: A generative AI platform capable of producing course outlines, scripts, and multimedia suggestions from a simple text prompt.

We kept the topic consistent: “Cybersecurity Fundamentals for Small Businesses.” This ensured both methods were working with the same scope and complexity. Timing the Manual Approach The manual process began with research, compiling credible sources, and outlining the course structure. This took approximately 8 hours. Writing the scripts for each module took another 12 hours, including revisions. Multimedia design, including slide creation, graphics, and basic animations, consumed 10 hours. Quality assurance and editing added 4 hours. In total, the manual approach required 34 hours of work. That’s nearly a full week for one person working standard business hours. Timing the AI Approach The AI process started with a single prompt outlining the course topic, target audience, and desired length. Within 90 seconds, the AI generated a course outline. Scripts for each module were produced in under 5 minutes. Multimedia suggestions were ready in less than 2 minutes. Even accounting for human oversight—fact-checking, minor editing, and adjusting tone—the AI approach took only 3 hours from start to finish. Most of this time was spent verifying accuracy and ensuring compliance with cybersecurity best practices. The Shocking Result On raw speed, AI outperformed manual creation by a factor of more than 10. Thirty-four hours versus three hours is a staggering difference. However, speed alone does not tell the whole story. Quality and Accuracy When reviewing the AI-generated course, we found several issues. Some statistics were outdated. A few definitions were oversimplified to the point of being misleading. The AI also suggested multimedia assets that were either generic stock images or inappropriate for the context. The manual course, while slower to produce, had fewer factual errors and was tailored more precisely to the target audience. The instructional designer was able to incorporate industry-specific examples, compliance considerations, and nuanced explanations that AI could not fully replicate. Engagement and Learning Outcomes We tested both courses with a small group of learners. The manual course scored higher in engagement and comprehension. Learners appreciated the real-world scenarios and interactive elements that the manual designer had built in. The AI course felt more generic, and while it was clear and structured, it lacked the depth that encourages deeper learning. Cost Considerations On paper, AI-assisted creation is cheaper. Fewer hours mean lower labor costs. However, the hidden costs of AI can be significant. Time spent fact-checking and correcting AI output can add up, especially for complex or regulated topics. There’s also the risk of reputational damage if an AI-generated course contains errors. The manual approach has higher upfront costs, but it produces a more reliable product. For organizations where accuracy and compliance are critical—such as healthcare, finance, or legal training—the manual route may be worth the investment. Scalability AI shines in scalability. Once the process is refined, multiple courses can be generated quickly. This is ideal for organizations that need to produce large volumes of training material in short timeframes. Manual creation struggles to match this speed, especially with limited staff. However, scaling AI-generated content without strong oversight can lead to a proliferation of low-quality courses. The McKinsey report on automation warns that while technology can replace certain tasks, higher cognitive skills—like judgment and creativity—remain essential for quality outcomes. Human Judgment vs Machine Efficiency AI tools are powerful, but they lack the lived experience and contextual understanding of human experts. As one developer noted in discussions about AI replacing frontend developers, AI can handle structured logic well but struggles with nuanced design decisions. The same applies to instructional design. AI can produce a skeleton quickly, but humans fill it with substance. Potential Risks The rise of AI in course creation also raises risks. Over-reliance on AI could lead to skill erosion among instructional designers. If professionals spend less time on deep research and pedagogical design, their ability to create high-quality content manually could diminish over time. There’s also the issue of bias. AI models are trained on existing data, which can embed biases into the course content. Without careful review, these biases can go unnoticed and perpetuate misinformation. The Future of Course Creation The future is likely to be hybrid. AI can handle the heavy lifting of initial drafts, outlines, and basic multimedia suggestions. Humans will refine, adapt, and ensure accuracy. This approach combines the speed of AI with the quality assurance of human expertise. Organizations should develop workflows that integrate AI without sacrificing quality. This means setting clear standards for fact-checking, compliance review, and audience customization. It also means investing in the skills of instructional designers so they can leverage AI effectively. Practical Recommendations For teams considering AI-assisted course creation, here are some practical steps:

• Use AI for initial drafts, but always review and edit thoroughly.

• Train staff on how to prompt AI effectively to get better results.

• Maintain a library of verified sources to cross-check AI output.

• Implement quality assurance protocols that include subject matter expert review.

• Monitor learner feedback to identify areas where AI-generated content may fall short.

Our experiment showed that AI can create a course more than ten times faster than manual methods. But speed is not the only metric that matters. The manual course was more accurate, engaging, and tailored to the audience. The AI course was faster and cheaper but required significant oversight to meet quality standards. The real shock is not that AI is faster—it’s that the best results come from combining AI’s efficiency with human judgment. In the race between manual and AI course creation, the winner is a balanced approach that respects both speed and substance.