I spent over 20 years as a technical trainer, delivering content on Windows Server, Linux, networking, cybersecurity and other practical system and network administration skills. My time included traditional, in-person classroom delivery and internet-based online live training.
I began authoring courseware and designing labs after leaving the training industry, which has given me a deeper appreciation for what course development entails.
To understand AI's full potential in technical training, instructors should separate AI use into two parts: one, as a tool for creating and delivering learning; two, as a necessary component of the curriculum itself, so students can learn to manage complex environments effectively.
This piece explores my thoughts on how AI affects technical training and curriculum design, including the following key takeaways:
AI is just another tool for trainers. AI won't replace curriculum authors, and it won't replace instructors. Trainers can embrace the advantages it provides within the learning experience while also considering its potential risks.
AI is a critical tool for modern administrators. As AI becomes increasingly essential for many technical roles, instructors should deliver thoughtful learning courseware and learning resources that explain AI technologies and how to use them within existing IT roles.
AI won't replace curriculum authors, and it won't replace instructors.
Damon GarnOwner, Cogspinner Coaction
AI can assist training delivery
As with nearly every other industry, technical trainers face dramatic headlines about being replaced by AI. Many IT learners, however, prefer human interactions for training. Sure, students can learn by reading and completing labs that simulate real-world environments, but nothing beats having an experienced, human trainer who's available to answer questions, rephrase explanations, provide examples and personalize the learning environment.
Instructors can view AI as similar to other revolutionary technologies: a tool. In educational settings, AI can provide context and information to supplement other equally essential mechanisms, such as labs and reading material.
Here are a few ways AI can integrate into training delivery:
Delivery improvements. Online collaboration technologies use AI to dynamically adjust performance settings, ensuring the highest-quality UX. For example, Zoom uses AI to optimize online collaboration experiences. It also offers an AI assistant, Zoom AI Companion.
Lab optimization. Online virtualized lab providers use AI to optimize performance, creating additional VMs and dynamically managing network traffic. Scaling environments offers the best performance and experience, balanced against cost and resource utilization.
Lab management. AI offers scoring opportunities, evaluating participants on their ability to complete specified tasks. AI also enables the personalization of lab activities, avoiding the time wasted on developing skills the user has already mastered.
Reviews. AI offers instructors an unparalleled opportunity to generate questions, quizzes and review materials, reinforcing the content delivered in class.
Classroom materials. AI can generate delivery resources. For example, AI can create images, network diagrams and other references. Generative AI enables instructors to create references based on student questions and examples, further personalizing the training experience.
All these approaches supplement the power of AI to research information or answer questions quickly. Whether it be custom AI chatbots or AI services like Perplexity, AI enables students and instructors alike to find information quickly.
AI can assist training development
AI offers data-driven design and delivery options, targeting learning to the specific skills gaps identified by the organization. These capabilities strengthen the standard approach of identifying skills gaps, transferring knowledge and supporting the learning process. The process relies on various components, including assessments, design and support.
Assessments
AI-powered assessments generate quizzes, hands-on activities and scenario-based exams that adapt to participant responses, enabling comprehensive and personalized assessments of an individual's skill.
The data extracted from these results can inform the development of efficient and effective learning plans. Post-learning assessments validate the training investment.
Design
AI has a significant effect on instructional design and curriculum development. Instructional designers can use AI to adapt materials to various learning styles and enable personalization, tailoring the knowledge transfer process to the participant's needs as identified by AI-driven assessments.
Delivery and support
AI also offers course designers new and unique delivery and support options. For example, AI chatbots can enable on-demand, contextualized support during the learning process, providing real-time answers to questions.
I appreciate how these options and opportunities enhance an instructor's ability to deliver exactly the knowledge the learner needs. I recall how challenging it is for an instructor to assess the knowledge and experience levels of various students and tailor training content to meet their needs.
I appreciate how these options and opportunities enhance an instructor's ability to deliver exactly the knowledge the learner needs.
Damon GarnOwner, Cogspinner Coaction
AI can assist training participants
We're still discovering the advantages -- and disadvantages -- AI can offer in education settings. AI benefits IT students similarly to how it helps other audiences, including in the following ways:
Accessibility options. AI can provide real-time captions, transcripts and content translation, including for live training sessions. It also optimizes text-to-speech tools for more accessible learning experiences.
Time savings. AI can save time when researching information, finding the answers to specific questions or documenting configuration procedures.
Natural language interaction.Natural language AI enables learners to phrase queries in a way that makes sense to them and receive helpful responses from chatbots or other tools.
Custom requests and queries. AI handles participant-specific requests effectively. Learners can request examples, diagrams or case studies based on criteria.
For example, imagine a learner trying to understand the TCP/IP stack, how its layers relate to each other and the concept of port numbers. Using a tool like Google Gemini, the student could enter a query like, "Generate an image of the TCP/IP stack, including protocols, port numbers and relationships between the layers."
The result would look like Figure 1:
Figure 1. Students can query AI chatbots to deepen their knowledge and understanding of complex technical topics.
I find such approaches to be effective for the learning process, and I encourage students to take advantage of these AI applications.
The risks of AI in education
Of course, learners might abuse AI or use it in counterproductive ways. AI also has its own set of flaws and limitations. Concerns that instructors should consider include the following:
Access equity. Not everyone has access to AI tools. In some cases, paid subscription structures can limit use.
Overreliance on AI. Students might rely on AI too much, impeding learning or generating a false sense of skill or exam readiness. Someone who relies on AI to find all procedures could struggle to accomplish daily tasks without it.
Restrictions and controls.Privacy, intellectual property and data sovereignty concerns can restrict access to AI tools.
Academic integrity. As seen in many industries, AI threatens ownership, originality and integrity. When learning environments require original material, such as case studies, research papers or scenario-driven essay questions, participants might be tempted to use generative AI rather than demonstrating their own knowledge and skills.
Technical education will increasingly need to cover AI technologies
Aside from using AI as a tool to aid in training development, delivery and participant experience, instructors must also consider that AI technologies will increasingly become a topic to cover within training.
Any discussion of skills development for today's IT operations staff must include AI. On-premises systems -- such as database servers, web application services and other infrastructure systems -- benefit from AI configuration and optimization. Cloud services are another candidate for AI-driven optimization. From monitoring to disaster recovery, AI helps cloud administrators manage single-vendor, hybrid and multi-cloud environments.
In other words, using AI to administer the physical and virtual infrastructures upon which businesses exist is crucial to any training plan.
AI is similarly essential for developer and DevOps roles. AI assistance in coding offers many advantages, including generating fresh code and conducting code reviews.
Technical trainers can embed advantages like these into training content, along with topics like AI ethics and privacy. It's equally crucial to emphasize the importance of using AI as a tool and not a crutch. Coding -- and many other technical skills -- is still complex and requires the intuition and creativity of humans.
Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to Informa TechTarget, The New Stack and CompTIA Blogs.
