The impact of AI on the role and work of instructional designers

AI technology does already simplify and accelerate the process of designing online training courses today. This trend is expected to continue. However, can AI completely replace instructional designers?

The debate about “human vs machine” is widely discussed, exploring which professions will be replaced by AI completely and which tasks will be transformed. We also thought about the extent to which AI can take over the work of conceptual designers. We did a lot of research, looked at various providers and tools, and made comparisons.

The current impact of AI on designing online trainings

AI already has a noticeable impact on the design of online training courses. Numerous companies and platforms use AI-powered tools and algorithms to enhance efficiency in content creation and improve the quality of their learning materials. AI is being applied in the following areas:

Information research:

AI tools can assist in content research by accessing and comparing various sources and consolidating the results. This enables instructional designers to gain a comprehensive overview of the topic.

Didactic concept:

AI can provide valuable support in creating a didactic concept for online training courses. It can help to structure the content into chapters and modules. The more detailed the information provided to the AI, the more precise the outcome will be.

Designing tasks and methods:

AI tools can suggest and create learning content and corresponding methods based on the learners' needs and the desired learning objectives. By analyzing extensive data and patterns, AI can determine the most effective types of tasks and interactive elements to achieve specific learning goals. It can also consider individual learning needs and preferences, proposing personalized tasks to enhance learner engagement and motivation.

Repetitive tasks:

Repetitive tasks, such as compiling learning materials, generating, formatting, and proofreading texts, can be taken over by AI tools. This allows instructional designers to focus on more complex and creative aspects of their work, such as designing interactive exercises, developing use cases and practical applications, or creating inspiring learning environments.

Personalization:

Data analysis enables informed decisions in content development. AI tools can search large amounts of data, identify patterns, and make predictions to assist in personalizing learning content. This empowers instructional designers to create customized learning programs that are tailored to the individual needs and learning styles of learners.

Quality assurance:

Another essential aspect is ensuring the quality of learning materials. AI can detect and correct grammar and spelling errors, check content consistency, and even analyze text comprehensibility. This allows instructional designers to ensure that the created learning materials are of high quality and provide learners with an optimal learning experience.

Training communication:

Effective communication is crucial for successful training. AI tools can support by designing marketing strategies and generating tailored texts for various communication channels.

An outlook into the future

The influence of AI on designing online training courses will continue to grow. Here are some potential developments:

Advanced personalization:

With the increasing availability of learning and user data, AI models can offer even more precise recommendations and personalized learning paths. Learning content will be further aligned with individual learners' needs and preferences.

Adaptive learning systems:

AI-powered tools enable the development of adaptive learning systems that adjust to learners' progress and understanding. Based on real-time data, AI systems can provide targeted feedback, additional materials, or alternative explanations to enhance learning outcomes. Instructional designers will increasingly create adaptive learning paths that automatically adapt to individual learning progress.

Chatbots and virtual assistants:

AI-powered chatbots can provide immediate support to learners, addressing their questions or issues. They can also serve as virtual assistants, offering personalized learning support and feedback. Instructional designers will define the role of such learning assistants and plan their integration into training concepts.

AI-driven feedback systems:

Furthermore, AI tools can provide learners with personalized feedback that goes beyond automated responses. For example, they can detect learners' emotional states or their understanding of the training material, and respond accordingly. Instructional designers will analyze which type of feedback is most effective for learners and how AI tools can help to deliver this feedback. They will define learning goals and content and determine which information from the learning process should be used to provide feedback.

Automated content development:

While AI tools are already used in content creation, generating texts, videos, or graphics, in the future, AI could go beyond that and decide which content format should be used at each stage and generate it directly. This would further increase efficiency, allowing instructional designers to focus more on strategic planning.

Advanced analytics and predictions:

AI enables more precise analyses to predict learning outcomes, derive personalized learning and action recommendations, or provide real-time feedback to learners.

Continuous integration of new AI technologies:

Instructional designers need to continuously familiarize themselves with new technologies and AI tools. This requires a willingness to learn and the ability to adapt quickly to new workflows and tools. Knowledge of different AI applications and their potential uses is crucial to fully exploit the technology's capabilities. Depending on the use case, it is necessary to identify the appropriate AI tool and evaluate its result.

It is important to note that ethical and social aspects must be considered in all these developments. It is the responsibility of instructional designers and companies to ensure that AI tools are used transparently, fairly, and without discrimination.

Conclusion

AI offers enormous potential and, when used correctly, can accelerate and improve processes. The tasks of instructional designers are evolving accordingly. They will be responsible for direct customer communication, ensuring that customer-specific goals and desires are met. This includes tasks such as collecting customer briefings, filling in missing information, feeding relevant data to AI tools, and ensuring quality.

However, human expertise and creativity will continue to play a vital role in ensuring that learning content is engaging, motivating, and didactically valuable. Striking the right balance between AI-assisted automation and human ingenuity will be crucial in creating the best learning experiences.

As with any other profession perceived as being "threatened" by AI, the key is to adapt to technological changes, recognize their potential, and overcome the fear of change.