Why AI Training Fails in Companies? AIrkaiz Explains How to Choose 'Practical' Training for PR and Creative Industries

AIrkaiz Co., Ltd. (Headquarters: Kiyosu City, Aichi Prefecture; Representatives: Kaito Kobayashi, Kaito Sasaki) has released insights on why corporate AI training often fails to be utilized on the ground and how to choose training that actually integrates into business workflows. This is in conjunction with their 'Generative AI Designer Training' service for PR departments, video production firms, and the advertising industry.

While attention on generative AI is high, many workplaces face issues like 'training conducted but not applicable to real tasks,' 'only specific persons using it,' or 'tools introduced but not connecting to creative work.' In fields like PR and advertising where speed and quality are critical, just 'knowing' about AI is insufficient. The key is whether it can be brought to a usable state in actual operations.

AIrkaiz provides practical, workshop-centric AI training based on expertise from currently producing corporate ads and videos using AI.

### Why AI Training Fails to Stick
AIrkaiz identifies five main challenges:
1. **Focusing only on tool descriptions**: Training often fails when it doesn't show *how* to use tools in specific production steps.
2. **Lack of hands-on workshops**: AI skills are sensory and best learned by doing, especially in image and video generation.
3. **Mismatch with industry-specific tasks**: Generic training doesn't bridge the distance to specific PR or ad production requirements.
4. **Unclear post-training application**: If participants don't know what to use it for starting the following week, adoption stops.
5. **Instructors who don't use AI in professional production**: Knowledge is different from operational know-how in a commercial context where quality and client requirements are paramount.

### Three Points for Choosing AI Training
1. **Is the provider actually using AI for production?**: Expertise from those facing real-world creative challenges is more practical.
2. **Is there a high ratio of workshops?**: Skills are acquired through a process of output, feedback, and improvement.
3. **Is it tailored to industry-specific needs?**: Quality and speed standards vary significantly by industry.