AI transcription technology was already making significant strides in accuracy and efficiency. However, I don't have information about developments that may have occurred after that time. Nevertheless, I can speculate on some potential directions the future of AI transcription might take:

1. Improved Accuracy: AI transcription systems will likely continue to improve in accuracy due to advancements in machine learning techniques, larger and more diverse training datasets, and fine-tuning models for specific domains or accents.

2. Real-time Transcription: The future might see real-time transcription becoming more seamless and instantaneous. This would have applications in live events, meetings, interviews, and more, allowing for immediate access to transcribed content.

3. Multi-Language Support: AI transcription systems could become more adept at transcribing multiple languages accurately and simultaneously, facilitating global communication and collaboration.

4. Contextual Understanding: Future AI transcription systems might better understand context, idiomatic expressions, and nuances in speech, resulting in transcripts that are more coherent and accurate in conveying the intended message.

5. Customization and Domain Specificity: AI transcription tools could become more customizable and adaptable to specific industries or domains, such as legal, medical, or technical fields, where specialized vocabulary and jargon are prevalent.

6. Emotion and Intention Recognition: AI might evolve to not just transcribe words, but also recognize emotions, tones, and intentions in speech. This could provide more meaningful insights from transcripts.

7. Enhanced Speaker Differentiation: AI could better differentiate between multiple speakers, even in cases where there is overlapping speech, making it easier to attribute statements to specific individuals in a conversation.

8. Integration with Other Tools: AI transcription might become more tightly integrated with other tools like summarization, translation, sentiment analysis, and content management systems, creating a more comprehensive solution for managing spoken content.

9. Privacy and Security: As AI transcription involves processing sensitive information, there could be a stronger focus on ensuring the privacy and security of transcribed data, including better encryption and access controls.

10. Human-in-the-Loop Systems: While automation is essential, AI transcription systems might increasingly involve human reviewers or editors to ensure higher accuracy, especially for critical content.

11. Accessibility: AI transcription could play a pivotal role in improving accessibility for individuals with hearing impairments, making content more inclusive and available to a wider audience.

12. Ethical Considerations: As AI transcription becomes more powerful, there might be increased attention to the ethical use of this technology, addressing concerns about data privacy, bias, and potential misuse.

Remember that these are speculative ideas, and the actual future of AI transcription will depend on a combination of technological advancements, societal needs, and regulatory considerations. For the most accurate and up-to-date information, I recommend looking into recent industry news and reports.