The Leap of AI-Human Interaction in the Context of LLM: Comparing 2025 with 2024

2024: A Turning Point for LLMs

Shortly before 2024 and even in early 2024, the concern of many experts and developers was how to understand about correct use of AI tools and LLMs. Along with this global concern, others thought that this fast-paced technology was a great opportunity to establish startups and invest heavily in them.

Another group, mainly social theorists and humanities experts, tried to work on this question :

“How can humans interact with GPTs”, while their concern about the importance of human-AI interaction seemed reasonable, they raised questions about the mode of interaction, the type of interaction, and the emotional variables affecting human-technology interaction.

What was and is most remarkable among all was the unprecedented speed of the emergence and evolution of large language models. This speed exceeded all the questions and challenges considered by experts, to the point that at the end of the new year and the last days of 2024, raising better and more practical questions about how to guide the human thought process and guide the human user by LLMs in the form of a dynamic coexistence.

The evolution from “assistant” “to “mentor “

Predictably, 2025 will also time for significant developments in the dimension of dynamic interaction between human and LLMs.

As you have been seeing in 2024 varieties of large language Models emerged, providing significant assistance to humans, to the point that many articles and technology experts selected the names “assistant” and “partner” to large language models. However, at the same time, these services still included pre-programmed responses. In addition, despite the efforts of various businesses in producing AI startups around the world, mainly in the United States, China Japan, and some European countries, the focus of AI tools was on healthcare, education, finance, and consumer services. So, they seldom were used in other industries.

Nevertheless, the developments at the end of 2024 the quantitative growth of LLMs on the one hand, and the expected expectations of a qualitative leap on the other hand, strengthen the prediction of more interesting developments. In other words, we can now see artificial intelligence in the context of LLMs becoming more specialized and having more dynamic interactions with humans. Going beyond the education and healthcare industry and including other industries and areas.

Instead of predetermined and specific answers, it will have more multifaceted and broader answers to human needs and questions and will be more personalized than ever.
There’s, the word “mentor “can better describe the roles than assistant and partner!

Some of the reasons for changing the name of the LLM systems from “assistant “to “mentor “in the coming year are:

– Key Features of 2025 LLMs

1- Emotional understanding

In 2024, language models were based on text clues and tones, while in 2025, it seems that multi-analysis including text, audio, video, or even deeper emotional impressions will be possible.

2- Feedback style

In 2024, responses were “reactive “and based on immediate inputs and seemed to lack thought and cognition. In the coming year, feedback from large language models can be advanced and progressive and strengthen the development of the emotional intelligence of users. In other words, they will be more “reflective “rather than reactive.

3- Context awareness

You, as a user of LLM, have experienced that when you ask for specific information about an article or a researcher, it gives you a specific answer and this answer may not even be durable. That is, when you ask the same question again, it gives you a different answer. This indicates shallow and non-durable information. In next year’s language models, it is expected that the level and duration of the requested information will be slightly longer and that users will be given coherent information based on previous information history.

4- Role in Empathy

As mentioned earlier, large language models were passive information partners that provided predefined scenarios to users and applicants. The terms “partner” and “assistant” have been used many times to describe their role.
For example, sometimes ask them for information that we do not currently have and that we urgently need to perform a specific function. LLMs remind us of the answer in the fastest time from the information store and our “puzzle “is solved because a piece of the puzzle was not available in our short-term memory and we probably found that piece and solved the puzzle with the help of our super-advanced partner.

On the other hand, this process can be even more advanced, meaning that instead of passively calling out a predefined answer, a response based on the user’s emotional state and feelings is issued.

This is empathy because it can transform the role of the AI from a passive assistant who only calls out the missing link in the puzzle and solves the puzzle to the role of a “mentor” who guides the user towards the goal with empathy and emotional support.

5- Collaboration-based connection

Probably you have also had the experience of using AI tools to perform or complete a task such as composing a piece of music, writing a letter or a targeted request, or designing a specific decoration. It quickly answers each of your questions and at the end asks whether the information it has provided in this way was sufficient or not. If you ask for more information again, it will still be responsive like a hardworking and tireless assistant. If it does not know enough about your question or request, it will respond with an apology.

This is a collaborative approach to LLM systems. But recently, significant advances in AI systems promise new changes.

Therefore, it is possible and predictable that in the next few months, for example, request for help to complete a project, it will not only guide you to the end of the task but also witness the system’s effort to bond and cultivate long-term collaboration and build trust in you. This effort to encourage the user is evidence of the change in the position of artificial intelligence from “assistant” to “mentor”.
You are right, “the interaction between humans – and technology is becoming easier because this collaboration will change from a dry and reactive to a reflective state. Therefore, what started in the last months of 2024 will gain strength in 2025.

7- Application Areas

As mentioned above, the major industries that applied AI last year are healthcare, education, finance, and customer service. Among these, education and healthcare were and are ranked first. However, as users’ knowledge expands and AI’s capabilities increase in guiding personal and professional performance, it seems that more industries will accept the dominance of AI and apply these technologies as non-human assistants and even mentors.

Conclusion

Last year, the world of technology faced rapid developments in artificial intelligence systems, so that LLMs were nicknamed “human assistants” in many industries. Considering the developments of the last months and days of 2024, it is not far-fetched the majority of companies will accept applying these technologies, and even AI will become a “mentor” in the context of LLM. This mentor doesn’t mean to replace humans, but rather an intellectual technology that responds to users’ requests and can dynamically guide their performance.

This guidance seems to rely on two-way collaboration, emotional elements, and other components mentioned in the article. Undoubtedly, these are all personal predictions that have arisen from studying past trends and logic, and we need to see what will happen in the first months of 2025.