Here we are in the last months of 2025, three years since the introduction of Generative AI tools to the public. As the initial wave of excitement settles, it’s time to examine the true impact on various sectors.
Aside from the huge hype surrounding this new technology, it is important to see beyond the buzz. More specifically, it is important to see the real “value” that is generated in different areas.
The past year has been full of innovation, revealing how technology still acts like a catalyst for transformation. We’ll explore the real-world applications, unraveling the ways in which both individuals and businesses are currently use Generative AI.
From obvious creative endeavors to more surprising use cases, we will go through the current state-of-the-art. What transformations have been sparked, and how are sectors worldwide adapting to this powerful force?
In this new era, it’s evident that major tech companies are at the forefront, trying to prevent being left out of apparent technological revolution. And with heavy investments, the boundaries of possible applications are pushed every day.
We will also touch on the obvious worker’s questions in the face of such technological advancement:
- Is my job at risk?
- Does my career path need adaptation?
So, buckle up as we navigate through the new landscapes of many industries and peek into the diverse areas that are currently reshaped.
Obvious Industries in the Crosshairs of Generative AI
Let’s start with sectors that are clearly going to change. In fact these areas have already changed, as generation of text or images is the core of the following sectors.
Content Creation
In the world of creative writing, journalism or blog posting, generative AI tools have been employed to draft articles, make content, and even assist in ideation. The ability to understand context, structure coherent sentences, and adapt to different writing styles bring high value to not only to write more articles, but it helps with unstucking the creative block and produce higher quality texts.
There is no question that writing any text is already heavily influenced at the moment, but there might be some downsides to consider:
- While these algorithms seamlessly help to produce articles, blogs, and even social media posts, the internet can eventually be flooded with generated text without any fact-checking. Every journalist and content creator should not forget that these tools are “just” sophisticated word generator and their output requires verification.
- Another issue can be a so called homogenization in content – in other words all articles and blog post can become very similar. Diversity in voices and perspectives, a cornerstone of vibrant storytelling, might be overshadowed by a standardized, AI-influenced narrative.
But even with possible downsides, generative AI definitely bring a lot of advantages to content creation. Helping with formulating ideas, improving grammar and unstucking creative block, these tools possibly allow to start writing even people that would never start without it. This sector will never be the same.
Art and Design
In the domain of graphic design and visual arts, generative AI tools are taking creativity to new heights. These tools allow anyone to generate unique and captivating visuals by simply inputting textual descriptions. The result is a fusion of human intent and AI creativity, producing visual content that push the boundaries of many visual field.
One of the most amazing aspects definitely lies in how simple it is to use these new tools. Artists and designers, whether seasoned professionals or amateur creatives, can create stunning images with very simple text description.
Just look what is generated by Bing on such a simple prompt like: “Create an image of a house nearby water. The house is nicely decorated with Christmas lights. The weather is snowy and the house can be seen in reflections from wavy waters.”
With such a simple description, we receive almost photorealistic image, exactly satisfying the desired scene and the whole process took only seconds to complete.
The efficiency of visual creators has therefore increased probably more than 10-fold times. While the resulting images are sometimes not ideal, they can still be used for producing new ideas and speed up the creative process.
Artists and designers now find themselves immersed in endless possibilities, trying various new prompts and styles, with the ability to witness results immediately. This iterative process of trying out various combinations allows rapid exploration and refinement of ideas.
Creators are not positioned to be replaced, but rather use these tools to enhance their artistic touch. The algorithms can bring unexpected suggestions, generate variations, and introduce novel elements, while artists steer the creative direction.
The digital visual world is no longer restricted to those with extensive technical skills. The accessibility of new tools is unprecedented and image generating tools like DALL·E provide us with capabilities that would look like magic only a few years ago. Anyone can experiment with art and design effortlessly.
Education
If we marveled at the swiftness with which the internet provides information in the last two decades, generative AI brings this process into new dimensions. Not only is it possible to ask about traditional encyklopedic records, but you can use it to provide clarifying explanations and tutoring help, adjusting to individual student needs.
The accessibility of information is no longer limited by the time it takes to search and retrieve data. With new tools, we have access to interactive, dynamic educators that can present complex topics in a way that resonates with learners.
One of the main benefits is definitely the endless patience that extends to learners. While human instructors can only provide a limited scope of individualized attention, the integration of tools like ChatGPT brings tireless software assistants that answer every question with incredible patience.
As the educational landscape is redefined, schools are faced with the necessity to adapt. The traditional model of education, with its reliance on standard assessments and homework assignments, is not going to work anymore, because students armed with generative AI can complete tasks and assignments within seconds.
However, this shift presents an opportunity to elevate education to new heights rather than a call to replace teachers. Educators can also take this technological advantage and transform classrooms into novel learning environments, becoming guides and mentors that navigate students through the vast expanse of available information.
On the other hand, it is crucial to acknowledge that while generative AI is a powerful tool, it can make mistakes. Fact-checking remains a necessary step, especially in educational settings where accuracy is paramount.
Software Development
One of the fields that is already undergoing a thorough transformation is software development. It is an obvious sector to undergo change, given that software code, at its core, is text — making it an ideal candidate for the training generative AI tools.
At the moment, the biggest change comes with the so-called copilots – new collaborative coding helpers, assisting developers by providing suggestions that help with various code related assignments.
With copilots, the result is more streamlined, efficient, and this new coding process empowers developers to focus on higher-level problem solving, rather than focus on syntax and other code details. The developers’ focus shifts from ‘how’ a task should be done, to ‘what’ should be done.
While the capability to code large and complex applications entirely through generative AI is not yet possible, one of the already utilized examples is simple script generation. Developer can provide description of a task in plain language like: “Generate a Python script that takes 2 files, concatenates them and saves to folder.” And you receive well formatted code, even with clarifying comments that explain it, in just a few seconds. Imagine how much faster does coding become:
import os
def concatenate_and_save(file1_path, file2_path, output_folder):
try:
# Read the content of file1
with open(file1_path, 'r') as file1:
content1 = file1.read()
# Read the content of file2
with open(file2_path, 'r') as file2:
content2 = file2.read()
# Combine the content of the two files
combined_content = content1 + '\n' + content2
# Ensure the output folder exists
os.makedirs(output_folder, exist_ok=True)
# Determine the output file path
output_file_path = os.path.join(output_folder, 'combined_output.txt')
# Save the combined content to the output file
with open(output_file_path, 'w') as output_file:
output_file.write(combined_content)
print(f"Content from {file1_path} and {file2_path} successfully combined and saved to {output_file_path}")
except Exception as e:
print(f"An error occurred: {e}")
# Paths to the input files and the output folder
file1_path = 'file1.txt'
file2_path = 'file2.txt'
output_folder = 'output_folder'
# Call the function to execute the script
concatenate_and_save(file1_path, file2_path, output_folder)It is quite possible that eventually the whole coding process will be completed by AI, similarly as text, images, and video generation in content creation.
However, there is one caveat that needs to be solved. While traditional content creation allows for flexibility and minor errors, the precision demanded in coding makes any mistake unacceptable. The responsibility for code accuracy and the identification of bugs remains in human hands.
So until a robust framework is established where AI can be held accountable, developers don’t need to worry about their jobs and they can use new copilots to improve their coding experience.
But one day, developers can easily become obsolete, as only machines might do the coding.
The Next Wave: Industries that are next in line
While the previous section was about sectors that are already undergoing big changes, the following industries are not yet disrupted. But with the current direction, they might be next in line.
Gaming
Similarly to software development, gaming is already affected by Generative AI tools that help with creation of video game assets – various elements used to construct the virtual environment.
However the true revolution is probably yet to come, as there are multiple areas that can highly benefit from these new tools. Here are a few possible usecases in the future of gaming:
- Generating the entire game world based on designer’s description. This is the most ambitious use case, which as presumably far in the future.
- Adaptive Gameplay: Player behavior can be analyzed in real-time, tailoring gameplay experiences to individual preferences and skill levels.
- Intelligent non-playable characters (NPCs) that exhibit more realistic and dynamic behaviors. The main challenge at the moment comes with memory of what happened and what didn’t as player interacts with NPCs.
- Personalized Storylines: With smart usage of Generative AI, dynamic and branching narratives based on player choices can be introduced, which would be a big change for the traditionally linear gameplay experience.
It looks like a huge change is inevitable for gaming industry in many areas of game development, but only if the potential is fulfilled.
While generating game assets is already assisted by copilots, the creation of entire games is unrealistic at the moment.
Entertainment media
In the traditional sector of entertainment media, encompassing TV series, films, music, and other consumption sources, the big changes are also yet to come. While technically also part of content creation sector, entertainment is much harder industry to disrupt.
There is a big difference between generating a few sentence for social media sites or blog post, and creating script for the first season of dramatic TV series or a new feature film. And even if Generative AI was capable of writing the whole script perfectly, there are, at the moment, many other parts of film making that need to be done by people.
But still, there are many areas for potential changes in scriptwriting, ideation, musical composition and visual effects. One of the potential innovation is creation of digital twins for actors. These digital counterparts, generated through sophisticated algorithms and deep learning, offer new possibilities for seamless integration of actors into virtual environments.
Obviously, clear rules must be established to prevent abuse of actors’ appearance. Just like many other areas in new technological transformation, ethics have to be priority.
As we envision the future of entertainment, it might be possible that entire films, encompassing scriptwriting, soundtrack composition, and visual creation, might be crafted by AI algorithms.
And if we push our imagination one step further, we can ask: could personalized filmmaking be the ultimate destination? Instead of browsing through streaming services or TV programs, people would simply describe what they want to see and the film would be generated to them. While it is an exciting idea where the boundaries between audience and creator might blur, it is still in distant future.
Healthcare
When we get out of entertainment industry, another sector that might be revolutionize by Generative AI is healthcare. One of the main issues why it is not yet going through massive changes can be that it is a domain traditionally characterized by strict regulations, which causes obstacles to any transformation.
Nevertheless, numerous areas within the healthcare domain hold substantial potential for improvement through the integration of generative AI, by offering innovative solutions in diagnostics, treatment planning, and personalized medicine. Disease detection can be more accurate, treatment more effective, and patients can have better overall experience.
But there are many more areas that can be transformed that the expected application like advanced diagnosis from images. One of the most surprising is not advanced data processing, but communication with patients.
Physicians tried to use ChatGPT to write a script aimed at helping them to communicate more compassionately with patients. The resulting script was genuine and empathetic, leaving doctors amazed by its authenticity and the impact it had on elevating their conversations. Who would have thought that AI can improve empathy in doctor-patient communication?
Another area with high potential for improvement is doctors’ administrative tasks. Streamlining appointment scheduling, automating routine paperwork, and optimizing medical documentation processes can free up a substantial amount of physicians’ time, allowing them to concentrate on more valuable aspects of patient care.
It is necessary to remind that in healthcare, the necessity for safety, privacy, and ethics is even more critical than in other fields. But even with that necessity on our mind the main question remains: Can we afford to deny the potential for enhanced care through the incorporation of advanced technologies?
The potential benefits in terms of improved healthcare industry are enormous, but the changes cannot be forced without thoughtful considerations.
From Bytes to Empathy: Industries are Transforming
In this post, we went through the sectors that either already has changed, or their transformation is more than likely. From obvious applications like text generation for articles to much more surprising uses as adding empathy to communication in healthcare industry, there is no doubt that Generative AI is reshaping today’s world.
Only a few example areas were mentioned and there are definitely many more fields that are going to be revolutionized. So, if we get back to the question from beginning “Is my job at risk?”, your 9-to-5 might not be taken over by AI as simply as some pessimists think.
If you notice your industry evolving under the influence of Generative AI, staying ahead of the curve by learning how to integrate it into your daily tasks could be a smart move.
Currently, advanced algorithms won’t replace your job, but another person who knows how to use these advanced algorithms might take it.
What do you think about these various AI applications? Which industries do you think will be affected next? Let me know in the comment section below!
