Senior Technical Specialist at a tech vendor with 5,001-10,000 employees
Real User
Top 5
Apr 13, 2026
Sometimes there is some difficulty while understanding the issue and the technical jargon, but otherwise it is all good. It is not a 10 for me because some features need to be improved on the technical jargon side.
There is a steeper learning curve for advanced agentic features that could be improved, and hallucinations should be reduced. The answers provided are long, which is impressive but not efficient for users needing rapid, crisp responses. Providing concise answers would improve the user experience. Google Gemini AI's UI code is too vague and the designs are not very appealing. Google Gemini AI can improve its UI code and address hallucination issues. The long answers provided can be tiresome to read, and the pricing is too high for individuals like me. These considerations led me to give a rating one point less than ten. Native GitHub or Vercel export could be integrated, and the context could be increased to over two million tokens. A simplified agentic setup for the UI could also help non-technical experts handle it more effectively.
Google Gemini AI is not used much because it does not appear to be as responsive or as effective as Alexa when responding to questions, queries, instructions, or commands. When in a room with Google Home Mini and a phone nearby, Google Gemini AI would interrupt or catch the command instead, resulting in an unexpected response. A strength that also becomes a weakness is that Google Gemini AI catches the command better than other Google digital assistant devices. Additionally, there is a slow response rate, especially when connecting a mobile phone to Android Auto.
Gemini can be improved in several ways. The ChatGPT platform is much more simple for getting started, whereas Gemini's initial setup is more difficult, particularly when using other services such as Document AI service. For Document AI services, there is a long drawn process involving installing the Google command-line interface, downloading the credentials, and configuring application access to those credentials. Microsoft Azure works through API calls, which means you download an API token, store it in your program, and start using it. With Gemini, it's a more tedious process. Though the facilities offered in Google Cloud Platform are extensive, one has to make a rigorous initial effort to get all of those things started.
I was thinking that now it is creating advanced images. In the same way, we could get video versions easily so it would be very helpful for people interested in video editing. If we give the scenario, it should try to create a story in video edition. I have not used that if it is already available.
Principal Data Architect at a computer software company with 201-500 employees
Real User
Top 5
Jul 9, 2025
The code generation capabilities in Gemini could be improved. When comparing it against Anthropic, they have better code generation capability. There are specific features that should be included in Gemini in the future. Code generation exists but sometimes debugging is not as good. For Google-related technology, it works very well, but for other code, it sometimes hallucinates.
Product Manager For Marketing And Strategy at a tech vendor with 10,001+ employees
Real User
Top 5
Jun 20, 2025
Google Gemini's biggest strength is also its drawback; it's excellent for generating reports and working with data in real-time, but it isn't the most creative LLM for tasks such as creating a digital storytelling campaign or crafting marketing messages.
There's a new release every two months and it's very fast. I would say that they should keep increasing the context size of information that we can provide. Going from 1 million to 10 million would be fantastic. The context size and improving creativity without hallucinating is very difficult to do, but I expect them to achieve that. I expect them to be more creative but still control the amount of hallucination.
Senior Consultant at a outsourcing company with 201-500 employees
Real User
Top 5
May 13, 2025
Areas that could be improved with Google Gemini include more up-to-date content, more flexibility, and quicker responses. This is probably everyone's complaint. If you start using some AI tools quite a bit, they can get a little slower.
There are ways to better enable and provide greater flexibility for experts to be more actively involved. Currently, it operates mostly autonomously, and while it provides structured activities, making the research configuration more accessible and flexible would be beneficial.
Director at a tech services company with 501-1,000 employees
Real User
Top 10
Mar 17, 2025
Google Gemini needs more accurate answers and the ability to export data to Excel or Google Sheets. Currently, I can only export to the Doc app in Google Workspace. Exporting presentations to PowerPoint or Google Slides is not supported.
Google Gemini AI integrates into Google Workspace for productivity, leveraging multi-modal capabilities to optimize tasks in text, image, and data handling. It balances cost and performance, enhancing operations through seamless real-time data processing and intelligent assistance.
Google Gemini AI is designed to enhance productivity through its integration with Google services, providing smart solutions for text writing, automated workflows, and image generation. It supports efficient data...
Sometimes there is some difficulty while understanding the issue and the technical jargon, but otherwise it is all good. It is not a 10 for me because some features need to be improved on the technical jargon side.
There is a steeper learning curve for advanced agentic features that could be improved, and hallucinations should be reduced. The answers provided are long, which is impressive but not efficient for users needing rapid, crisp responses. Providing concise answers would improve the user experience. Google Gemini AI's UI code is too vague and the designs are not very appealing. Google Gemini AI can improve its UI code and address hallucination issues. The long answers provided can be tiresome to read, and the pricing is too high for individuals like me. These considerations led me to give a rating one point less than ten. Native GitHub or Vercel export could be integrated, and the context could be increased to over two million tokens. A simplified agentic setup for the UI could also help non-technical experts handle it more effectively.
Google Gemini AI is not used much because it does not appear to be as responsive or as effective as Alexa when responding to questions, queries, instructions, or commands. When in a room with Google Home Mini and a phone nearby, Google Gemini AI would interrupt or catch the command instead, resulting in an unexpected response. A strength that also becomes a weakness is that Google Gemini AI catches the command better than other Google digital assistant devices. Additionally, there is a slow response rate, especially when connecting a mobile phone to Android Auto.
Gemini can be improved in several ways. The ChatGPT platform is much more simple for getting started, whereas Gemini's initial setup is more difficult, particularly when using other services such as Document AI service. For Document AI services, there is a long drawn process involving installing the Google command-line interface, downloading the credentials, and configuring application access to those credentials. Microsoft Azure works through API calls, which means you download an API token, store it in your program, and start using it. With Gemini, it's a more tedious process. Though the facilities offered in Google Cloud Platform are extensive, one has to make a rigorous initial effort to get all of those things started.
I was thinking that now it is creating advanced images. In the same way, we could get video versions easily so it would be very helpful for people interested in video editing. If we give the scenario, it should try to create a story in video edition. I have not used that if it is already available.
The code generation capabilities in Gemini could be improved. When comparing it against Anthropic, they have better code generation capability. There are specific features that should be included in Gemini in the future. Code generation exists but sometimes debugging is not as good. For Google-related technology, it works very well, but for other code, it sometimes hallucinates.
Google Gemini's biggest strength is also its drawback; it's excellent for generating reports and working with data in real-time, but it isn't the most creative LLM for tasks such as creating a digital storytelling campaign or crafting marketing messages.
There's a new release every two months and it's very fast. I would say that they should keep increasing the context size of information that we can provide. Going from 1 million to 10 million would be fantastic. The context size and improving creativity without hallucinating is very difficult to do, but I expect them to achieve that. I expect them to be more creative but still control the amount of hallucination.
Areas that could be improved with Google Gemini include more up-to-date content, more flexibility, and quicker responses. This is probably everyone's complaint. If you start using some AI tools quite a bit, they can get a little slower.
There are ways to better enable and provide greater flexibility for experts to be more actively involved. Currently, it operates mostly autonomously, and while it provides structured activities, making the research configuration more accessible and flexible would be beneficial.
Google Gemini needs more accurate answers and the ability to export data to Excel or Google Sheets. Currently, I can only export to the Doc app in Google Workspace. Exporting presentations to PowerPoint or Google Slides is not supported.
I do not have a special recommendation for improvement. It works well for my business.