Office AI use is rapidly increasing.
The problem is that there are too many tools. ChatGPT, Claude, Gemini, Copilot, Perplexity, Grok. That is six just by name. Each has a free version and a paid version. Some generate images, some write code, and some can read an entire 100-page PDF. Even when given the same question, different tools return different answers.
It is only natural for people to say, “I don’t know what to use where.” When people repeatedly get wrong answers because they chose the wrong tool, distrust grows.
This article sorts AI by type and organizes the best combinations for office work situations.
Editor’s note
OpenAI unveiled GPT-6 Astra on the 3rd (local time). Anthropic released Claude Fable 5.1 on the 1st of this month. Google launched Gemini 3.8 Flash on the 2nd. It is the third model in six weeks, following 3.6 on July 21 and 3.7 on August 13. In May, it also introduced Gemini Spark, a 24-hour assistant. Microsoft 365 Copilot has used GPT-5.6 as its default model since July 9.
The three companies are making the same claim: this is no longer AI that answers questions, but AI that does the work. OpenAI said GPT-6 Astra can fill out online forms, fix customer relationship management records, and schedule appointments. Anthropic embedded a browser in the Claude desktop app “CoWork,” allowing web tasks to be delegated to it. Google says Gemini Spark searches Gmail, Docs, and Sheets to draft text on a user’s behalf.
Tools keep multiplying and names keep changing. In the office, the question comes up again: “So what should we use?” When people repeatedly get wrong answers because they chose the wrong tool, distrust grows.
The 기준 for choosing AI has changed
Just a year ago, AI was chosen in two broad categories: general models that answered quickly, and reasoning models that spent time thinking step by step. OpenAI’s “o” series was the classic reasoning model.
That distinction is fading. OpenAI retired o3 from ChatGPT on the 26th of last month. In the current ChatGPT model selector, there are names like GPT-5.6 Sol, GPT-5.5 Instant, and GPT-5.4 Thinking. Within the same GPT line, “Instant” answers right away, while “Thinking” takes time to reason before responding. Anthropic has also added an “effort control” feature to the Claude app, letting users choose how long the model should think without changing the model itself.
So today, AI is best understood in three layers.
The first is the chat layer. It answers immediately when you ask a question. Drafting emails, summarizing, translating, and refining wording all belong here. It is fast and inexpensive.
The second is the reasoning layer. You turn on “thinking” mode within the same tool. It is used for tasks where errors are unacceptable, such as comparing contract terms, checking calculations, or finding logical flaws. It is slower and more expensive.
The third is the agent layer. The AI opens a browser, fills out forms, and moves files by itself. GPT-6 Astra, Claude CoWork, and Gemini Spark are targeting this layer. It is used when you want to hand over repetitive work wholesale. However, because the AI performs real actions using your account, it requires the greatest caution.
There is also AI beyond generative AI. Predicting next month’s demand from past sales, identifying suspicious transactions among thousands of deals, and automatically classifying customer inquiries are tasks handled by predictive and classification AI. Excel forecasting sheets and CRM churn prediction scores in systems like Salesforce are examples. They are less visible, but already in use in offices.
Tool strengths by category
ChatGPT is highly versatile. It handles writing, coding, image generation, and file analysis in one place. OpenAI said GPT-6 Astra completed tasks 47% faster than earlier models in computer-operation evaluations. It also has the broadest range of connections to automation services such as Zapier and Make. Its weakness is long documents. When context becomes too long, it can miss earlier parts.
Claude is strong at writing and long-document handling. At the launch of Opus 4.8, Anthropic said the model is better at flagging uncertainty and less prone to unsupported claims. Fable 5.1 is a top-tier model, so additional credits are required under the Pro plan. Its weakness is that it cannot generate images.
Gemini is integrated with Google Workspace. It moves between Gmail, Drive, and Sheets. Gemini 3.8 Flash can be used in Google Sheets from the day it is released, and Google says its performance for finance and legal tasks has improved. With a 1-million-token context window, it can read hundreds of pages in one go. Gemini Spark gets a dedicated email address and watches the inbox around the clock. However, Spark is still available only to subscribers of the top-tier AI Ultra plan. Its weakness is that it loses power outside the Google ecosystem.
Microsoft 365 Copilot lives inside Word, Excel, PowerPoint, and Outlook. Its strengths are meeting-note summaries, email drafts, and Excel formula generation. For companies already using Microsoft 365, there is no need to open a separate window. Its weakness is cost. Copilot is added on top of the Microsoft 365 subscription fee.
Perplexity specializes in search. It attaches sources to its answers. It is suited for work where fact-checking is important, such as market research and competitor analysis. It is not ideal for long-form writing.
Personal subscription prices are similar. ChatGPT Plus, Claude Pro, and Gemini AI Pro are all around $20 per month, or about 29,000 won. The difference is not price, but what you use them for.
How to combine tools by task
Writing reports. Start with Perplexity or Gemini Deep Research for research, gathering facts with sources attached. Put that material into Claude and have it draft the first version. Turn on “thinking” mode again to review the numbers and logic. For tables and charts, ChatGPT’s file-analysis feature is fast.
Email. If you use Microsoft 365, Copilot is the fastest. It summarizes incoming emails, drafts replies, and schedules appointments. If you use Google Workspace, Gemini plays the same role. In the end, using the tool that does not require opening a separate window is what people keep using the longest.
Reviewing long documents. When extracting conditions from a contract or rulebook of hundreds of pages, Claude or Gemini is the right choice. Both can read long documents all the way through. In this case, you must turn on “thinking” mode. Missing a single clause can be costly.
Data analysis. Uploading an Excel file to ChatGPT lets it build pivot tables and draw charts. In Google Sheets, Gemini can write formulas. But forecasting next month’s demand is more accurately handled not by generative AI, but by Excel forecast sheets or BI tool forecasting features. Predictive AI produces the numbers, and generative AI turns those numbers into report text—that is the right division of labor.
Meetings. Before a meeting, ChatGPT or Claude can organize the agenda. During the meeting, recording tools such as Clova Note transcribe in Korean and separate speakers. After the meeting, summaries and action items can be handed back to generative AI.
Repetitive work. Tasks like visiting the same website every week to collect numbers and organize them into a table, or sending the same-form email to ten clients, should be delegated to the agent layer. GPT-6 Astra Agent, Claude CoWork, and Gemini Spark are aimed at such work. However, a person should watch for the first few runs.
The key to combinations is breaking work into steps
The difference between people who use AI well and those who do not is not the tool. It is whether they break work into stages.
If you ask, “Write a report for me,” in one shot, any AI will produce something thin. “Analyze last month’s sales data” is step one. “Summarize three causes from the analysis” is step two. “Write this as a two-page report for the manager” is step three. Breaking it down like this changes the result. Attaching the right tool to each step takes it one level higher.
A public-first survey released by Google Korea on the 27th of last month points in the same direction. Office workers who used well-crafted prompts saved three times more time than those who used basic prompts. Even with the same tool, the way you ask determines the result.
There is another caution with agents. The AI performs real actions using your email and account. If it receives the wrong instruction, it can send the wrong message. At first, it is safer to give it read-only access and keep a human approval step for sending and payment. Confidential company data should be handled only in enterprise plans approved by the company. Enterprise plans do not use input data for training, but free versions generally do not offer that guarantee.
It is also risky to use AI output as-is. Generative AI can produce plausible but incorrect information. Fact-checking is the human’s job. It is safest for AI to draft and humans to verify.
There is no universal tool. Even with three new models released this month, the principle remains the same: ask questions of chat, verification of reasoning, and repetition of agents. The combination is the answer.