Learning AI is only half the equation: Are we learning to use it responsibly?

We are already using AI in more ways than we realize

For one person, using AI might mean opening ChatGPT and asking a few questions. For another, it might mean using AI throughout the day to analyze financial information, build forecasts, research, create dashboards, develop processes, draft communications, recruit, automate workflows, or support business decisions.

And then there are people using AI every day who may not even think of themselves as AI users. That is because AI is increasingly embedded in the tools we already use: accounting platforms, CRMs, Microsoft and Google products, search engines, recruiting platforms, marketing software, and countless other business applications.

So when we tell businesses and employees that they need to “learn AI,” I think we are leaving out an important part of the conversation. We should not just be learning how to use AI. We should be learning how to use it responsibly.

AI literacy is more than prompting

There is enormous attention right now on learning how to write better prompts, automate tasks, and get more productivity from AI. Those things matter. But true AI literacy should also include understanding the questions behind the tool.

• What information are we giving the AI?
• Where does that information go?
• Can it be used to improve or train models?
• How long is it retained?
• Could another person review it?
• What happens when we connect AI to another business application?
• Are we using a consumer account or a business or enterprise product?
• What policies should our organization have around AI use?

The stakes change when AI touches business information

Those questions become especially important when AI moves beyond writing an email or brainstorming ideas and begins touching financial information, employee data, customer information, contracts, or other confidential business information.

One of the biggest misconceptions about AI privacy is assuming all of these tools operate under essentially the same rules. They do not. Even within the same platform, the rules can differ depending on your account type, settings, connected applications, and how you use the product.

The examples below are not a ranking of the safest AI platforms. They summarize privacy controls and distinctions the providers themselves publish so readers know what to investigate in their own accounts.

Privacy policies and product settings change frequently. This article reflects publicly available information as of September 2026; always review the provider’s current privacy documentation before making business decisions.

Claude

Claude allows consumer users to control whether their chats are used to improve its AI models. Users can turn off “Help Improve Claude,” preventing new chats and coding sessions from being used for future model training. Claude also offers Incognito chats that are not used for model improvement.

Anthropic makes a separate distinction for its commercial products, including Claude for Work and its API: customer inputs and outputs are not used for model training by default.

ChatGPT

ChatGPT users can turn off “Improve the model for everyone” under Data Controls. When it is turned off, conversations can remain in chat history, but new conversations are not used to train OpenAI’s models. ChatGPT also offers Temporary Chats, which are not used for model training.

An important distinction for businesses: ChatGPT Business, Enterprise, and Edu, as well as OpenAI’s API offerings, do not use customer inputs and outputs for model training by default.

Microsoft Copilot

Signed-in consumer Copilot users can control whether their conversations are used for generative AI model training.

Microsoft also makes an important distinction between its consumer Copilot experience and organizational Microsoft 365 environments. Microsoft 365 Copilot Chat provides enterprise data protection when a user signs in with a qualifying work or school account, and Microsoft says those prompts and responses are not used to train foundation models.

Perplexity

Perplexity also distinguishes between consumer and enterprise use. Consumer users can review and change the AI data-retention control associated with their account. Enterprise customers are automatically excluded from AI training data collection.

The important lesson is not to assume the default settings match your expectations simply because you recognize the product name.

Gemini

Google’s Gemini privacy documentation deserves careful reading by anyone using it with confidential information. Google explains that a subset of conversations can be reviewed by trained human reviewers to improve its services. It advises users with Keep Activity enabled not to enter confidential information they would not want a reviewer to see or Google to use to improve its services.

Google provides controls for this, including its Keep Activity setting and Temporary Chats. Temporary Chats are not used to train Google’s AI models, and future chats are not used to improve its models when Keep Activity is off and the user does not submit feedback. Google still retains those chats with the account for up to 72 hours to provide and protect the service.

That does not make Gemini “unsafe.” It demonstrates exactly why understanding the tool and its settings matters.

There is no simple “safest AI” list

I would be cautious about anyone declaring one AI platform completely safe and another unsafe. Privacy depends on more than the company name on the screen. It depends on your settings, your account type, what information you are sharing, what applications you have connected, and how you are using the tool.

A consumer account used to brainstorm social media ideas presents a very different risk profile from an AI agent with access to company email, cloud storage, customer information, and financial systems.

AI agents change the conversation

We are moving quickly from AI that simply answers questions to AI that can take action. AI agents can potentially search email, access documents, interact with business systems, research information, update workflows, and perform multi-step tasks.

That is incredibly powerful. It also means businesses need to think beyond, “What information am I typing into this chat?” The better question becomes, “What information and systems have I given this AI permission to access?”

That is a governance and internal-control question—not simply a technology question.

Before you give AI business information, ask these questions

Before uploading financial statements, employee information, customer information, contracts, or other confidential data into an AI platform, take a few minutes to understand:

• Is my information used to train AI models?
• Is model training turned on by default?
• Can I opt out?
• How long is my information retained?
• Could conversations be reviewed by humans?
• What happens to information accessed through connected applications?
• What permissions have I given an AI agent?
• Does a business or enterprise account provide different protections?
• Does my company have guidelines about what employees should—and should not—put into AI?

Responsible AI does not mean avoiding AI

I am a huge advocate for AI. I use it extensively because I have seen how much it can improve analysis, efficiency, research, decision-making, and the way businesses operate. The answer is not to become afraid of AI. The answer is to become better educated about it.

Businesses went through similar learning curves with cloud computing, online banking, SaaS applications, and remote work. We learned that adopting technology and controlling technology have to happen together. AI should be no different.

The businesses that benefit most from AI will not necessarily be the ones that adopt every new tool first. I believe they will be the organizations that figure out how to combine innovation with good judgment, appropriate controls, and responsible use.