These applications can save time, but they also introduce important privacy questions. What happens to information submitted to an AI chatbot? Can conversations be stored? Who can access uploaded documents? And how should businesses protect confidential data when employees use AI-powered tools?

Understanding AI privacy risks in 2026 is essential for consumers, professionals, and organizations adopting new technology.

This guide explains the most important concerns and provides practical steps to reduce unnecessary exposure without abandoning the benefits of AI.

Why AI Privacy Matters More Than Ever

Traditional software often requires users to enter information into clearly defined fields. Conversational AI is different because it encourages people to communicate in natural language.

Instead of selecting an option from a menu, someone might describe an entire business problem, paste a customer email, or upload a document for analysis.

That convenience can lead to accidental disclosure of information that would not normally be shared with an unfamiliar service.

For example, an employee might ask an AI assistant to summarize a confidential sales report without checking whether company policy permits the upload.

Another user might discuss personal finances, family circumstances, or medical information with a chatbot without reviewing its privacy settings.

These situations do not mean that all AI services handle information irresponsibly. They illustrate why users need to understand the policies and controls of each product.

What Information Can AI Tools Collect?

The information processed by an AI service depends on the application, its configuration, and the user’s actions.

Potential categories include:

• Text entered into conversations.
• Documents and files uploaded for analysis.
• Images, audio, or video submitted to supported features.
• Account and subscription information.
• Technical information such as device and connection details.
• Usage information needed to operate or improve a service.
• Information retrieved through connected applications.

Some products also provide memory or personalization features that can retain useful preferences or contextual details.

These features vary by provider and plan. Users should consult the current privacy policy and product documentation rather than assume that every AI tool uses information in the same way.

Risk 1: Sharing Sensitive Personal Information

One of the most common AI privacy risks comes from users voluntarily entering sensitive information.

Someone seeking help with a financial problem might paste bank account details. A person drafting a complaint could include another individual’s private information. An employee might upload a customer database for analysis.

Even when the purpose is legitimate, sharing unnecessary personal information increases exposure.

A safer approach is to remove identifying details whenever they are not needed for the task.

For example, if you want help rewriting a customer service email, the AI tool may not need the customer’s full name, home address, telephone number, or order number.

You can often replace those details with generic descriptions while preserving the information necessary for the writing task.

Risk 2: Uploading Confidential Business Documents

AI document analysis can be extremely useful. It can summarize reports, identify themes, compare information, and help employees understand complicated material.

However, documents may contain trade secrets, financial projections, employee information, customer records, or contractual details.

Before uploading business files, organizations should determine whether the AI service is approved for that information.

Important considerations include the provider’s data-processing terms, retention practices, access controls, and available enterprise security features.

Employees should not assume that a consumer AI account offers the same protections as an enterprise deployment.

Businesses should also consider whether uploaded information is subject to contractual confidentiality obligations or industry-specific requirements.

Risk 3: Conversation History and Data Retention

Many AI services provide conversation histories so users can return to previous interactions.

History can be convenient, but it creates questions about retention and access.

Users should understand whether conversations are saved, whether deletion controls are available, and whether removing a conversation from the interface has the same effect as deleting all associated records.

Some services may retain certain information for security, legal, or operational purposes, depending on their policies.

It is important to review the provider’s current documentation rather than assuming that pressing a delete button always results in immediate removal from every system.

Risk 4: AI Training and Secondary Data Use

Some AI providers may use certain categories of submitted information to improve their services, subject to the applicable product settings and policies.

Other products or plans may provide different contractual protections or data-use arrangements.

There is no universal rule that every conversation is used for model training, just as there is no universal guarantee that every submitted conversation is excluded.

Before using an AI service for sensitive tasks, review its data-use disclosures and available controls.

Businesses should pay particular attention to enterprise agreements, permitted processing purposes and restrictions on secondary use.

Risk 5: Connected Applications and Permissions

Modern AI assistants may connect to email, calendars, cloud storage, collaboration tools and other services.

These integrations can help users find information and complete tasks more efficiently.

However, connecting an application may allow the AI service to access information beyond a single conversation, depending on the permissions granted.

Before authorizing a connection, review the requested permissions and consider whether the integration is necessary.

For business environments, administrators should evaluate which applications employees may connect and whether access can be restricted to appropriate information.

Permissions should be reviewed periodically, especially when employees change roles or no longer need a particular integration.

Risk 6: AI Chatbots and Emotional Trust

Conversational AI can communicate in a friendly and personalized way. That makes it approachable, but it may also encourage users to share more than they intended.

In October 2026, actor and digital governance advocate Joseph Gordon-Levitt drew attention to concerns about the relationship between AI product design, emotional attachment, and corporate incentives.

His remarks highlight an important distinction: an AI chatbot may feel conversational without being equivalent to a trusted human professional.

Users should remain aware that the service operates according to technical systems and provider policies.

When discussing sensitive matters, consider whether the information is necessary to share and whether the tool is appropriate for the situation.

Read our article about Joseph Gordon-Levitt’s AI warning for more context.

Risk 7: AI-Generated Misinformation

Privacy is not the only concern. AI systems can also generate inaccurate or misleading information.

An AI assistant might produce an incorrect technical specification, misunderstand a document, or confidently describe something that is not supported by reliable evidence.

For consumers, this can lead to poor purchasing decisions. For businesses, inaccurate information may affect operations, customer communication, or internal reporting.

Important outputs should be verified using appropriate sources and human review.

Organizations should identify situations in which AI-generated information must not be used without additional checks.

How to Protect Your Privacy When Using AI

Users can take several practical steps to reduce privacy risks.

1. Share Only Necessary Information

Before submitting a prompt, ask whether the tool actually needs every detail.

Remove names, account numbers, addresses, and other identifiers when they are not essential.

2. Review Privacy Settings

Check the provider’s available controls for history, personalization, training preferences, and connected applications.

Settings can change as products evolve, so review them periodically.

3. Avoid Sharing Passwords and Credentials

Do not paste passwords, recovery codes, private encryption keys, or authentication tokens into ordinary chatbot conversations.

If a tool requires access to another service, use its supported authorization process rather than sharing login credentials directly.

4. Verify the Service Provider

Use legitimate websites and applications. Be cautious of unfamiliar services claiming to provide access to well-known AI models.

Review the developer, privacy policy, permissions, and available support information before uploading sensitive files.

5. Use Approved Business Tools

Employees should follow organizational policies concerning AI services.

If a company provides an approved enterprise AI environment, use it for authorized work rather than transferring confidential information to an unapproved personal account.

6. Limit Connected App Access

Grant only permissions necessary for the intended task and disconnect integrations that are no longer needed.

7. Review Outputs Before Sharing

AI-generated content can accidentally include sensitive details from the information supplied to it.

Check documents, summaries, and emails before sending them to external recipients.

AI Privacy Checklist for Businesses

Businesses adopting AI should develop a clear approach to acceptable use and data protection.

• Maintain an inventory of approved AI applications.
• Classify confidential and personal information.
• Define which data categories may be submitted to each tool.
• Review vendor privacy and security documentation.
• Require appropriate authentication and access controls.
• Evaluate retention and deletion practices.
• Train employees on safe prompting and document handling.
• Establish human review for important AI-generated outputs.
• Document how incidents and suspected disclosures should be reported.
• Review policies when tools or regulations change.

These controls should be proportionate to the organization’s size, industry, and the sensitivity of its information.

What Is the Difference Between Consumer and Enterprise AI?

Consumer AI products are generally designed for individual users, while enterprise offerings may include additional administrative, contractual, and security features.

Enterprise capabilities can include centralized user management, access controls, organizational settings and specific data-handling commitments.

However, an enterprise label alone does not guarantee that a service meets every organization’s legal or security requirements.

Businesses should evaluate the actual agreement, product configuration, and documented protections.

Can AI Run Locally Without Sending Everything to the Cloud?

Some AI models and features can operate on local hardware. Depending on the implementation, this may reduce the need to transmit certain information to external servers.

Local processing can provide additional control over data handling, but it does not automatically eliminate privacy or security risks.

Devices can still be compromised, software may have vulnerabilities, and applications may use cloud services for some functions.

Organizations evaluating local AI should consider hardware requirements, maintenance, access controls, and the specific capabilities of the chosen software.

Why Hardware Security Still Matters

AI privacy is not only a question of chatbot settings. The devices and networks used to access AI services also influence security.

Keeping operating systems updated, using appropriate authentication, and managing access to business devices can help reduce exposure.

Organizations handling sensitive information should also consider endpoint protection, encryption, and backup practices appropriate to their environment.

For businesses researching suitable hardware, Aztek Computers provides a catalog of computers, storage products, and other technology equipment. Product selection should be based on verified compatibility, security requirements, and workload needs.

Who Controls the Information Behind AI?

Privacy questions are closely connected to the broader issue of AI governance.

Model developers, service providers, businesses, and users may each have responsibilities concerning data collection and processing.

Understanding those responsibilities can help organizations evaluate contractual obligations and make informed purchasing decisions.

For a broader discussion, read Who Controls Artificial Intelligence?.

Final Thoughts

Artificial intelligence offers useful capabilities, but responsible adoption requires attention to privacy and data security.

The most effective approach is not to assume that all AI tools are unsafe or that every provider handles information identically.

Instead, users should understand what they are sharing, review the policies of the services they use, and apply appropriate safeguards.

For businesses, clear employee guidance, vendor evaluation, and regular review are essential parts of responsible AI adoption.

AI can be a valuable productivity tool when people remain informed about its limitations and maintain appropriate control over sensitive information.

Frequently Asked Questions

Is it safe to share personal information with AI?

Safety depends on the service, the information involved, and the provider’s policies. Avoid sharing unnecessary sensitive information and review privacy controls before submitting data.

Can AI chatbots store conversations?

Some services retain conversation history or other records. Retention practices vary by provider, product, and settings.

Does every AI company use conversations for training?

No. Data-use practices differ across providers and plans. Review the applicable documentation and available settings.

Should businesses allow employees to use AI?

Businesses can benefit from AI, but they should establish clear policies, approve appropriate tools, and protect confidential information.

Is local AI more private than cloud AI?

Local processing may reduce certain external data transfers, but privacy still depends on software design, security configuration, and how the system is used.

How can I reduce AI privacy risks?

Limit sensitive disclosures, review privacy settings, use trusted services, manage connected-app permissions, and verify important outputs.

His comments have attracted attention at a time when generative AI is becoming part of search engines, workplaces, creative tools, customer service and personal communication. AI can be useful, but its rapid adoption raises questions about accountability, privacy, ownership, and the public’s ability to influence decisions that affect them.

So what did Joseph Gordon-Levitt actually say about AI, and why does it matter to people who use these tools? Understanding his argument requires looking beyond dramatic headlines about robots and examining the companies, business models, and policies behind today’s AI products.

What Did Joseph Gordon-Levitt Say About Artificial Intelligence?

In an October 2026 video interview with The New York Times, Gordon-Levitt encouraged audiences to focus on the organizations creating and deploying AI rather than treating artificial intelligence as an independent villain.

His comments reflect a concern that decisions about the future of AI could become concentrated among a small number of companies with significant financial and technological resources.

Those decisions include what information AI systems are trained on, how products are designed, which safeguards are implemented, what users are encouraged to share, and how generated content is monetized.

Gordon-Levitt’s position is not that every AI application is inherently harmful. Instead, he argues that the public should question the incentives and accountability of organizations that increasingly influence how people communicate, work, and create.

Readers can watch the New York Times video featuring Joseph Gordon-Levitt for the original discussion.

Why Is Joseph Gordon-Levitt Speaking About AI?

Gordon-Levitt is known for acting in films including Inception and 500 Days of Summer, but his involvement with technology and creative collaboration extends beyond acting.

He founded HITRECORD, a collaborative creative platform, and has publicly discussed the relationship between technology companies and the people whose work gives those platforms value.

In 2026, he also took on a United Nations advocacy role focused on human-centric digital governance. The role involves raising awareness of how digital technologies affect people and encouraging public discussion about their development and oversight.

His background in creative industries is particularly relevant because generative AI can produce writing, images, audio and video using patterns learned from large datasets. This raises questions about the treatment of artists, writers, performers and other contributors whose work may be included in training material.

However, being a prominent actor does not automatically make someone a technical authority on machine learning. His arguments should be assessed on their evidence and reasoning, alongside research from computer scientists, economists, policymakers and privacy experts.

The Real Concern: Who Controls AI?

Artificial intelligence requires substantial resources. Advanced systems depend on computing infrastructure, specialized chips, large datasets, engineering teams, and ongoing investment.

These requirements can create advantages for organizations with access to capital, cloud computing and distribution networks.

When a small number of companies control important infrastructure, users and businesses may become dependent on their products. That dependence can influence prices, access to technology, privacy choices, and the availability of alternatives.

For example, a business might integrate an AI assistant into its customer support workflow. Over time, employees may rely on that assistant for answering questions, finding information, and creating reports. If the provider changes its pricing, privacy practices or product features, switching to another system could become difficult.

These concerns are not unique to AI. Similar questions have emerged around search engines, social networks, app stores and cloud platforms. However, AI may intensify them because it can become involved in a wider range of decisions and tasks.

For a broader explanation, read our guide to who controls artificial intelligence and why it matters.

Why AI Companies’ Business Models Matter

AI systems do not exist independently of the organizations that build and operate them. Their features reflect engineering decisions, commercial strategies, legal requirements, and organizational priorities.

Some AI products are sold through subscriptions. Others are integrated into larger software services or offered through enterprise agreements. Different business models can create different incentives.

A subscription provider may prioritize retaining customers and expanding paid usage. An enterprise provider may emphasize reliability, security, and administrative controls. A company offering a consumer application may focus on convenience, engagement or growth.

None of these incentives automatically makes a company irresponsible. The important question is whether commercial objectives are balanced with transparent policies, meaningful safeguards and user control.

Responsible product evaluation therefore involves more than asking whether an AI system gives useful answers. Users should also examine what data it collects, whether information is retained, what controls are available, and how the provider handles mistakes.

AI Chatbots and Emotional Attachment

One particularly notable part of Gordon-Levitt’s recent comments concerns the possibility that conversational AI products can encourage emotional attachment.

Modern chatbots can respond naturally, maintain context, and adapt their language to a user’s preferences. These features can make interactions feel comfortable and personalized.

For many people, conversational interfaces are simply convenient. They can help explain difficult subjects, organize thoughts, or provide writing assistance.

However, highly personalized conversations can also encourage users to disclose sensitive information. Someone who treats a chatbot as a trusted companion might share financial problems, workplace information, personal relationships, or other private details without understanding the provider’s data practices.

The potential risk is not that every chatbot deliberately manipulates users. It is that design choices affecting trust, engagement, and disclosure deserve careful examination.

Users should understand whether conversations are stored, whether they can be deleted, what memory features do, and whether submitted information may be used for additional purposes.

Our AI privacy risks guide explains practical steps for reducing unnecessary exposure.

What About Artists, Copyright and Compensation?

Gordon-Levitt has also emphasized the relationship between generative AI and human creativity.

AI models can generate text, images, music, and other material by learning statistical patterns from training data. That data may include human-created works, depending on the model and its development process.

This has prompted disputes about consent, licensing, attribution, and compensation. Some creators argue that companies should obtain permission or provide compensation when copyrighted works are used for training. AI developers and other stakeholders have advanced different legal and technical arguments concerning permitted uses of training data.

The legal landscape varies by jurisdiction and continues to develop. It would be inaccurate to suggest that every AI model uses the same datasets or that every training practice has already been determined lawful or unlawful.

For content creators, the practical questions include whether their work has been licensed, whether they can control certain uses, and how they should evaluate AI-generated material in their own projects.

These questions also matter to businesses that use AI for marketing, design and documentation. Organizations should consider intellectual property policies and review generated outputs before commercial use.

Is Gordon-Levitt Against Artificial Intelligence?

His recent remarks are better understood as criticism of concentrated corporate influence and inadequate accountability than as a blanket rejection of AI technology.

There are legitimate reasons to be optimistic about AI. It can assist with accessibility, research, software development, education, translation, and many other activities.

At the same time, useful technology can create risks when implemented without appropriate safeguards.

The two positions are not mutually exclusive. Someone can support advances in AI while advocating stronger transparency, privacy protection, and public oversight.

Gordon-Levitt’s argument encourages readers to separate the capabilities of a technology from the incentives of the organizations deploying it.

What Does Human-Centric AI Governance Mean?

Human-centric governance means designing and regulating digital systems around people’s rights, interests, and ability to make meaningful choices.

In practice, this can involve transparency about automated decisions, mechanisms for reporting harm, appropriate human oversight and clear responsibility when systems fail.

For example, an organization using AI to screen job applications should consider whether the system produces unfair outcomes, how candidates can challenge decisions and who is responsible for reviewing mistakes.

A business deploying an AI customer service tool should consider data protection, accuracy, accessibility and the circumstances in which a human employee should take over.

Good governance is not necessarily a demand that every AI decision require government approval. It is a framework for identifying risks, assigning responsibility and providing meaningful accountability.

How Could Stronger AI Oversight Affect Businesses?

Organizations adopting AI may face growing expectations concerning privacy, documentation, vendor evaluation, and responsible use.

For small and medium-sized businesses, this does not necessarily require creating an extensive compliance department. A practical starting point is to understand where AI is used and what information employees provide to it.

Businesses can establish clear policies for sensitive data, review vendor agreements, train employees, and define when human verification is required.

They can also avoid depending entirely on a single provider without considering alternatives and data portability.

These measures can improve operational resilience even when specific regulations do not apply.

What Can Everyday AI Users Do?

Consumers do not need to understand every technical detail of machine learning to make more informed choices.

• Review the privacy settings of AI applications before sharing sensitive information.
• Avoid entering passwords, financial credentials, or confidential workplace data into tools without appropriate authorization.
• Check important AI-generated claims against reliable sources.
• Understand whether an AI tool is intended for entertainment, general assistance, or professional use.
• Compare providers rather than assuming every AI product has the same policies.
• Use available controls for conversation history, personalization, and data retention.
• Pay attention to independent research and public discussion about AI governance.

These steps will not resolve every issue involving corporate power, but they can help individuals make more informed decisions about the products they use.

Why This Debate Matters Beyond Hollywood

Gordon-Levitt’s involvement has brought additional attention to issues that extend far beyond the entertainment industry.

AI is being integrated into office software, smartphones, search tools, creative applications, and business systems. The decisions made by AI developers can therefore influence millions of users who may never follow technology policy closely.

His comments provide an accessible entry point into a complicated debate: how can society benefit from powerful AI while ensuring that organizations remain accountable to the people affected by their products?

Answering that question will require contributions from researchers, companies, policymakers, workers, and users.

Final Thoughts

Joseph Gordon-Levitt’s warning about AI companies highlights a central challenge of the technology’s rapid growth: the importance of human oversight and accountability.

The debate should not be reduced to choosing between excitement about AI and fear of its consequences. AI can provide substantial benefits while still requiring scrutiny of how it is built, financed, governed and deployed.

For readers interested in understanding the broader issues, continue with our guide to AI ownership and corporate control and our practical AI privacy guide.

Frequently Asked Questions

What did Joseph Gordon-Levitt say about AI?

He warned that people should pay close attention to the companies building and controlling AI, including their incentives, influence, and accountability.

Why is Joseph Gordon-Levitt involved with the United Nations?

He has taken on an advocacy role focused on human-centric digital governance, encouraging discussion about the relationship between technology and people’s rights and interests.

Is Joseph Gordon-Levitt opposed to AI?

His recent comments focus on corporate accountability and the risks of concentrated power rather than arguing that all AI technology should be rejected.

What is human-centric digital governance?

It is an approach to technology policy that emphasizes human rights, transparency, accountability, and meaningful public oversight.

Why are AI chatbots a privacy concern?

Users may disclose sensitive information during natural conversations. Privacy risks depend on the provider’s policies, product design, and the information shared.

What can consumers do about AI risks?

Consumers can review privacy controls, limit sensitive disclosures, verify important outputs and compare the practices of different AI providers.