AI Copyright Questions Are Now Your Business Problem

You may already be using AI to draft marketing copy, summarise documents, prepare customer replies, or create product descriptions. It is fast, convenient, and often useful. But if you are running a Malaysian SME, you also need to ask a less comfortable question: where did the AI learn from, and who owns the material it produces?

The legal debate is no longer limited to technology companies and authors. It affects agencies preparing client campaigns, retailers creating catalogue content, training providers producing course notes, and professional firms handling reports. A careless workflow can create disputes over copied text, confidential information, brand ownership, or whether your business has permission to use the output.

The underlying issue remains unsettled in many jurisdictions. Courts are examining whether training AI on copyrighted works is sufficiently different from copying them, whether the use competes with the original work, and how much human input is needed before an output receives copyright protection. The original analysis from TechCrunch highlights why business owners should treat AI use as a governance issue, not just a productivity shortcut.

TL;DR

AI-generated content is not automatically safe to publish, own, or sell. Use approved tools, avoid uploading third-party or confidential material without permission, keep records of human review, and check important outputs before they reach customers.

The safest approach is not to stop using AI. It is to create clear internal rules around source material, prompts, review, approval, and ownership.

What This Means

AI copyright discussions often combine several separate questions. First, there is the question of training: can an AI company use books, articles, images, code, or other protected works to build a model? Second, there is the question of output: does the response generated for you reproduce someone else’s protected material? Third, there is the question of ownership: can you claim exclusive rights over content that was created mainly by a machine?

These questions do not have one simple answer. Copyright rules differ between countries, and court decisions may address only a particular dataset, business model, or type of copying. The TechCrunch article describes a US court decision involving Anthropic in which the judge reportedly treated AI training differently from obtaining books through illegal shadow libraries. The reported settlement was US$1.5 billion, while the article also noted that the ruling considered some forms of AI training lawful.

That distinction matters to you. A tool may have been trained lawfully, but its response can still contain material that resembles a protected article, product description, photograph, code sample, or book passage. You should also remember that the tool provider’s terms may give you usage rights without guaranteeing that every output is free from third-party claims.

Fair use is another concept mentioned in the article. In the US, courts may consider the purpose of the use, the amount taken, whether the new work is transformative, and its effect on the original market. The article also discusses the Ross Intelligence case, where training on Thomson Reuters content to create a competing legal platform was found not to be sufficiently transformative. That example suggests a practical warning: using another party’s content to build a competing product creates greater risk than using AI for internal drafting and review.

Useful rule of thumb: AI can assist your work, but you remain responsible for checking whether the final work is accurate, authorised, original enough, and suitable for its intended use.

How This Applies to Malaysian SMEs

Marketing agencies and service businesses: You may ask AI to write a Facebook caption, landing page, email campaign, or proposal. The risk increases when you prompt it with a competitor’s website, a client’s paid report, or a published article and ask it to “rewrite” the material. Even if the wording changes, the result may follow the original structure too closely. Instead, provide your own facts, brand guidelines, target audience, and approved claims. Ask for several original alternatives, then have a staff member edit the final version.

Retailers, manufacturers, and distributors: Product listings often contain specifications, safety information, supplier descriptions, and photographs. AI can help organise this information, but it should not invent certifications, warranty conditions, ingredients, performance claims, or compliance statements. Keep the original supplier documents and confirm every important detail. If an image comes from a supplier, stock library, or photographer, record the permission or licence instead of assuming that a publicly visible image is free to use.

Training providers, consultants, and professional firms: Your business may handle paid reports, client presentations, employee records, legal documents, or industry research. Uploading these materials into an AI tool without checking its data handling terms can expose confidential information. A safer workflow is to remove names, account numbers, customer identifiers, and commercially sensitive details before using AI. You should also define which employees may use AI for client work and which tools have been approved.

Software and automation providers: AI coding assistants can generate functions, documentation, and test cases. However, generated code may resemble code from open-source projects with licence conditions. Your team should retain a basic record of the tool used, review generated code, scan dependencies, and ensure that client contracts explain how automation and third-party components are handled. This is particularly important when you are delivering a system that the client expects to own or operate exclusively.

A Simple Risk View for Your Team

AI activity	Typical risk	Safer business practice
Drafting internal notes	Low to moderate	Remove confidential details and verify facts
Creating public marketing copy	Moderate	Use original business information and conduct similarity checks
Uploading client documents	High	Obtain permission, anonymise content, and use an approved tool
Generating images for paid campaigns	Moderate to high	Check commercial usage terms and retain asset records
Generating software code	Moderate to high	Review code, dependencies, licences, and security issues

This table is a practical screening guide, not a legal opinion. The actual risk depends on the material, the tool, the prompt, the output, your contract, and how the content is used.

Practical Takeaways

• Set an approved-tools list. Name the AI services your team may use and explain which business information must not be uploaded.
• Classify information before prompting. Separate public information, internal information, confidential client information, and regulated or sensitive records.
• Keep a human approval step. A manager or subject specialist should review customer-facing content, claims, technical instructions, and contractual documents.
• Do not treat “public online” as “free to copy.” Check licences, permissions, attribution requirements, and usage limits.
• Ask for original work. Avoid prompts such as “rewrite this article in the same style” when you do not own the source.
• Keep simple records. Note the tool, date, purpose, source materials, editor, and final approver for important work.
• Review contracts. If a client is paying for exclusive content, explain how AI assistance is used and confirm who owns the final deliverables.
• Check outputs for invented facts. Copyright compliance does not protect you from inaccurate product claims or misleading customer information.
• Escalate sensitive matters. Ask a Malaysian intellectual property lawyer when content is central to your product, brand, training materials, or commercial dispute.

The Bigger Picture

The long-term direction is likely to involve clearer rules, better licensing systems, stronger disclosure expectations, and more detailed contracts between AI providers and business users. The article notes that US copyright law was not comprehensively updated for the modern AI question and that courts are producing decisions that may later be refined or contradicted. That uncertainty means you should avoid building a critical business process on an assumption that has not been tested.

For Malaysian SMEs, the sensible response is disciplined adoption. You do not need a large legal department to manage basic AI risk. You need a short policy, a list of approved tools, sensible data handling, human review, and records for important outputs. These steps also improve quality: when staff know what information they may use and who approves the result, errors are easier to catch.

AI will continue to be useful for routine drafting, customer service support, research summaries, workflow automation, and internal operations. But the strongest businesses will treat AI output as a working draft rather than unquestionable property. Your competitive advantage will come from your own customer knowledge, processes, judgement, and original business information—not from asking a tool to imitate someone else’s work.

Before your team uses AI on its next project, ask three questions: Do we have the right to use the source material? Are we exposing confidential information? Who will verify and approve the final output? If you can answer all three clearly, you are taking a much safer and more practical path.

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