Increased productivity is a good thing, but unsanctioned and unregulated AI use poses risks. A February 2025 TELUS Digital survey found that 57% of enterprise employees admit to entering high-risk information into publicly available chatbots. This includes personal data about employees or customers, product or project details, and confidential financial information like revenues, profit margins, budgets, and forecasts.

A clear AI policy will help a business minimize the risks of using AI tools. These risks include leaks of confidential information, compliance failures, accidental copyright violations, and reputational damage. As AI becomes a routine part of knowledge work, every business—even small firms—must establish an AI policy to maximize the benefits of using AI while safeguarding the company, its employees, and its clients.

Risks Addressed by a Formal AI Policy

Unauthorized AI use can create several types of problems:

• Data security: Employees routinely paste sensitive data—including customer information, financial records, and unreleased products—into public AI tools, thereby losing control over how that data is used. That can make security audits nearly impossible and drive IT staff crazy. Notably, the free versions of ChatGPT (by default, it can be turned off) and Google’s Gemini can incorporate user data into their training models, making it possible that the information could be included in a discussion with someone else.
• Legal and compliance risks: Sharing protected information with non-compliant AI systems could result in penalties during regulatory audits, even if no actual data breach or harm occurs. For instance, using such systems to summarize patient records could violate HIPAA, while using them to analyze customer data could run afoul of the California Consumer Privacy Act (CCPA).
• Unintentional discrimination: Without clear guidelines, the use of AI can lead to unintentional discrimination in hiring, customer service, and decision-making. This may violate ethical standards and expose the company to legal liability.
• Employee confusion: The lack of a coherent AI policy leads to inconsistent practices and uncertainty about acceptable tools and proper procedures, resulting in reduced productivity and increased anxiety about AI use.

Essential Elements of an AI Policy

The specifics of an AI policy vary by the type and size of company, but at minimum, most AI policies should include the following:

• Permitted AI uses and tools: Clear guidelines on the types of tasks employees may undertake with AI assistance and a list of approved AI platforms for business activities
• Data privacy and legal compliance: Rules for safeguarding confidential, personal, and proprietary information when using AI, coupled with rules that ensure adherence to relevant industry-specific regulations and privacy laws
• Human oversight and transparency: Requirements that employees thoroughly review AI-generated content before use and disclose AI involvement when appropriate in client-facing or public materials
• Risk reporting and incident response: Clear instructions for reporting AI-related errors, security incidents, or potential misuses
• Ownership and intellectual property clarifications: Statements affirming that work products created with AI assistance belong to the company. These statements should also address any intellectual property considerations.

Building Your AI Policy

If your company doesn’t already have an established process for generating policies, AI tools can themselves provide a starting point when used thoughtfully. Here’s an approach:

1. Prompt an AI tool like ChatGPT or Claude to generate a basic AI policy template. Be explicit about your company’s size, industry, and other relevant details, and be sure to specify that it must cover the elements listed above—you can paste them in. Iterate as necessary until the template has all the required sections.
2. Review the generated template carefully, removing generic content and noting areas that need company-specific details.
3. Ask for feedback on the draft from key stakeholders, including:
   • Leadership to align with company goals and values
   • IT team to verify technical feasibility and security measures
   • Legal counsel to ensure compliance with relevant regulations
   • Department heads to confirm that it will be practical to implement the policy
4. Incorporate the feedback to create a policy that reflects your company’s specific needs while maintaining necessary protections.

Remember: An AI-generated template is for starting the conversation. The final policy must be tailored to your organization’s specific needs and thoroughly vetted by relevant stakeholders.

The rise of AI tools in the workplace isn’t just a trend—it’s a fundamental shift in how work gets done. Whether your employees are already using AI tools without oversight or are hesitant to use them due to uncertainty, now is the time to establish a formal AI policy. Start with the template approach outlined above, engage your stakeholders, and develop guidelines that work for your organization. A well-crafted AI policy will help your business harness the benefits of AI while minimizing its risks.

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Despite Apple’s recent relabeling of features as using AI, when most people think about AI, they’re thinking of “generative AI” systems like OpenAI’s ChatGPT chatbot or Adobe’s Firefly artbot. These systems generate impressively good text and images from scratch based on user prompts. Ask ChatGPT to write an excuse for your sick kid, and you’ll get fluid, correct English. With Firefly, describe an image—“silhouettes of male and female runners with bright colors and black background”—and you’ll get images that match pretty well.

How do they accomplish this magic? Chatbots use statistical models to predict the next word based on training datasets that contain hundreds of billions of words—think autocomplete on radioactive steroids. Artbots work a little differently, but they also use statistical models to create images based on having been trained to identify numerous images.

Enough background. How can you make the most of today’s leading chatbots (ChatGPT, Claude, Copilot, Gemini, Meta AI, Pi, and Le Chat Mistral) and artbots (Adobe Firefly, Microsoft’s Copilot Designer, NightCafe, Meta AI, and Midjourney)?

Identify Good Uses of Generative AI

It’s essential to recognize that the effectiveness of generative AI for a particular task is highly individualized. What works for one person may not work for another due to varying skill levels, requirements, and preferences. With that in mind, here are three ways to evaluate tasks that might be a good fit for generative AI.

• Skill levels: The less skillful or knowledgeable you are about a subject, the happier you’ll be with generative AI’s results. You can think of an AI chatbot as a C+ student—its work will get a passing grade, but it won’t fool an expert. But we’re all happy to do or receive C+ work in many parts of our lives—no one is above average in everything.
• Requirements: Are you looking for something definitive—precisely what you have in mind—or would you be happy with an open-ended set of results? AI chatbots and artbots generate statistically likely results, so if you’re not caught up in things being just right, you’ll probably like what you get. Don’t expect them to read your mind, however.
• Preferences: It’s best to think of an AI chatbot as an assistant, because you must be willing to go back and forth with it. And that means you have to be willing to work with an assistant who is dumber than they seem, entirely reactive, unpredictable, and inconsistent. (On the plus side, chatbots are also tireless, imperturbable, incredibly well-read, and non-judgemental.)

To sum up, the best tasks for generative AI are those where you know little or aren’t particularly skillful, don’t have specific expectations about what you’ll get, and are willing to interact with a potentially annoying helper.

Get Better Results from Generative AI

These recommendations will help you get better responses from AI chatbots:

• Set the stage with detail and expectations: Unlike Web searches, chatbots work best when provided with more than essential keywords. Instead, tell the chatbot a little about yourself, provide background about the topic, and lay out your expectations. ChatGPT even lets you provide instructions to apply to all your chats. Additional detail helps the chatbot’s statistical model better predict what you want.
• Iterate repeatedly and push harder: You don’t have to provide all that detail up front. Chatbots retain context—they know what has been said in the chat—so after your initial prompt, you can and should keep pushing the chatbot to refine and improve its answer. Don’t be shy to ask, “What’s missing from this?” or “How could this be improved?” While it’s always best to be polite, there’s no harm in asking a chatbot to do better. Pretend you’re a coach or therapist and keep asking probing questions.

Remember, unlike a search engine, where each search stands alone, working with an AI chatbot is a conversation. Right now, that’s less true of AI artbots, but we’re moving in that direction.

Good Uses for Generative AI

AI has innumerable possible uses, limited mostly by your imagination. Here are a few that have worked well for us:

• Brainstorming: Have you ever needed to come up with a name for a program, product, or service and found your mind utterly blank? Or maybe you’re writing and can’t put your finger on precisely the word you want? Ask an AI chatbot! With a little direction, they’re great at coming up with a bunch of possible names or words. You may not get exactly what you want, but the chatbot’s suggestions will help you think in new directions.
• Coding: An AI chatbot won’t turn you into a professional programmer, but it can help you write a small AppleScript to automate a task like adding sequentially numbered calendar events to every Monday for the rest of the year. Chatbots are also good at helping you use powerful but complex Unix tools for reformatting text like sed, awk, and grep. But perhaps our favorite real-world use is getting help with devilishly complicated spreadsheet formulas that do lookups as part of their calculations.
• Talk to documents: Some AI chatbots (and services like ChatPDF) enable you to have conversations with long documents. That sounds weird, but it’s much easier to ask a few questions about how a hundred-page report affects your business, for instance, than to slog through the entire thing. Such systems provide page references to support their answers, so you can (and should) verify what you’re told.
• Drafting difficult email: Some email messages are hard—no one likes having to reprimand an employee, express condolences to a business associate, or announce layoffs. But such messages are essentially genres—if you’ve seen one corporate merger announcement, you’ve seen them all. If you seed your prompt with plenty of appropriate details, an AI chatbot can generate a credible first draft that you can tweak to improve accuracy and make it sound like you instead of an overeager college student. Never send an AI-generated email without taking an edit pass.
• Evaluating ideas: It’s always a good idea to talk through ideas and decisions, and conversations with AI chatbots can help you think about them. Should you ask for a raise or try for a promotion? What are the pros and cons of moving to a new location? Does it make more sense to rent or buy? An advantage of AI chatbots is that you can tell them to respond like a particular type of professional, such as a lawyer, financial advisor, or life coach. Of course, all chatbot responses are just statistically probable, so they won’t compete with those from actual professionals, but they’re a good start.

AI-Powered Searching

Finally, let’s look at AI-powered search engines like Perplexity and Arc Search (on the iPhone), and increasingly prominent AI-generated summaries in Google, Bing, and Brave Search. They blur the distinction between search engines and chatbots. Search engines focus on providing answers to questions, either link to or summarize their sources, and include the most recent information. In contrast, chatbots focus on conversation, generate answers from scratch, and always have some date after which their knowledge stops.

When might an AI-powered search engine be more effective than a traditional search engine’s list of links? Try one in situations like these:

• Searches for easy but non-obvious answers: If you want to know who held the mile world record before Hicham El Guerrouj, for instance, an AI search engine will just tell you, rather than make you read a Wikipedia page about the world record progression. It could even tell you who has come the closest to his world record in the last decade, which would be difficult to determine otherwise.
• Searches for answers to idle questions: If you don’t want to spend a long time reading source materials and don’t care much about the answer, an AI-powered summary will be efficient.
• Searches that require assembling information from multiple sources: Imagine that you want to know how many people live in New York City, Boston, and Chicago. With a traditional search engine, you’d need to find each city’s population independently (or a list of major US city populations) and add them manually. An AI-powered search engine could find them all and add them for you.
• Searches where you don’t quite know what you’re looking for: When you’re starting to explore a topic, an AI-powered search engine can suggest additional searches as you home in on aspects of the topic that especially interest you.

Google’s recent addition of AI-driven summaries quickly drew mockery for suggesting the addition of glue to pizza and encouraging the ingesting of rocks. But remember, humans say incorrect things all the time, often intentionally. In fact, both of those examples were triggered by jokes and could have come up in traditional searches as well, but in contexts that were clearly silly.

Regardless of whether information comes from an AI chatbot, an AI-powered search engine, a Facebook post, or the woman next to you on a plane, you have to discern whether it’s likely to be right. AI can be helpful in many ways, but it won’t do your thinking for you.

None of the text of this article was generated by AI.

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To be sure, many conversations aren’t sensitive, such as asking for a recommendation of bands similar to The Guess Who or help writing an AppleScript. But increasingly, we’re hearing about people who’ve asked an AI chatbot to analyze or summarize some information and then pasted in the contents of an entire file. Plus, services like ChatPDF and features in Adobe Acrobat let you ask questions about a PDF you provide—it can be a good way to extract content from a lengthy document.

While potentially useful from a productivity standpoint, such situations provide a troubling opportunity to reveal personally sensitive data or confidential corporate information. We’re not talking hypothetically here: Samsung engineers inadvertently leaked confidential information while using ChatGPT to fix errors in their code. What might go wrong?

The most significant concern is that sensitive personal and business information might be used to train future versions of the large language models used by the chatbots. That information could then be regurgitated to other users in unpredictable contexts. People worry about this partly because early large language models were trained on text that was publicly accessible online but without the knowledge or permission of the authors of that text. As we all know, lots of stuff can unintentionally end up on the Internet.

Although the privacy policies for the best-known AI chatbots say the right things about how uploaded data won’t be used to train future versions, there’s no guarantee that companies will adhere to those policies. Even if they intend to, there’s room for error—conversation history could accidentally be added to a training model. Worse, because chatbot prompts aren’t simple database queries, there’s no easy way to determine if confidential information has made its way into a large language model.

More down to earth, because chatbots store conversation history (some let you turn off that feature), anything added to a conversation is in an uncontrolled environment where at least employees of the chatbot service could see it, and it could be shared with other partners. Such information could also be vulnerable should attackers compromise the service and steal data. These privacy considerations are the main reason to avoid sharing sensitive information with chatbots.

Adding emphasis to that recommendation is the fact that many companies operate under master services agreements that specify how client data must be handled. For instance, a marketing agency tasked with generating an ad campaign for a manufacturer’s new product should avoid using any details about the product in AI-based brainstorming or content generation. If those details were revealed in any way, the agency could be in violation of its contract with the manufacturer and be subject to significant legal and financial penalties.

In the end, although it may feel like you’re having a private conversation with an AI chatbot, don’t share anything you wouldn’t tell a stranger. As Samsung’s engineers discovered, loose lips sink chips.

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Social Media: Privacy concerns are starting to crop up around conversations held with AI chatbots. For safety’s sake, never share anything with a chatbot that you wouldn’t tell a stranger.

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ChatGPT is an AI-powered chatbot designed to mimic a human conversationalist. Its goal is to make communicating with computers more natural. Type anything into ChatGPT, and it will respond in clearly written English. You can also ask it to write things for you, like email responses or school essays, and it can generate text in a wide variety of styles, generating fairy tales, poetry, and even computer code. Unlike most chatbots, ChatGPT remembers what you’ve said and considers that context in its replies.

One way to think of ChatGPT is as a sort of search engine like Google or Microsoft’s Bing. There are three huge differences, however. First, ChatGPT answers your queries directly, rather than presenting you with a list of websites that contain information about your query. Second, although it sounds confident, ChatGPT often gets facts wrong. Third, if you ask ChatGPT the same question twice, you might not get precisely the same answer—there’s an element of randomness in its responses.

How could this be? ChatGPT is what’s called a “large language model,” a neural network that trains itself on extremely large quantities of text—reportedly 300 billion words from 570 GB of datasets. That means ChatGPT doesn’t “know” anything. Instead, it looks at a prompt and generates a response based on the probability that one word follows another. In some ways, it’s the ultimate form of auto-complete. Ask ChatGPT to write a fairy tale, and it will start “Once upon a time” because in its training data, text that matches the prompt of “fairy tale” very likely begins with those words. That’s also the source of its mistakes—just because words occur near one another says nothing about their relationship.

It’s difficult to avoid anthropomorphizing ChatGPT and similar AI-driven chatbots that are flooding the market. Their answers sound utterly convincing, but again, they don’t “know” anything. Despite AI being short for “artificial intelligence,” they don’t think (whatever that might mean). They have no agenda and aren’t trying to convince or mislead.

Rather than think of an AI as a person on the other side of the screen, it’s essential to realize its limitations, a few of which include the following:

• AI-generated text tends to use generalities without much supporting detail, at least without further prompting. Non-experts may not notice, but experts often cringe when they read AI-generated text.
• When details are present, there’s no guarantee that they’re correct. They could be slightly off or ludicrously wrong, so you must double-check everything before assuming it’s true.
• If the desired information isn’t in the training set or is only weakly included, conversations about it can get weird. Notably, ChatGPT’s training data is from before 2021, so it can’t converse about anything more recent than that. Plus, it can completely fabricate answers. (When asked about American marathoner Keira D’Amato, ChatGPT stated that she held the world record for the mile while balancing a fruit basket on her head, which has no basis in reality.)
  
• When prompts contain words that have multiple meanings, like break, run, and set, AI chatbots can return nonsensical results that confuse the different meanings.
• Although the programmers behind AI chatbots try to head off requests aimed at producing obviously racist, sexist, or otherwise offensive responses, the training data includes all sorts of biased and even hateful text. As a result, AI chatbots can say things that are either explicitly or implicitly problematic.

Despite these very real concerns, the AI genie is out of the bottle. The two highest-profile announcements have come from Microsoft and Google. Microsoft has invested in ChatGPT-maker OpenAI and integrated the technology behind ChatGPT into a new version of its Bing search engine (available only in the Microsoft Edge browser for now), whereas Google, which pioneered the technology underpinning ChatGPT, has now released its own AI chatbot, Bard.

Those are just the tip of the iceberg. We’ve also seen AI appearing in products that can help write code, summarize meeting notes, polish email messages, and even create unlimited text adventure games. CARROT Weather, the famously snarky iPhone weather app, has even integrated ChatGPT and tuned it to respond with attitude.

It’s early days, but many people have already found good uses for ChatGPT. For instance:

• If you’re faced with writing a difficult email, consider asking ChatGPT to draft it for you. It likely won’t be perfect, but you might get some text that you can tweak to make it better serve your needs. In fact, for many forms of writing, ChatGPT can both give you a draft to start from and suggest improvements to what you write. This is especially useful for people who struggle with writing in English.
• ChatGPT can help generate code. For inexperienced programmers, it’s a good start, and for long-time coders, ChatGPT can save typing and debugging time. We tried asking it to write an AppleScript that would create a sequentially numbered calendar event every Monday, and although it didn’t work on the first try, after telling it about the errors generated by the code, it arrived at a functional script.
• We know people who enjoy composing doggerel for birthday cards. If you’d like to do that but can’t come up with the words or rhymes, ask ChatGPT. For instance, try asking it to write a “roses are red” poem on a particular topic. Or ask it for a country music song— but don’t buy a ticket to Nashville.
• Need to come up with a clever name for a project or event? Ask ChatGPT to give you ideas that are three or four words long and include certain concepts. Keep asking it to refine or nudge it in new directions. It may not generate exactly what you want, but it will give you lots of ideas to combine on your own.
• If you’re editing some confusingly written text, you can ask ChatGPT to simplify the language in the paragraph. Again, it may not be perfect, but it might point you in a useful direction.

What all these examples have in common is that they use ChatGPT as a tool, not as a replacement for a person. It’s at its best when it’s helping you to improve what you already do. For instance, it won’t replace a programmer, but it can help get you started with simple scripts. The hard part is learning how to prompt it to output the results you want, but remember, it’s not a person, so you can keep asking and nudging until you’re happy with the results.

There are many reasons to be skeptical of how AI services are being used, and we recommend using them cautiously. But given the levels of interest from businesses and users alike, it seems that they’re here to stay.

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