Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteUse customer data with an AI tool at work only through a workflow your organization has approved for that type of information. Before entering anything, check whether the task can be done with anonymized, synthetic, redacted, or less detailed data; understand where the information goes, who can access it, and how long it is kept; and involve privacy or security specialists when the risks or rules are unclear.
Can I paste customer information into an AI tool at work?
Not unless your organization has approved that tool and workflow for the specific customer data involved. A tool being available to use—or having a business account—does not by itself establish that it is appropriate for confidential or personal information. Follow your employer’s policy and ask the relevant privacy, security, or legal team if approval is unclear.
There is no single control that makes every AI use safe. The Information Commissioner’s Office (ICO) says, “There is no ‘one-size-fits-all’ approach to security.” Its guidance emphasizes assessing the particular processing, system, suppliers, and connected components. See the ICO’s security and data minimisation guidance.
How to protect customer data when using AI tools at work
- Check approval and purpose. Use only an organization-approved tool and workflow for the relevant data category. Confirm the business purpose and that the AI task is within the approved use.
- Reduce the data before sharing it. Ask what information the task actually needs. Remove names, account numbers, contact details, and other identifiers where they are unnecessary; omit irrelevant conversation history or records. If the task can be completed with synthetic or less detailed information, use that instead.
- Check whether the remaining details can identify someone. Replacing a name with a code is pseudonymization, not necessarily anonymization: other details or a lookup key may still identify the person. Do not treat a simple substitution as proof that the information is anonymous.
- Understand the whole service chain. Check what the AI provider does with inputs and outputs, how long it retains them, who may access them, and whether they are shared or used for model training. Include integrations, connected storage, third-party components, and your organization’s own access controls in the review. An AI feature may pass information through several systems, not just the visible prompt box.
- Record the decision and safeguards. The responsible team should document the purpose, information involved, expected outcomes, access and sharing, retention, risks, and the controls chosen. Make sure someone is accountable for approving and reviewing the use.
- Escalate before use when risk is unclear or elevated. Take sensitive, large-scale, high-impact, or otherwise uncertain proposals to privacy, security, or legal specialists before customer information is entered.
What should an organization assess before approving a workflow?
Assess the actual use rather than relying on a general label such as “AI assistant.” The ICO recommends a holistic view of AI security, including third-party code and interconnected components. A practical assessment should cover:
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- Purpose and necessity: What outcome is needed, and can it be achieved without personal data or with less detail?
- Data and people affected: What types of customer information are involved, how sensitive are they, how many people may be affected, and how is the data collected and stored?
- Providers and connections: Which service providers, integrations, storage systems, and other components receive or can access the information?
- Access, retention, and sharing: Who can see prompts, outputs, or logs; how long are they kept; and are they disclosed to other parties or used for another purpose?
- Outcomes and risks: What will the AI output be used to do, what could go wrong for customers, and what safeguards and human oversight are appropriate?
- Ownership: Which business owner is responsible, and which privacy and security functions must review or monitor the workflow?
These questions help teams decide whether a particular service fits a particular task and data type; they are not a substitute for checking applicable law or internal policy.
What privacy information should customers receive?
Applicable privacy information should explain why the data is processed, how long it is retained, and who receives it or can access it. The ICO’s transparency guidance says that, where information is collected directly, this information should be provided at collection and before the data is used to train a model or apply a model to those individuals. Organizations should make sure their privacy information matches the actual AI workflow, rather than describing a different or more limited use.
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When is a DPIA needed in the UK?
For UK processing, assess case by case whether the proposed use is likely to result in high risk and whether a data protection impact assessment (DPIA) is required. Document why a DPIA is or is not needed and involve the appropriate privacy and security functions. The ICO’s accountability and governance guidance also places responsibility on the organization, with senior management and relevant specialists involved; AI risk should not be left solely to technical teams.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which legal guidance applies?
The cited ICO guidance concerns the UK GDPR and Data Protection Act 2018. It distinguishes legal requirements from good-practice recommendations, is not an exhaustive guide to every organizational obligation, and notes that measures depend on context. The ICO says its AI and data protection guidance—updated 15 March 2023—is under review following the Data (Use and Access) Act. Check the live ICO guidance and applicable law when making a decision.
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These UK sources do not establish the legal requirements for the United States, EU, or other jurisdictions. Organizations operating across borders should check relevant local privacy law as well as their own policies.
Quick Recap
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