What Is the NIST Privacy Framework? Explanation and How to Implement It

Imagine a customer asks your company to delete all of their data, and no employee knows which systems hold it. Marketing keeps it in a spreadsheet, customer service in a ticketing app, and finance still has an old archive.

Situations like this are growing more common because artificial intelligence (AI) systems now process personal data too. In the Cisco 2026 Data and Privacy Benchmark Study, 90% of organizations reported that their privacy programs have expanded because of AI, based on a survey of more than 5,200 professionals across 12 markets.

One reference for sorting this out is the NIST Privacy Framework, a set of guidelines for managing privacy risk. This article covers what it is, how it differs from the Cybersecurity Framework, its five core functions, its relationship to Indonesia’s UU PDP, and how to implement it.

What Is the NIST Privacy Framework?

The NIST Privacy Framework is a voluntary guide that helps organizations manage the privacy risks that come from processing personal data. NIST stands for the National Institute of Standards and Technology, a technology standards agency of the United States government.

The framework was first published in January 2020 and was designed to work alongside the NIST Cybersecurity Framework. Version 1.1 realigns it with Cybersecurity Framework 2.0 and adds guidance on privacy risks that arise from AI, as described on the official NIST Privacy Framework page.

It does not require certification and does not replace legal obligations. Its purpose is to give organizations a way to build a privacy program, assign responsibility, and measure progress.

Its viewpoint is distinctive: the risks being assessed are the effects on the individuals the data belongs to, such as discrimination, financial loss, or embarrassment from exposure. Harm to the company is counted afterward.

Take an online store that collects customers’ home addresses and purchase histories. Using the framework, the team asks what would happen to customers if those addresses leaked, then designs safeguards based on the answer.

Organizations of many sizes and sectors can use it, from a small clinic to a multinational company. It scales to fit: a small organization can adopt only the relevant activities, while a large one can work through the entire Core.

The framework has three components: the Core, Profiles, and Implementation Tiers. The Core lists privacy activities, Profiles describe an organization’s current state and its target, and Tiers indicate how mature the implementation is.

For example, a logistics company uses a Profile to record that it has no data retention policy. The gap between its current state and its target becomes visible, and it turns into next quarter’s task.

NIST Privacy Framework vs NIST Cybersecurity Framework

The two frameworks are often mentioned together because they were designed to be used as a pair. Even so, each answers a different question, as the table below shows.

Aspect	NIST Privacy Framework	NIST Cybersecurity Framework
Risk focus	Effects of personal data processing on individuals	Threats to the security of systems and information
Core functions	Identify, Govern, Control, Communicate, Protect	Govern, Identify, Protect, Detect, Respond, Recover
Main question	Is personal data collected and used in a reasonable way?	Is the system protected from attack, and can it recover?
Overlap	Govern and Protect functions	Govern and Protect functions
Example problem	An app collects location data it does not need	An attacker breaks into a company server

An app can be immune to hackers and still harm its users. For instance, a flashlight app that records user location for no clear reason creates privacy risk even though no cyberattack takes place.

That is why many organizations use both. The Cybersecurity Framework protects the system, while the Privacy Framework governs how personal data is treated inside it.

The Five Core Functions of the NIST Privacy Framework

The Core is divided into five functions that do not have to be completed in sequence, with Govern at the center. The sections below explain each function with an example.

Identify

Identify asks an organization to understand what personal data it processes, for what purpose, and who is affected. The result is a data inventory and a privacy risk assessment.

For example, the recruitment team records that applicant résumés sit in staff members’ personal email and in a shared folder. That record reveals that the two locations follow different access rules.

Govern

Govern sets privacy policies, roles, and decision paths at the organizational level. Without it, responsibility tends to fall on whoever happens to be closest to the problem.

For example, an e-commerce company forms a small committee of legal, IT, and marketing representatives. Every campaign that uses new customer data must pass that committee’s review first.

Control

Control covers what the organization does with data day to day: collection, storage, access, and deletion. Written rules need working mechanisms behind them, such as retention limits and procedures for handling requests from individuals.

For example, a clinic decides that inactive patient records are deleted once the retention period ends. When a patient asks for a copy of their data, staff follow a procedure with a set deadline.

Communicate

Communicate makes sure data owners understand how their data is used. A twenty-page privacy policy full of legal terms rarely gets read, so the explanation has to be short and clear.

For example, a shopping app shows a three-sentence summary before users approve location access. The summary states that location is used only to calculate shipping costs.

Protect

Protect connects privacy with cybersecurity. Encryption, role-based access limits, and logging of user activity act as a fence that keeps data from leaking or being misused.

For example, an employee who has resigned can still log in to the CRM and see active customer data. With routine access reviews, that account is disabled on the employee’s last day of work.

Benefits of the NIST Privacy Framework for Organizations

The framework does not promise a certificate, but it gives structure that shows up in daily operations. Here are four benefits organizations report most often, each with a short example.

• A shared language across teams. Legal, IT, and marketing use the same terms when they discuss data. For example, a meeting about an email campaign no longer stalls on what “sensitive data” means in each department.
• Clear risk priorities. You know which risks to handle first, so budget is not spread across low-impact issues. For example, a company secures its customer database before it tidies old paper archives.
• Easy alignment with other rules. The framework is not tied to one jurisdiction, so its structure can be mapped to many data protection laws. For example, a company operating in several countries can use one program structure to answer many sets of rules.
• Stronger customer trust. An organized practice makes it easier to explain how data is used. For example, when a customer asks why a phone number is required, staff can answer with a clear, documented purpose.

How the NIST Privacy Framework Relates to Indonesia’s UU PDP

In Indonesia, personal data protection is governed by Law No. 27 of 2022 on Personal Data Protection (UU PDP), which took effect when it was promulgated on 17 October 2022. It is legally binding, unlike the NIST Privacy Framework, which is voluntary.

The two complement each other: UU PDP sets out what must be met, while the NIST Privacy Framework helps organize how to meet it. The framework does not make an organization compliant automatically, so mapping to specific articles of UU PDP should still be done with legal counsel.

The table below shows examples of how the framework’s functions relate to the obligations of a personal data controller.

NIST Function	Relation to UU PDP	Example in Practice
Identify	Knowing what data is processed, including specific data such as personal financial data	A financing company flags customer financial data as a special category
Govern	Policies and people responsible for personal data protection	An organization appoints an officer who oversees data protection
Control	Meeting data subjects’ rights over their personal data	A written procedure for handling access or deletion requests
Communicate	Written notice when a data protection failure occurs	An incident notification template prepared in advance
Protect	The duty to keep data confidential and secure	Encryption and role-based access limits

Take the obligation to notify data subjects and the authority within 3×24 hours of a personal data protection failure. An organization that has prepared its communication workflow through the Communicate function can carry it out without drafting procedures from scratch while an incident is under way.

How to Implement the NIST Privacy Framework

NIST suggests a staged approach built around Profiles. The six steps below summarize that flow in practical terms, with examples.

1. Define the Scope and Involve the Right People

Start with a clear boundary: which business unit, product, or process comes first. Bring in legal, IT, and process owners from the beginning so findings do not stay stuck in one department.

For example, a retail company starts with its customer loyalty program because that is where the most data is collected. Legal, IT, and marketing sit in the same meeting from the first week.

2. Build a Current Profile and Map Your Data

Record the privacy activities already running, then build an inventory of data types, collection purposes, storage locations, and who has access. You cannot protect data you do not know exists.

For example, an insurance company finds that it never wrote a policy for deleting old customer data. The finding is logged as a gap in the Current Profile.

3. Assess Privacy Risk to Individuals, Including AI Risk

Ask what could happen to data owners if their data is misused or leaked. The assessment should also cover data used to train or run AI systems.

For example, a bank uses customers’ transaction histories for an automated credit scoring model. The risk assessment shows that the model could wrongly reject an application with no reason that can be explained to the customer.

4. Set a Target Profile and Implementation Tier

Define the privacy state you want to reach, then choose a matching tier, from Partial to Adaptive. The target should reflect risk, available resources, and the legal obligations that apply.

For example, a fintech startup realizes that its privacy handling depends on one person. It sets a target of written processes that keep running regardless of who is on duty.

5. Analyze the Gaps and Build an Action Plan

Compare the Current Profile with the Target Profile, then rank the gaps by risk level and ease of completion. Each action needs an owner, a deadline, and a measure of success.

For example, a company finds that it has no retention policy, no clear incident notification flow, and no review of access rights. The retention policy comes first because the risk is high and the work is quick.

6. Run, Measure, and Review Regularly

Carry out the plan, record the results, and schedule a recheck, for example every six months. Changes in systems, vendors, or regulations can alter your profile at any time.

For example, a newly installed customer service chatbot that stores user conversations enters the next review. The team updates the data inventory and reassesses the risk.

Conclusion

The NIST Privacy Framework gives a clear structure: know your data, assess the risk, assign responsibility, then manage, communicate, and protect. For organizations in Indonesia, that structure helps build ways of working that support meeting UU PDP.

A privacy program is not a one-off project. Schedule regular reviews, especially when the organization starts using new technology that processes personal data.

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