You probably know how AI tools can speed up repetitive PR tasks and uncover valuable insights that once took hours to find.
But with that convenience comes responsibility.
Sensitive data often powers these tools. They also rely on algorithms that may not always be fair and operate in areas where trust and data transparency matter.
So, how can PR teams use AI responsibly?
They must ask the right questions, be aware of legal boundaries, and ensure that human judgment remains at the center of the process.
Understanding AI in PR
AR in PR is the use of artificial intelligence (AI) to support and streamline public relations tasks. Teams use it to track brand mentions, analyze audience sentiment, generate media lists, and even draft content (e.g., social media posts, blogs, press releases, articles, etc.).
According to a 2024 survey:
- 65% of public relations professionals say that AI would be impactful on research and listing building.
- 62% would use it for ideation or brainstorming.
- 57% of respondents would use AI for writing first drafts.
(Source: Statista)
However, despite its usefulness, AI isn’t a replacement for good judgment. It can provide key insights and suggestions, but it still requires people to interpret results, shape narratives, and make decisions about what to say and when to say it.
Ethical questions PR team can’t ignore
AI raises lots of ethical concerns. For example, when a machine writes content or informs decisions, there are questions about how transparent and fair the process is:
- Should audiences know when they’re reading AI-generated content?
- How do you check for bias in tools trained on incomplete or skewed data?
- What happens if a tool pulls from inaccurate or outdated sources?
- What level of transparency is required when collecting and analyzing public data at scale?
- At what point does media monitoring begin to resemble surveillance?
- How do teams ensure that automated engagement doesn’t feel impersonal, misleading, or inappropriate?
- Are AI-generated insights being validated before informing strategy or public messaging?
- What processes exist to regularly audit tools for bias, accuracy, and unintended consequences?
Example: Spotify used AI to generate personalized podcasts and DJ commentary during its 2024 Wrapped campaign, but chose not to highlight these features.
The company placed these features in a separate tab rather than in the main shareable slides. This cautious rollout suggests concern about how audiences might react if they knew more of the experience was machine-generated.
Data security risks behind the tools
AI tools often need access to sensitive data in order to work effectively. For example, they may process press lists, internal documents like email lists, customer insights, and tracking reports.
Managing that data opens the door to unnecessary risk.
Common problems include using tools without reviewing their data policies, sharing confidential information through unsecured platforms, and failing to control access within the team.
It only takes one oversight to cause a breach. And in PR, that kind of mistake can escalate fast. Protecting information should always take priority over speed or convenience.
When using AI tools to manage communications or store sensitive data, you’ll want to regularly run vulnerability scanners to catch weak points early. These tools help identify potential security gaps in your systems so you can fix them before they’re exploited, especially important when handling large volumes of media contacts, customer data, or internal documents.
Compliance, privacy laws, and what they mean for PR
Bringing AI into public relations means thinking carefully about how you handle data and make decisions, especially when handling personal information.
Take the Social Security Administration (SSA), for example. It uses AI to speed up the process of handling disability benefits. The goal is to cut down wait times and make the system more efficient, but it’s also raised questions about whether the algorithms treat everyone fairly, especially those with disabilities. That’s the kind of situation where clear communication matters.
For the SSA, this means ensuring that the public remains informed about measures it’s taking to protect personal data and uphold ethical standards in services like social security disability representation.
The same risks apply in PR. Whether your team is analyzing sentiment, tracking engagement, or personalizing outreach, the tools often rely on data that’s subject to privacy laws like GDPR or CCPA.
These laws require you to explain what data your brand is collecting, how you’re using that data, and whether individuals have consented to that use.
If your process or the way your tools handle data isn’t clear, you risk crossing a legal line.
Achieving Responsible AI in PR
To use AI responsibly, PR teams need clear standards. They should understand:
- What specific problem the AI is helping to solve
- What data the tool depend on to function
- What oversight is in place to catch errors, gaps, or misuse
Training also matters. Everyone using AI should know:
- How the system works and what it can and can’t do
- Where human input is still necessary
- How to recognize when a result seems off or incomplete
As AI becomes increasingly embedded in PR operations—handling everything from sentiment analysis to media monitoring—the integrity and security of the underlying data infrastructure is just as important. This is where colocation solutions come into play.
By housing critical servers in secure, third-party data centers, organizations gain access to high-level physical security, redundant power systems, and environmental controls—all essential for minimizing downtime and protecting sensitive data.
Example: The New York Times integrates AI to help track story engagement and forecast reader interest. Instead of letting the algorithm decide what to publish, editorial teams review all recommendations and maintain control over final decisions.
The Times also published an article outlining how the tool worked and what it didn’t do, which helped build transparency and trust with readers.
What’s next for AI in PR?
AI is now a regular part of modern PR. It can scan news coverage, draft reports, sort audience data, and flag trends faster than any person can.
So, yes, to sum up, AI can help PR teams work more effectively. But that’s only part of the story.
Take the time to understand the limits of the tools, follow the rules that apply to the data, and keep your standards clear.
