Data privacy and security concerns are top barriers to AI adoption, and there’s no shortage of predictions about the possible risk ahead for privacy and cyber security teams.  

But rather than viewing AI agents — a type of AI that can complete tasks without human intervention — as privacy threats, it’s time to see them as privacy enablers. 

With the right guardrails, AI agents can in fact fortify a company’s privacy efforts, minimizing human error, limiting data access by design, and acting as privacy intermediaries — shielding individuals and organizations from excessive data collection, access, and use while still delivering personalized experiences. 

With the right guardrails, AI agents can in fact fortify a company’s privacy efforts, minimizing human error, limiting data access by design, and acting as privacy intermediaries…

Agentforce, the agentic layer of the Salesforce Platform, empowers businesses to configure agents with strict boundaries when processing personal data, prioritize data minimization, and ensure compliance with global privacy regulations. 

The future of privacy isn’t about locking data down. It’s about choosing a trusted platform that minimizes the surface area for potential threats and sets agent guardrails to boost privacy and security efforts. With the right platform, privacy turns into a business enabler‌ — ‌driving customer trust, operational efficiency, and long-term value for the business.

Reducing the threat surface with agentic AI

After decades of working in the privacy field, I’ve seen firsthand how human error is often at the heart of privacy and security incidents. AI agents offer a powerful advantage: they minimize the risk of human mistakes and misconduct, closing the gaps that most commonly lead to security vulnerabilities. 

Traditional data handling processes often involve multiple human touchpoints, each a potential source of mistakes, negligence, or even malicious intent that can lead to privacy breaches, data leaks, or regulatory violations.AI agents reduce this risk by consistently following pre-defined rules and protocols. Unlike humans, agents don’t get tired, distracted, or fall for social engineering tactics. Their predictable behavior makes them less likely to expose data, mishandle sensitive information, or make unauthorized copies. 

Agents also enable secure collaboration. For example, third-party vendors can get the answers they need from agents without direct access to sensitive data — keeping customer information under the customer’s control. Consider a hospital lab technician entering patient results into an EHR system. Errors — whether accidental or intentional — are possible. But if an agent automates data entry, human touchpoints decrease, reducing both mistakes and misuse.

Within organizations, agents can further protect privacy by automatically monitoring data handling, archiving or deleting data after set periods, and masking identifying information — making it harder to trace data back to individuals.

Limiting data sent to AI models

Of course, there’s always the possibility of humans programming bad-acting AI agents. But the beauty in having a trusted platform like Agentforce is the way it works to counteract these threats through its Trust Layer and techniques like retrieval-augmented generation (RAG).

RAG is a technique that uses semantic search to retrieve relevant snippets of information from any data source for better AI outputs. When used correctly, RAG does double duty: By surfacing only the most relevant data to an LLM, RAG ensures that AI outputs are limited to only what’s necessary.

In accordance with global privacy principles, companies should only use the minimum amount of personal data needed for a task. RAG and similar techniques can automate and scale the process of determining the minimum set of relevant data for grounding, giving organizations the benefit of higher-quality outputs that rely on just the right amount of external data.

RAG is also useful for ensuring accuracy when using general-purpose LLMs that were trained on data that may be stale or irrelevant to a customer-specific query. Yet by keeping the external data store up-to-date, organizations can ensure that the outputs from AI agents remain highly accurate and reflective of the current state of play within their business. 

Programming agents to be privacy enforcers

The agentic AI era is not just a revolution for tech and innovation — it’s a revolution for privacy. Seventy-one percent of consumers are increasingly protective of their personal information, yet 73% expect better personalization as technology progresses. AI agents solve for this paradox by incorporating privacy considerations into their design and functionality. 

The agentic AI era is not just a revolution for tech and innovation — it’s a revolution for privacy.

From the first touchpoint through the entire customer lifecycle, agents can be configured to enhance privacy. For example, an AI agent can be configured to present an organization’s privacy statement to individuals at the first point of contact, provide “just-in-time” notices if at any point further personal data is collected from individuals, and provide up-to-date and relevant information on how to exercise data subject rights on request. Agents could also be configured to help consumers better understand a company’s privacy policies by creating a conversational interface for them to ask questions, demystifying complex legal jargon, and fostering transparency with the brand. 

Sixty-five percent of consumers also feel companies are reckless with customer data, and data breaches make headlines regularly. Organizations that fail to prioritize privacy risk not only regulatory consequences but also customer attrition. On the other hand, organizations that use platforms like Agentforce can use AI agents to minimize these risks while building trust with their customers.

Our customers have legitimate questions about managing risk with AI agents. Salesforce is committed to helping customers achieve trusted agentics — AI systems that have proper data governance, guardrails, and compliance in place.

Edward Britain, SVP, Global Privacy, Salesforce

“Our customers have legitimate questions about managing risk with AI agents. Salesforce is committed to helping customers achieve trusted agentics — AI systems that have proper data governance, guardrails, and compliance in place,” said Edward Britain, SVP, Global Privacy, Salesforce. 

Guidelines for implementing trusted agentic AI

AI agents can serve as a privacy compliance force for any company. Organizations should consider the following principles:

• Trusted Data: AI agents rely on accurate and relevant data to make informed decisions and take appropriate actions. Businesses must invest in robust data governance frameworks to ensure data quality, integrity, and compliance with privacy regulations. 
• Compliance: The regulatory landscape for AI is rapidly evolving, with new laws and guidelines emerging globally. Organizations must stay up-to-date on and comply with new AI-specific laws and global privacy laws that regulate any processing of personal data. Businesses must also design with the future in mind, keeping their systems flexible and allowing for easy updates and modifications as regulations evolve. 
• Transparency: Trust in AI-driven decisions hinges on transparency. People need to understand how AI agents collect, process, and use their data, and be confident that their privacy rights are being respected. Explainability is key — AI agents should be able to provide clear and understandable explanations for their decisions.

Prioritizing privacy and security through agentic AI

Salesforce customer Precina, a healthcare company specializing in diabetes care, is an example of a company that is putting agents to work for patient privacy and organizational security. 

Instead of a patient waiting months for a clinical visit to adjust a medication dose or review a new dietary habit, Agentforce taps into Salesforce Health Cloud and Data Cloud to instantly access their medical records, lab results, and prescription history. It then uses that data — securely and in compliance with HIPAA standards — to deliver tailored suggestions, recommend incremental lifestyle changes, and even coordinate prescription refills. 

By embracing a privacy-first approach, businesses in any industry can leverage the power of AI agents to drive efficiency, innovation, and growth while safeguarding user privacy and security.

Go deeper:

• Read how Salesforce builds trust in the agentic AI era
• Learn how to navigate the changing regulatory landscape
• Discover key considerations for integrating AI agents responsibly

Blog Article: Here