Security Reviews for Seller AI Tools: A Checklist

The sales floor is buzzing with AI, and for good reason. But for every new efficiency gained, a new security question arises. With a staggering 75% of sales teams expected to use AI-powered tools by 2025, security professionals are facing a tidal wave of new vendor requests. The problem? Your traditional security questionnaire is no longer enough.

AI sales tools, especially those that handle voice commands and integrate directly with your CRM, operate on a completely different level. They create complex data flows that standard security checklists were never designed to evaluate. Trying to assess a generative AI tool with a playbook from 2015 is like trying to road-test a spaceship with a driver's manual. It’s time for a new approach, one centered on the single most critical element: the data itself.

Why Your Old Security Playbook is Obsolete

Standard vendor assessments focus on familiar territory: access controls, encryption standards, and maybe a SOC 2 report. While these are still important, they miss the unique risks introduced by AI.

According to a recent report from Vena Solutions, as generative AI adoption rises, "concerns about data privacy and security" are increasing proportionally. This isn't just paranoia; it's a rational response to new threats. Cisco’s 2025 State of AI Security Report identifies critical, AI-specific attack vectors like prompt injection, data poisoning, and data extraction attacks that can turn a helpful AI assistant into a security liability.

When a sales tool can listen to voice commands, transcribe conversations, and update your Salesforce records, you need to ask questions that go beyond a typical SaaS application:

• Where does the voice data go for transcription?

• How is that unstructured data processed?

• Is customer PII sent to a third-party AI model like GPT-4 or Claude?

• How long are transcripts and audio files stored after the task is complete?

Failing to answer these questions exposes your organization to compliance violations, data breaches, and significant reputational damage. The key is to shift your focus from static controls to the dynamic journey of your data.

The Data Flow Diagram: Your New Best Friend

You don't need to be a systems architect to perform a modern security review for sales AI tools. You just need to think like one. The most effective way to analyze the security of an AI tool is to map its data flow from creation to deletion.

By breaking down the tool’s process into three key stages—Scopes, Storage, and Deletion—you can build a comprehensive security profile that addresses the real risks. Let's turn this concept into a practical checklist.

The AI Security Checklist

1. Scopes: What Data Goes In?

Before data can be compromised, it must first be accessed. The principle of least privilege is more critical than ever with AI. Your first step is to rigorously define the tool’s access scope.

Your Checklist Questions:

• Access Scope: Does the tool demand broad, "read-all" access to your CRM, or does it operate on a need-to-know basis? Be wary of any tool that requires blanket permissions to function.

• Data Types: What specific data is being ingested? Is it just names and emails, or is it unstructured voice data, conversation notes, and sensitive deal information? The more sensitive the data, the higher the scrutiny required.

• Third-Party Flow: Where is the data really going? Does the vendor process data on their own infrastructure, or do they pass it to a large language model (LLM) provider? You must assess the security of every link in the chain.

For example, a tool like getcolby.com operates as a Chrome extension that interacts directly with Salesforce. This architecture can inherently limit its scope. Instead of being a separate system requiring sweeping API access, it works within the secure environment of the user's browser, acting as an intelligent interface to the CRM you already trust. This is the kind of security-first design you should be looking for.

See how a security-conscious architecture can streamline your sales workflow. Explore the Colby approach.

2. Storage: Where Does Data Live?

Once data is ingested, it has to live somewhere—both in transit and at rest. Salesforce itself states that data security is "non-negotiable" for AI sales tools, requiring "encryption to protect data in transit and storage, along with access controls."

Your Checklist Questions:

• Encryption: Is all data encrypted with strong, modern standards (e.g., TLS 1.2+ in transit, AES-256 at rest)? This is a baseline requirement, not a bonus feature.

• Data Residency: Where are the vendor's servers located? If you're subject to GDPR or other regional data protection laws, the physical location of stored data is a critical compliance point.

• Data State: Is sensitive data anonymized or pseudonymized during processing? For a voice-to-text tool, the raw audio file is far more sensitive than the resulting text update in a Salesforce field. How does the vendor handle these different data states?

• Vendor Certifications: Does the vendor have a SOC 2 Type II report or ISO 27001 certification? While not a complete picture of AI security, these reports provide a valuable baseline for their overall security posture and control environment.

A responsible AI tool should be designed to minimize its data footprint. The goal is to process the data to complete a task—like when a user tells Colby to "update all my open opportunities in San Francisco to Stage 4"—and not hold onto the sensitive inputs longer than necessary.

3. Deletion: How is Data Forgotten?

The "right to be forgotten" is a cornerstone of modern data privacy regulations like GDPR and CCPA. For AI tools that may create and store copies of your data, a clear and auditable deletion process is non-negotiable.

Your Checklist Questions:

• Retention Policies: Does the vendor have a clearly defined data retention policy? How long are voice recordings, transcripts, or other temporary data stored before being permanently deleted? Look for specifics, not vague promises.

• User-Initiated Deletion: Can an administrator or user manually trigger the deletion of their data from the vendor's systems? This is crucial for both compliance and user control.

• Proof of Deletion: How does the vendor verify that data has been permanently and irretrievably deleted from all systems, including backups?

• Third-Party Purge: This is the question most security teams forget. If the vendor sent your data to a third-party AI model for processing, is that data also deleted according to your retention policy? Many LLM providers have their own data retention policies that may not align with yours.

The most secure tools are often the ones that have the least to delete. By focusing on ephemeral processing, tools can execute a command and immediately purge the input data. For instance, a well-designed tool processes a voice command to update Salesforce, confirms the update, and then has no business reason to retain the original audio file, minimizing the long-term risk.

Vet Smarter, Not Harder

The explosion of AI in sales doesn't have to mean an explosion in your attack surface. By moving away from outdated checklists and adopting a data-centric approach, you can confidently evaluate and approve tools that empower your sales team without compromising your organization's security.

This new framework—focusing on Scopes, Storage, and Deletion—gives you the clarity to cut through the marketing hype and assess what truly matters. It allows you to quickly identify vendors who have built security into the core of their product versus those who have bolted it on as an afterthought.

Don't let security reviews become a bottleneck for innovation. Equip your team with the right framework to make smart, secure decisions.