AI agents and chatbots are no longer pilots or side projects. They answer customer questions, pull account details, summarize tickets, and route cases. And as this shift accelerates, companies gain a dangerous blind spot in the conversations and workflows that happen around the clock.
A recent study found that “90% of security leaders” have reported “using unapproved AI tools at work, with 69% of CISOs incorporating them into their daily workflows.” The report also found that approximately 80% of all employees have admitted to doing the same. And while 52% of employees “are familiar with their company’s AI usage policy,” 70% of those surveyed were nevertheless aware of “sensitive data shared with AI tools at their workplace.”
To meet this new risk, SendSafely offers end-to-end encryption infrastructure as a foundational trust layer, sitting between sensitive customer data and the growing set of AI applications that touch it.
SendSafely warns that traditional security tools weren’t built for AI data security
Most traditional security tools assume a simple model. Users transmit a file and store it somewhere. Controls like DLP rules and email gateways are layered around that flow. Secure FTP replacements and access permissions all fall under this same perimeter-minded monitoring.
But today, AI-driven workflows blur the divide between messaging and file sharing in ways older security controls weren’t built to follow. In a typical AI-enabled environment, a customer uploads data mid-conversation, and an agent automatically routes it to another system. Then a bot can hand off the interaction to a human rep without anyone realizing how many systems the data encountered along the way.
Old approaches force users to switch tools, but this adds friction.
“Instead of slowing down the experience with another file transfer tool, today’s companies need encryption infrastructure,” says SendSafely’s Co-founder and Chief Product Officer, Brian Holyfield. “When we embed end-to-end encryption into the systems where work happens, teams don’t need to change behavior because security travels with the workflow.”
In practice, data is encrypted on the sender’s device and can only be decrypted on the authorized recipient’s device. This ensures that no intermediary party, including AI bots or even SendSafely, can access the content without authorization. That is a different guarantee from encrypting data after it reaches a server, or from a vendor that keeps the ability to decrypt.
Why SendSafely says that AI data security needs a new layer of protection
AI drastically increases the number of places sensitive data appears. In fact, the amount of enterprise data flowing through AI and ML apps reached 18,033 terabytes in 2025. Given that 39.7% of those AI interactions expose sensitive data, this 93% year-over-year increase is extremely troubling.
People share what they need to share in a chat to get support or verify their identity. They often bypass best practices to complete a claim or move an onboarding step forward.
“Customers and employees will take the path of least resistance,” notes Holyfield. “Security teams can’t train that away, but they can redesign the workflow to protect sensitive content by default.”
SendSafely HALO handles this with a layer of encrypted data collection for AI chatbots. On platforms such as Ada, Forethought, Intercom, Zendesk, ServiceNow, and Agentforce, the chatbot keeps the interaction moving while HALO encrypts data in real time. End-to-end encryption happens before the files ever contact a server, so neither the chatbot platform nor SendSafely can access the contents.
SendSafely MCP, currently available in limited Beta, provides a local Model Context Protocol server so LLM-driven agents can work with encrypted data operations through an emerging standard. Those agents already retrieve and move data as part of routine work. The SendSafely MCP adds the encryption layer now, rather than later.
How SendSafely’s enterprise AI security infrastructure keeps sensitive data encrypted without disrupting the way teams work
“Security that disrupts work gets bypassed,” Holyfield observes. “Anything that feels separate from the workflow often prompts employees to cut corners, copying sensitive details into chats or using consumer-grade file-sharing links. Modern enterprise security has to be judged on both strength and usability.”
SendSafely’s integrations look and feel like part of the tools teams already use. In Zendesk, agents can collect and send encrypted files inside tickets, while customers upload through a secure widget without leaving the conversation. In Salesforce, encrypted Dropzones embed into Cases or portals..Encrypted file collection in Intercom ties into the Messenger experience, ensuring that both AI-driven and human-assisted support paths maintain protection. And encryption in Gmail’s compose window makes secure sending feel like an everyday action. Recipients are never required to create an account.
For organizations that need custom implementation, SendSafely provides a REST API with SDKs and a Dropzone widget that drops into any page. That covers internal tools and the fast-built, vibe-coded applications now handling real customer data. Encryption still happens on the client side.
“The most effective security strategies add an encryption layer so teams can move fast without compromising on security,” concludes Holyfield. “If AI is becoming embedded in your daily operations, encryption infrastructure needs to be embedded there too.”
