The rise of AI allows for mass-produced yet highly personalized emails that traditional spam filters struggle to detect. This has led to an overwhelming volume of "slop," making the email inbox increasingly dysfunctional. A proposed solution is to rewrite spam laws to prohibit unprompted machine-to-human communication.

Address security concerns by granting AI tools access incrementally. Start with low-risk tasks like drafting content. As you build confidence, gradually allow it to read your emails, then your calendar, and eventually perform actions. This "trust spectrum" approach makes adoption more comfortable.

AI tools for text, image, and video generation allow scammers to create high-quality, scalable impersonation campaigns at near-zero cost. This threat, once reserved for major global brands, now affects companies of all sizes, as the barrier to entry for criminals has vanished.

To encourage safe experimentation, Sendbird provides an app template with pre-built security, authentication, and infrastructure. This 'happy path' allows any employee, like marketers or CSMs, to build and deploy AI tools without needing to be a security or infrastructure expert.

AI agents using free consumer services like Gmail for tasks will inevitably get banned for bot-like activity. This creates a clear market opportunity for API-first infrastructure built specifically for agents, such as AgentMail, which provides a reliable, stateful email service that won't be shut down.

Implementing DMARC for email security has an unexpected benefit: it reveals all services sending emails on behalf of a domain. This gives MSPs and IT departments visibility into unauthorized or unknown SaaS tools used by teams like marketing, effectively turning a security measure into a discovery tool.

The sophistication of attacks like the Axios NPM compromise necessitates a shift to AI-driven defense. Tools like Cognition's Devin Review are reportedly catching malware before public disclosure, indicating that organizations must adopt AI security tools to counter the rising threat of automated, AI-powered attacks.

Adopting AI in the enterprise requires solving two distinct problems. The first is data security from external threats, addressed by certifications like FedRAMP. The second, and separate, issue is internal control: ensuring AI agents have the right permissions and guardrails to prevent them from "going rogue."

Unlike training a human, feeding an AI SDR historical 'good' emails can limit its effectiveness. The better approach is to train it on core personas and ways to add value, allowing the AI to use its ability to scrape vast, real-time data for hyper-personalization.