Cognizant packages security for agents as a lifecycle service

What changed: Cognizant launched Secure AI Services to help enterprises secure, govern, and scale AI and agentic systems. The offering covers secure agent development, AI behavior monitoring in production, identity and access management, agent behavior controls, evidence for audits, and generative AI risk management.

Why it matters: Buyers are starting to ask a harder question: “Who is responsible when an agent takes the wrong action?” Cognizant is turning that question into a service line, which means founders and builders should expect enterprise customers to require proof of testing, logging, permissions, and monitoring before buying agent software.

Try/watch: Add an “agent risk packet” to your sales process: what the agent can access, what it can change, how actions are logged, how humans can intervene, and how failures are reviewed.

Sendbird launches an agent designed to own long customer issues

What changed: Sendbird launched Agent Steward on its Delight.ai platform for long-running, multi-step customer cases. It is designed to coordinate across systems, teams, and channels, with sub-agents, cross-channel continuity, and human handoff when judgment is needed.

Why it matters: This is a useful shift for customer experience teams: the agent is not just answering a question; it is meant to be the “owner” of a case from intake to resolution. That matters for businesses where customer problems span logistics, billing, returns, scheduling, or back-office systems.

Try/watch: Pilot this pattern on one painful workflow—damaged shipment, refund exception, missed appointment, failed payment—before using it broadly. Make sure customers can stop, override, or escalate the agent; Sendbird’s own survey says those controls increase trust.

LiveAgent adds named AI agent seats and easier AI-tool connections

What changed: LiveAgent’s May product update says AI Agents will act as virtual agent seats, with AI actions tracked under the AI agent’s name in ticket history, reports, and agent views. It also announced an MCP integration, which lets external AI tools such as Claude Desktop and Cursor access ticket data and perform tasks according to the user’s identity and permissions.

Why it matters: This is especially relevant for small support teams. Naming AI agents and tracking their work makes automation easier to supervise, measure, and explain to staff. The external-tool connection also points to a future where support teams can use their preferred AI tools without manually copying ticket context around.

Try/watch: Before connecting outside AI tools to help-desk data, review role permissions and create a separate AI identity. Start with low-risk tasks like summarizing tickets or drafting replies before allowing transaction changes.