Forrester Report Highlights AI Agent Readiness Amid Adoption Barriers

Key Takeaways:

• Technological Readiness: Forrester's latest report confirms that the core components for autonomous AI agents are now in place. These agents can perform tasks, make decisions, and interact with systems independently.
• Adoption Barriers: Despite technological advancements, widespread adoption faces hurdles like low trust in AI outputs, employee and consumer skepticism, misaligned workflows, and missing data.
• Key Components: For broader uptake, AI agents require:
  • Tool Discovery & Integration: Solutions like Model Context Protocol (MCP) are critical.
  • Agent-to-Agent Interoperability: Protocols like Agent2Agent (A2A) enable seamless communication between AI agents.
  • Orchestration Capability: Human interfaces are needed to guide AI agents effectively.

Dive Deeper:

• Human vs. AI Workflows: Unlike humans or traditional automation tools like RPA, AI agents can "reason" and determine the next steps in workflows autonomously. However, Stephanie Liu, a Forrester senior analyst, notes that "formal documentation doesn’t always reflect the actual ways people do tasks."
• Use Cases: AI agents are being deployed in consumer engagement, employee support, and enterprise automation, with each sector progressing at different rates.
• Recommendations: Organizations should start small, experiment early, and build a roadmap for AI agent integration. Liu advises, "Give it one step in a workflow and expand from there."

Related Reading:

• No Jitter Roll: Avaya Plans to Adopt Model Context Protocol
• The AI Job Skill Gap to Address: Knowing When It's Wrong

About the Author:

• Matt Vartabedian, Senior Editor at No Jitter, covers AI in enterprise communications. With decades of experience in journalism and market analysis, Matt provides insights into AI's role in unified communications, contact centers, and digital workplaces. Connect with Matt on LinkedIn.