Back to Dashboard Created: 2026-02-01 03:47

Research One-Pager

Topic: Research request for latest trends in AI agents

Prepared by Moltbot Lite

PKT Research Digest

Structured Analysis: Latest Trends in AI Agents (2025-2026 Outlook)

Compiled: | Topic: Strategic Technology Research

1. EXECUTIVE SUMMARY

The discourse around Artificial Intelligence is undergoing a fundamental shift from generative AI tools to autonomous, goal-driven AI agents. While generative AI has entered a phase of market correction ("trough of disillusionment"), AI agents are now at the peak of the hype cycle, poised to redefine business processes and human work by 2026.

This transition marks a move from passive, query-based assistants to active, multi-step systems capable of planning, acting across applications, and coordinating with other agents. The core implication is a transformation of the human role from task-doer to AI orchestrator and manager, with significant impacts on productivity, security, customer experience, and enterprise architecture.

2. KEY FINDINGS

  • From Tools to Teammates: AI is evolving beyond chatbots. Agents are goal-driven systems that plan, act, and coordinate across apps, with humans in a supervisory, not micromanaging, role.
  • Human Role Redefinition: The core job for employees is shifting to becoming "AI managers"—defining goals, delegating to agents, reviewing outputs, and making critical judgment calls.
  • Workflow Supremacy: Competitive advantage will stem from building sophisticated "agentic workflows" or "digital assembly lines" where multiple agents collaborate, rather than from owning the best single AI model.
  • Ecosystem Interoperability: The next platform shift is agent-to-agent (A2A) communication. Open standards (e.g., Agent2Agent, Model Context Protocol) are critical for agents from different vendors to interact and access tools/data, enabling scalable ecosystems.
  • Democratization of Creation: Building and deploying intelligent agents is moving beyond developers to everyday business users, lowering technical barriers and driving innovation from the front lines.
  • Market Trajectory: Experts predict AI agents will handle most transactions in large-scale business processes within 5 years, but the technology is expected to enter its own "trough of disillusionment" around 2026 following current hype.
  • Key Application Areas: Trends point to transformative use in concierge-level customer service (proactive, personalized), agentic security (autonomous threat remediation), and agentic commerce (monitoring and transacting within guardrails).

3. FEASIBILITY / RECOMMENDATION

Analysis: High Strategic Value, Approaching with Measured Pragmatism

The trend toward agentic AI is not speculative; it is a logical evolution of current AI capabilities with clear, near-term business applications. The convergence of workflow automation, LLMs, and interoperability standards makes this a highly feasible direction for investment.

However, the current hype level is a warning. The prediction of a 2026 "trough of disillusionment" suggests that overpromising and technical challenges (reliability, security, cost) will lead to a market correction. Therefore, the recommendation is to engage strategically but avoid "hype-driven" procurement.

Recommended Next Steps:

  1. Internal Capability Assessment: Identify 1-2 high-volume, rule-based business processes (e.g., IT ticket triage, routine customer inquiries) as pilot candidates for agentic workflow design.
  2. Focus on Orchestration, Not Just Agents: Invest in understanding "agent control planes" and multi-agent dashboards. The strategic value lies in workflow design and human-agent interaction models.
  3. Governance & Security First: Develop internal policies for agent authorization, accountability, and data access before deployment, especially for agents that initiate transactions.
  4. Skill Development: Begin training programs focused on "AI management" and agent orchestration skills to prepare the workforce for the shifting role.

4. SOURCES & NEXT STEPS

Primary Sources Analyzed:

Specific Actionable Tasks:

  • Task 1 (2 weeks): Convene a cross-functional workshop (IT, Operations, Security) to map one candidate process for agentic automation.
  • Task 2 (1 month): Research and evaluate two "low/no-code AI agent builder" platforms (e.g., n8n, Zapier with AI) for rapid prototyping.
  • Task 3 (Ongoing): Monitor developments in Agent-to-Agent (A2A) communication standards (Agent2Agent, MCP) to inform future architecture decisions.
  • Task 4 (Quarterly): Review market analysis from Gartner/Forrester on the AI agent space to track the hype cycle and vendor landscape maturation.
© 2026 Moltbot Lite. All rights reserved.