Why AI agents fall short in fragmented hospitality tech

How the Model Context Protocol (MCP) could finally make agentic AI work for hotels

Most AI tools in hospitality promise automation but deliver little beyond surface-level features. The reason isn’t the models themselves — it’s the lack of unified connectivity between the dozens of systems hotels use daily. The Model Context Protocol (MCP) could change that by giving AI agents a consistent, scalable way to interact across all hotel systems.

Key takeaways

• Fragmented systems limit AI’s potential: Hotel tech stacks are filled with isolated systems—PMS, CRM, housekeeping, payments—that prevent AI agents from performing end-to-end tasks.
• Custom integrations slow automation: Each property and vendor pairing requires bespoke API connections, making large-scale automation too complex and expensive.
• MCP acts as a universal connector: The Model Context Protocol lets AI agents discover and orchestrate workflows across all connected systems without new code each time.
• Practical benefits for hotels: With MCP, AI can manage real operational tasks such as rescheduling bookings, automating revenue summaries, or processing accounts receivable—all in real time.
• Roadmap for hoteliers: Operators should assess their “agent readiness,” ask vendors about MCP adoption, test small end-to-end workflows, and measure performance gains to expand gradually.
• Strategic outlook: MCP may become the foundational layer for agentic AI in hospitality, much like cloud computing once did—turning the promise of intelligent automation into daily operational reality.

Ge the full story at Apaleo