Preparing IT for the Future: How MCP and AI Agents Transform Infrastructure
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Artificial intelligence has become ubiquitous in technology. If you work in IT or development, you’ve likely encountered AI projects or will soon. Understanding how to evolve your IT architecture to be AI-ready requires looking at where AI came from and what it’s trying to replicate: the human brain.
The Current State: AI Swallows the Enterprise
Today’s AI landscape began with large language models consuming vast amounts of internet data. GPT-driven models processed text and images from across the web, creating powerful general-purpose tools. This first paradigm worked well for broad applications, but it presents challenges inside organizations.
Enterprise environments differ fundamentally from the open internet. Organizations care about specific data relevant to their operations, not everything available online. They rely on a mix of SaaS applications, internally developed tools, and networking infrastructure that connects everything together.
The problem? We’re currently in a “plus AI” paradigm, attempting to jam AI into existing enterprise infrastructure. The results speak for themselves: over 90% of AI initiatives structured this way are failing.
What We Can Learn from the Human Brain
To build better AI systems, we need to understand what artificial intelligence is actually trying to mimic: human intelligence. Every biological organism has a body plan, which is essentially an architecture for processing data from the environment and generating responses.
The human brain organizes itself into three distinct regions:
Lower Brain: Handles primitive functions like temperature regulation and basic physical responses. This is where fundamental survival mechanisms operate.
Midbrain: Manages connectivity and data exchange. It determines what information gets ignored, what gets stored in memory, and what gets routed to different brain regions. The midbrain also contains structures that enable communication between the left and right hemispheres.
Upper Brain: Provides executive functioning and integration. The frontal area acts as the pilot, deciding what to do next based on integrated information from all sources. Other regions process auditory data, visual information, and enable long-term strategic thinking.
The Brain’s Secret Weapons
Two capabilities make the human brain remarkably effective:
Integration: The brain excels at combining information from multiple senses and sources. When you recall a beach memory, you might simultaneously remember the smell of salt air, the sound of waves, the taste of food, and even the pain of stepping on a sharp shell. This seamless integration across different data types is what we struggle to replicate in technology.
Selective Attention: The brain ignores approximately 99.8% of all data it encounters. During your morning commute, you don’t remember the sequence of car colors or most vehicle makes and models unless something unusual appears. The brain stores what stands out and what’s likely to be important in the future.
Traditional Enterprise Architecture: A Star Problem
Most enterprise IT architectures organize around three categories:
Applications: Executive functioning systems that do things
Data: Various types of stored information
Network: Communication infrastructure connecting everything
A typical enterprise might include a CRM system, an HRIS platform, financial accounting software, and a contract management system. These applications connect to a data layer, often structured as a data lake.
The traditional approach creates what amounts to a star structure. Applications connect through APIs in very specific ways. The CRM talks to the HRIS, which connects to the financial system, which interfaces with contract management. Each integration performs predetermined tasks with little room for flexibility.
This rigid structure works for planned operations but becomes problematic when you can’t leave anything to chance. Any deviation causes things to break.
The MCP Revolution: Making IT AI-Ready
Transforming enterprise architecture to be AI-ready requires introducing two new elements without disrupting current operations.
Orchestration Layer
First, you need an orchestration layer that can spawn multiple AI agents. These agents work across your infrastructure, performing tasks and gathering information as needed.
Model Context Protocol (MCP) Services
Second, each application and data source needs to expose itself through MCP services. This protocol transforms applications into sets of:
Tools: What the application can do
Data sources: What the application knows about
When you add orchestration and transform applications into MCP services, you create a fundamentally different architecture. Applications become specialized organs, similar to different brain regions. Your CRM might function like auditory processing, your HRIS like sensory input, your financial system like strategic planning, and your contract management like motor coordination.
Agents as Synapses
In this new architecture, AI agents function like synapses connecting neurons in the brain. When you need to accomplish something complex, the orchestration layer acts like the brain’s frontal lobe, determining which specialized systems to activate and how they should work together.
The orchestration layer focuses on:
Goals: What you’re trying to achieve
Outcomes: What results are acceptable
Agents light up across different functional areas of your application layer, moving between systems and diving into relevant data sources as needed. This mirrors how the brain activates different regions to accomplish integrated tasks.
The Path Forward
The goal isn’t just to add AI to existing infrastructure. It’s to reorganize enterprise IT to mirror the integrated, compartmentalized, and efficient functioning of biological intelligence.
An AI-ready architecture shares key characteristics with the human brain:
Integration: Seamless information flow across specialized systems
Compartmentalization: Distinct functions in dedicated areas
Organization: Clear structure with defined roles
Efficiency: Compact design that operates with minimal overhead
Selectivity: Focus on relevant information while filtering noise
By moving from rigid API connections to flexible MCP services orchestrated by AI agents, enterprises can achieve the 80%+ success rates that currently elude most AI initiatives.
The transformation from data lakes to AI-ready data layers, combined with MCP-enabled applications and intelligent orchestration, creates an infrastructure that doesn’t just accommodate AI but is fundamentally designed for it. This approach allows organizations to leverage artificial intelligence the way nature intended: as an integrated, efficient system that mirrors the remarkable capabilities of human cognition.
To learn more about how Terzo can help your enterprise plan for the future, reach out to the team at Terzo for a free consultation.
