NextAI Foundry Blog
Application Assessment & Modernisation
Practical insights for enterprise architects evaluating agentic AI readiness across large application portfolios.
18 July 2026 · 9 min read
Model Context Protocol: Why MCP Is the Most Consequential Recent Development in Agentic AI
The agentic AI conversation in 2026 has been dominated by model capability. The more consequential shift happened at the protocol layer: Model Context Protocol, Agent2Agent, and Agent Communication Protocol are standardising how agents connect to enterprise systems — and changing what Integration readiness actually means for every application in your portfolio.
Read articleAI Readiness Scorecard: How Enterprise Architects Score and Rank Applications for AI
An AI readiness scorecard gives enterprise architects a single, defensible number for each application in their portfolio — showing exactly where each system sits across five structural dimensions and what investment is required to advance. Here is how the scorecard works, what it measures, and how to use it to prioritise AI deployment across a complex enterprise portfolio.
30 June 2026 · 8 min read
AI Readiness Report: What Enterprise Architects Need in an Assessment Output
An AI readiness report is the output that transforms assessment scores into an actionable investment plan. Here is what a rigorous AI readiness report contains, why most internal assessment outputs fall short, and what the report needs to communicate to move a board-level AI programme from diagnosis to committed action.
30 June 2026 · 7 min read
AI Readiness Checklist for Enterprise Architects: Generative AI Deployment
Enterprise architects evaluating generative AI adoption need a fast, repeatable way to assess each application in their portfolio before committing to deployment. This checklist covers the five structural dimensions that predict production success — with specific questions, red-flag patterns, and the remediation priorities that unlock generative AI capability fastest.
29 June 2026 · 9 min read
Generative AI in the Enterprise: Why Most Deployments Stall Before Production
Enterprise interest in generative AI has never been higher — and neither has the rate of failed production deployments. The models are not the problem. The application infrastructure that generative AI systems need to operate on is. Here is the pattern that separates the organisations scaling generative AI from those perpetually in pilot.
28 June 2026 · 10 min read
What Is AI Readiness? Why Enterprise Initiatives Fail and What to Measure First
Most enterprise AI adoption programmes stall not because of the model or the budget, but because of the application infrastructure they run on. Here is the structural readiness question that determines whether your AI adoption scales beyond the pilot stage — and why most organisations are measuring the wrong things.
27 June 2026 · 8 min read
AI Readiness Assessment Framework: The Enterprise Model That Works
Most enterprise AI adoption frameworks focus on strategy and governance — and stall when they reach the application infrastructure. A structured assessment framework that scores your portfolio against the structural criteria AI agents actually require is what separates programmes that scale from those that produce impressive pilots and little else.
26 June 2026 · 9 min read
What AI Readiness Means in 2026: Why Infrastructure Beats Model Selection
Enterprise AI adoption is the top technology priority in 2026 — and the top source of misallocated investment. Organisations are spending on models, platforms, and talent while the actual constraint on AI adoption sits in their application portfolio. Here is what that constraint is, why it matters more than model selection, and what separates the enterprises scaling AI from those stuck at the pilot stage.
25 June 2026 · 11 min read
How to Assess AI Readiness: Enterprise Application Portfolio Guide
Most enterprises commit AI adoption budgets before they know which applications can actually support production deployment. A structured portfolio assessment changes that sequencing — surfacing the ready candidates, the remediable ones, and the genuine blockers before a single line of agent code is written.
24 June 2026 · 10 min read
Agentic AI Readiness: The Five-Level Enterprise Maturity Model
Enterprise AI transformation means different things at different organisations — co-pilot tools, workflow automation, autonomous agents, or something in between. This five-level model gives teams a precise framework for locating where their application portfolio sits today, what each level unlocks, and what structural investments are required to advance.
19 June 2026 · 11 min read
Five Signs Your Legacy Application Is Ready for Agentic AI
Most enterprise applications were built before AI agents existed as a concept. Here are the five structural signals that predict whether a legacy system can absorb agentic capabilities without a full rewrite.
10 June 2026 · 7 min read
Understanding the Migration Readiness Score: How We Calculate MRS
The MRS is a composite of five weighted dimension scores. This post explains the methodology, the weightings, and why we chose these specific dimensions over alternatives like cloud-native maturity models.
3 June 2026 · 9 min read
Should You Modernise Before Adopting AI? The Sequencing Debate
Some enterprise architects insist on a clean modernisation programme before any AI adoption. Others say adopt AI first to fund modernisation. Both positions are wrong. Here is the sequencing logic that actually works.
27 May 2026 · 8 min read