AI PROJECT FAILURE RATES DRIVE TRUST INSIGHTS TO RELEASE FREE AI READINESS ASSESSMENT FRAMEWORK AND CHECKLIST

Five-minute evaluation tool helps enterprise teams benchmark data foundations, governance maturity, infrastructure readiness, and technical feasibility.

BOSTON, MA, UNITED STATES, February 4, 2026 /EINPresswire.com/ -- With industry analysts including Gartner predicting that data readiness issues will cause the majority of AI project failures in 2026, Trust Insights today released a free AI Readiness Assessment designed to help organizations evaluate their preparedness for AI initiatives and identify critical gaps in their data foundation, governance, infrastructure, and organizational maturity before AI implementation begins.

The AI readiness assessment framework arrives at a pivotal moment for enterprise AI adoption. As organizations move beyond experimental pilots toward full-scale operationalization of AI projects, the gap between ambition and actual organizational readiness has become increasingly apparent. Research from MIT CISR maturity models and enterprise frameworks from major technology providers like Microsoft, AWS, and Cisco consistently demonstrate that many AI initiatives fail not due to technology limitations, but because organizations lack the data foundation, data quality, governance frameworks, technical infrastructure, skills, talent, and organizational maturity required for AI project success.

"Every week we talk to organizations that have invested heavily in AI tools but haven't addressed the fundamentals—their data quality is poor, their data hygiene and data availability practices are inconsistent, their processes aren't documented, and their teams lack the AI literacy skills to manage and audit AI outputs," said Katie Robbert, CEO of Trust Insights. "This AI readiness assessment helps surface those organizational readiness issues before they become expensive project failures."

The AI Readiness Assessment uses the Trust Insights 5P Framework to evaluate organizational readiness across twenty questions spanning five critical dimensions—incorporating pillars from enterprise maturity models, standardized frameworks from organizations like the ITU and Oxford Insights Government AI Readiness Index, and cloud adoption frameworks from major technology providers:

Strategy and Purpose evaluates strategic clarity, business alignment, and leadership sponsorship, including whether the AI project addresses a documented business problem with clear ROI metrics, technical feasibility criteria, and measurable success benchmarks aligned to the organization's strategic roadmap. This dimension assesses whether initiatives solve high-priority business needs rather than experimental pilots.

People and Talent assesses team readiness, skills, talent, and organizational culture, examining executive sponsorship, change management, dedicated project leadership, and whether team members possess the foundational AI literacy and AI fluency needed to work effectively with AI systems while maintaining critical thinking capabilities that prevent skill atrophy—a key concern in 2026 readiness frameworks.

Process and Governance examines workflow documentation, human-in-the-loop review protocols, responsible AI policies, and governance procedures for handling AI errors and hallucinations—critical guardrails for any autonomous or agentic AI deployment that requires bounded autonomy within governed parameters. This includes compliance considerations for protocols like the Model Context Protocol (MCP) and agent-orchestrated automation.

Platform and Infrastructure evaluates technical infrastructure, data foundations, digital infrastructure, security compliance, and tool accessibility. The assessment examines whether data is accessible, organized, and not trapped in silos, whether enterprise-grade platforms and cloud-native tools are approved by IT and security teams, and whether proper safeguards and sandbox environments protect against unauthorized data training—essential considerations for sovereign AI requirements, jurisdictional integrity, and compliance with regulations such as the fully applicable EU AI Act.

Performance and Measurement reviews measurement readiness, success criteria, scoring methodology, and continuous monitoring capabilities, including baseline metrics, cost calculations using ROI frameworks, budget allocation, scheduled success reviews, and alignment with the organization's twelve-month strategic priorities and business initiatives. This dimension ensures organizations can demonstrate value and track AI project outcomes including model drift.

Upon completion of the 20-question assessment, users receive a personalized maturity grade along with specific, actionable recommendations tailored to their organization's gaps. The assessment provides a clear rubric and scoring system for evaluation using technical readiness levels (TRL) similar to those used by enterprises to benchmark project feasibility, with organizations typically requiring higher readiness scores before receiving full funding for AI initiatives.

The tool reflects Trust Insights' experience across hundreds of AI implementations and aligns with established AI readiness assessment frameworks including the AWS Cloud Adoption Framework for AI (CAF-AI), Microsoft AI Readiness Assessment pillars covering AI Governance, Data Foundations, and Model Management, Cisco AI Readiness Index categories that benchmark organizations as Pacesetters, Chasers, Followers, or Laggards, and the governance standards emphasized in the ITU Standardized Readiness Framework. These frameworks collectively address everything from data availability and digital infrastructure to model management, inference efficiency, and continuous monitoring for model drift.

"The most successful AI projects and initiatives we've seen share a common trait: the organization honestly evaluated its AI readiness using a structured assessment framework and checklist before committing resources," said Christopher Penn, Chief Data Scientist at Trust Insights. "This AI readiness assessment gives every organization—regardless of size or budget—access to that same evaluation methodology and benchmark scoring that enterprises use to determine technical feasibility, data readiness, and organizational preparedness for AI implementation."

The free AI Readiness Assessment is available immediately at https://www.trustinsights.ai/ai-readiness-assessment.

About Trust Insights
Trust Insights is a data analytics and AI consulting firm founded in 2017 that helps enterprise marketing and business teams operationalize AI through rigorous AI readiness evaluation, data foundation assessment, governance implementation, and infrastructure planning. The company's methodology addresses the full spectrum of organizational AI maturity—from initial feasibility assessment and technical readiness evaluation through pilot programs to industrialized AI operations with real-time observability and performance monitoring. Specializing in AI readiness assessment frameworks, data quality and data hygiene benchmarking, ROI calculation, and compliance with emerging AI regulations including the EU AI Act, Trust Insights serves organizations seeking to evaluate their platform infrastructure, improve data availability, benchmark their AI readiness against industry standards, and build the skills, processes, talent, tools, and governance required for successful AI project implementation. Headquartered in Boston, MA. For more information, visit https://www.trustinsights.ai.

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