AI Readiness
Your AI Is Only As Smart As Your Data Foundation
Every enterprise has an AI strategy. Most don’t have the data to make it work. Get an AI-ready data foundation in 8-12 weeks, not years. Start with the research, the assessment, and the roadmap.
42%
Of AI Projects Fail
Due to Data
Readiness
Fivetran/Redpoint, 2025
77%
Say Data
Integration Is
Top AI Barrier
Fivetran/MIT, 2024
68%
With Uncentralized
Data Report Lost
Revenue
Fivetran/Redpoint, 2025
8–12
Weeks to an
AI-Ready Data
Foundation
QuickLaunch Customer Data
Built on the Modern Data Stack
The AI Execution Gap
Most AI
Initiatives Don’t
Fail Because Of
Bad Technology
They fail because the data feeding them is fragmented, inconsistent, and ungoverned. Companies invest millions in AI tools and talent, then discover their data isn’t ready for any of it.
Fragmented Data Sources
74% of enterprises manage 500+ data sources across ERP, CRM, financial planning, and operational systems. AI can’t reason across data it can’t see.
Fivetran/Redpoint AI & Data Readiness Survey, 2025
Integration Complexity
Data integration is the #1 barrier to AI success, cited by over a third of enterprises as the top reason AI initiatives fall short.
Fivetran/Redpoint AI & Data Readiness Survey, 2025
Pipeline Maintenance Burden
67% of data teams spend 80%+ of their time just maintaining existing pipelines. There’s no bandwidth left for AI development.
Fivetran/Redpoint AI & Data Readiness Survey, 2025
Governance Gaps
Without data quality controls, lineage tracking, and access governance, AI models produce unreliable outputs that break trust with every stakeholder who sees them.
Skills & Organizational Readiness
80% of leaders use AI tools, but only 6% are actually training their teams to use them well.
The Databricks AI Maturity Model, Economist Impact, 2024.
The Foundation AI Demands
AI Doesn’t Need
More Tools.
It Needs
Better Data.
The organizations succeeding with AI invested in their data infrastructure first. Here’s what that looks like and how QuickLaunch delivers it in a fraction of the typical timeline.
Automated Data Movement
Stop relying on manual exports, batch jobs, and brittle scripts to move data between systems. Automated pipelines connect your ERP, CRM, and operational systems so data flows reliably without constant maintenance. Your data team focuses on building, not babysitting.
Governed Lakehouse Architecture
A modern lakehouse built on Databricks or Microsoft Fabric combines warehouse governance with data lake flexibility. Open formats like Delta and Parquet keep you vendor-neutral. One foundation that supports BI reporting today and AI workloads tomorrow without a rebuild.
Trusted Enterprise Semantic Layer
Pre-built semantic models with consistent business definitions, governed access, and embedded quality controls. This is the layer that makes Copilot and Genie produce answers people actually trust. Production-ready in 8-12 weeks with 20+ years of enterprise data modeling built in.
AI Readiness Playbook
The Research, The Framework, And The 90-Day Roadmap
73% of enterprise data initiatives fail to meet expectations. This guide explains why and what the organizations succeeding with AI did differently. Co-authored with Fivetran and backed by research from Databricks, MIT Technology Review, and Gartner.
✓ Five-Dimension AI Readiness Framework
Score your organization across integration, governance, infrastructure, people, and use case clarity
✓ The Three Foundations
Automated data movement, governed lakehouse, and enterprise semantic layer: what AI requires before it can reach production
✓ What AI Agents Need from Your Data
A 7-point checklist based on research showing 12x more AI projects reach production with unified governance
✓ 90-Day Roadmap
Action plans matched to your maturity stage with milestones you can bring to your next budget conversation
✓ Technology Decision Framework
How to evaluate platforms without getting locked in
AI Readiness Assessment
How AI-Ready
Is Your Organization?
01
Data Integration
Maturity
02
Data Quality &
Governance
03
Infrastructure &
Architecture
04
Organizational
Readiness
05
Use Case Clarity &
AI Ambition
✓ Overall AI readiness score out of 100 mapped to four maturity bands
✓ Dimension-level breakdown showing exactly where your gaps are
✓ Specific next steps tailored to your current maturity stage
✓ Comparison to industry and regional benchmarks
Live Webinar
AI Starts
With Data
April 28, 2026 · 11:00 AM PST / 2:00 PM EST · 60 Minutes
QuickLaunch Analytics CEO Adam Crigger and Fivetran’s Kelly Kohlleffel sit down for a practical conversation about what AI readiness actually looks like inside real enterprises. Grounded in research from Fivetran’s survey of 500+ data and technology leaders.
Plus: Live demos of Databricks Genie and Microsoft Copilot on a governed data foundation.
Adam Crigger
CEO, QuickLaunch Analytics
Kelly Kohlleffel
Sr. Global Director, Partner Sales Engineering, Fivetran
AI Readiness Insights
Research And
Practical Guidance
Why 80% of AI Projects Fail Before They Start
The root causes behind AI project failure rates and what organizations get wrong before they even begin.
Build vs. Buy Your AI-Ready Data Foundation
A comparison of cost, risk, and timeline for building a custom AI data foundation versus buying pre-built.
What AI Actually Needs from Your Data
The specific governance, quality, and architecture requirements your data has to meet before any AI or ML model can produce results you’d trust.
Real Results
Enterprises That Built The Foundation First
“It’s been interesting watching the company become data driven… we know we’re doing a better job at making better decisions.”
Bill Sandblom
Chief Information Officer,
The International Group, Inc.
$72M
increase in annual revenue identified through combined data source visibility
$8M
increase in annual profit using machine learning and AI on unified data
Stop Guessing.
Start Building.
Your AI strategy is only as strong as the data behind it. Whether you’re just starting to explore AI or you’ve had a pilot stall, the path forward starts with your data foundation.