Managing Director på Northridge Analytics

Most companies aren’t struggling with AI.
They’re struggling with the foundations underneath it.

After 11+ years working across enterprises as an advisor in data strategy, governance, and AI, I keep seeing the same pattern:

✔ Vision is high
✔ Tools are expensive
✔ AI pilots are promising
✘ But the foundations ownership, definitions, lineage, quality, access are nowhere near ready

That’s the real reason AI initiatives stall.
Not because the model is wrong, but because the organisation is.

As Managing Director at Northridge Analytics and President of DAMA Sweden, I help CDOs, CIOs, and Data/AI Leaders fix governance debt, build stable data foundations, and create the conditions where AI can actually work at scale.

Enterprises call me when they see symptoms like:
• Conflicting definitions (revenue, customer, product…)
• Multiple “sources of truth”
• AI pilots that don’t survive contact with the real data
• Shadow processes and tribal knowledge slowing everything down
• Reporting chaos and lack of trust in numbers
• Architecture drifting faster than governance
• A growing gap between strategy decks and operational reality

What I deliver:
► Data Governance Maturity Assessment (DAMA-based, fast, honest, executive-ready)
► Governance Program Build-Out (clear ownership, definitions, lineage, quality, access)
► AI & Data Foundations Roadmaps (strategy → architecture → execution)
► Retained Advisory for CDOs & CIOs (ongoing decision support, structure, prioritization)

My work is practical, politically aware, and focused on business value not frameworks for the sake of frameworks.

If your AI ambitions are growing faster than your foundations or if you want an unfiltered view of where your governance truly stands send me a message with “Governance” or “AI Map”.

Let’s make sure your organization is ready for the AI you’re trying to scale.

If your entire AI strategy collapses when Tom is on vacation, you don’t have an AI strategy. You have a dependency.

And this is how most org charts really work:

CEO
↓
CTO
↓
CDO
↓
AI Lead
↓
Data Team (trying their best)
↓
Tom
Owns everything. No documentation. Knows every workaround ever invented.

This is the part nobody wants to admit.
You can talk GenAI, agents, copilots, platforms.
But if all your critical data flows through one person’s head, nothing scales.

Tom is not the problem.
The system around Tom is.

Every company has a Tom.
Only a few fix the root cause.

➤ Hit Follow John for daily, no-fluff insights on data, AI, and what actually works.
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John Wernfeldt

I help CDOs, CIOs & Data and AI Leaders fix data governance and foundations so AI actually works. | AI & Governance Advisor | MD @ Northridge Analytics | President, DAMA Sweden

Frankly, this is the part no one wants to admit.

Every AI strategy eventually becomes one thing:

→ A data engineering project

Because behind the “AI Steering Group”
→ Strategy Consultants
→ Innovation Lab
→ Enterprise Architects
→ PMO
→ AI Ethics Council

…there is always one person:

→ The data engineer keeping everything alive

The real blockers are never the model. They are the usual suspects:

→ Broken pipelines
→ Missing lineage
→ Ownership confusion
→ Legacy systems
→ Random CSVs
→ Ask Tom

If u want AI that actually works, start where the pain lives:

→ Access
→ Quality
→ Integration
→ Governance
→ Engineering

Everything else is theatre.

➤ Hit Follow John for daily, no-fluff insights on data, AI, and what actually works.
🔔 Tap the bell on my profile to get notified when I post.
♻️ Repost if u found this valuable.

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Honestly, this is the AI loop inside 90 percent of companies.

CEO:
→ “Where’s your AI ROI?”

Business people:
→ “Where is it?”

Meanwhile the business is out there building six random AI pilots on top of:
→ Broken source systems
→ Missing owners
→ Zero lineage
→ Ten versions of the truth
→ And a data foundation that’s basically a group chat + some Excel exports

Everyone wants AI ROI.
No one wants to fix the data that creates it.

If u want help setting up a data foundation that actually delivers ROI, DM me “governance”.

I help CDOs, CIOs & Data and AI Leaders fix Data Governance and Foundations so AI actually works. | AI & Data Governance Advisor | MD @ Northridge Analytics | President, DAMA Sweden

AI projects always start like a Michelin-star dinner.
Beautiful decks. Perfect mockups. Zero friction.

Then reality shows up.
And suddenly… it’s not the oven that burned the project.
It’s the data, the ownership gaps, the missing lineage, the “temporary” workarounds from 2015, and the 19 systems nobody wants to talk about.

→ Great AI strategy decks are easy.
→ Great AI foundations are not.

Most teams don’t fail because they lack ambition.
They fail because the assumptions inside the deck never survived contact with the actual data.

If u want fewer “burnt chicken” PoCs:
Fix the definitions.
Fix the sources.
Fix the ownership.
Then build the AI.

What’s the most common “hidden ingredient” that burns AI projects in your org?

➤ Hit Follow John for daily, no-fluff insights on data, AI, and what actually works.
🔔 Tap the bell on my profile to get notified when I post.
♻️ Repost if you found this valuable.

I share insights about Data & AI | Data Governance Consultant | ex-Gartner | President DAMA Sweden | Managing Director på Northridge Analytics

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