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David Ohnstad

AI & Machine Learning in Enterprise Software | Product Management

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Author: David Ohnstad

David Ohnstad is a Senior Data Product Manager based in Minneapolis, MN, writing weekly about AI, machine learning, and enterprise technology. He has over 15 years of experience in data, technology, and product leadership. Connect at https://davidohnstad.net.

The Real Impact of AI and ML on Enterprise Problem-Solving: Beyond the Hype

Some shifts arrive quietly. They don’t make a dramatic entrance, and they certainly don’t wait for an industry white paper to declare their importance. They weave their way into daily routines – a small shortcut here, a smoother workflow there

Published May 20, 2026
Categorized as Enterprise AI and ML

Edge Computing vs. Cloud Computing: Which is the Future?

As businesses strive to improve efficiency, reduce latency, and leverage the power of data, understanding the strengths and limitations of these two computing paradigms is crucial.

Published May 20, 2026
Categorized as Enterprise AI and ML

Building AI Products in the Enterprise: What Actually Works in 2025

Web3, the World Wide Web’s third generation, is full of decentralization and blockchain technology. Artificial intelligence, otherwise known as AI, has the power to transform society. Put them together, and the world as it’s currently known will be technologically revolutionized.

Published May 20, 2026
Categorized as Enterprise AI and ML

Google’s Generative AI Search Revolution: What Enterprise Software Companies Must Do Now

Artificial Intelligence has certainly gained attention in recent years and shows no sign of attracting any less as multiple applications and uses for the digital marvel increase! The question is, how well does AI do in information retrieval? According to

Published May 20, 2026
Categorized as Enterprise AI and ML

The Feedback Loop Problem: Why Most People Learn Slowly Despite Constant Experience

Without effective feedback loops, experience becomes repetition rather than progress.

Published April 28, 2026
Categorized as Enterprise AI and ML

Stability vs Growth: Why Comfort Zones Are Often Misunderstood

Comfort zones are not the enemy of growth; they are part of its structure.

Published April 28, 2026
Categorized as Enterprise AI and ML

From Concept to Launch: The Critical Phases of a Product Management Lifecycle Understanding the Product Lifecycle

Product management revolves around transforming an idea into a solution that fulfills customer needs and aligns with business objectives.

Published January 22, 2025
Categorized as Enterprise AI and ML

Building Scalable Products: Lessons from Rapid-Growth Startups The Essence of Scalability

While product scalability is often discussed in the context of technology, it is equally a matter of strategic foresight and efficient execution.

Published January 22, 2025
Categorized as Enterprise AI and ML

Making Sculptural Furniture: Where Function Meets Art

We discuss how sculptural furniture combines creates functional works of art that redefine how we interact with our living spaces.

Published November 20, 2024
Categorized as Enterprise AI and ML

Designing a Small Woodshop: Maximizing Space and Workflow

With careful planning and attention to detail, even the most modest spaces can be transformed into productive hubs where creativity thrives.

Published November 20, 2024
Categorized as Enterprise AI and ML

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Recent Posts

  • Why Most ML Models Never Reach Production
  • AI in Enterprise Software 2026: What the Data Shows
  • AI Product Roadmaps: Building Teams Before Features
  • AI Governance Theater: Why Dashboards Fail in Enterprise
  • AI Governance in Enterprise: Why Vendor Consolidation Fails

Recent Comments

  1. Google's Generative AI Search Revolution: What Enterprise Software Companies Must Do Now - David Ohnstad on Why AI Models Fail in Enterprise: The 89% Problem
  2. Why Enterprise AI Projects Fail: Platform-First Thinking - David Ohnstad on Enterprise AI Integration: Why Platform Replacement Is a Trap
  3. Enterprise AI Agents: Why Most Companies Should Wait - David Ohnstad on Why AI Models Fail in Enterprise: The 89% Problem
  4. Why Enterprise AI Projects Fail: Platform-First Thinking - David Ohnstad on Why Enterprise AI Projects Fail After POC Success
  5. Real Reasons Enterprise AI Projects Stall at Pilot Stage - David Ohnstad on Why Enterprise AI Projects Fail After POC Success

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