Blog
By Jeffrey Dirrenberger, CEO
The question comes up in almost every kickoff call: "Should we start with web or mobile?" It sounds straightforward, but the answer shapes everything – your timeline, your budget, and your ability to reach users quickly. After years of guiding product launches across industries, I've seen this decision made both brilliantly and badly. The difference isn't luck. It's clarity about what actually matters for your specific business.
A recent MIT report revealed a staggering statistic: 95% of generative AI pilots fail to reach production. As TechNexus Director of Strategy Matt Meyers aptly noted in a recent post, "Not because models don't work, but because organizations underestimate the hard part: integrating AI into messy, real-world workflows."
This resonates deeply with what we see at VAULT. The problem isn't the technology – it's the implementation discipline.
According to Informatica's CDO Insights 2025 survey, the top obstacles to AI success are data quality and readiness (43%), lack of technical maturity (43%), and shortage of skills (35%). These aren't technology problems. They're organizational challenges that require a fundamental shift in how companies approach innovation.
After helping businesses build hundreds of custom applications and digital products, I've identified three critical missteps:
Too many organizations approach AI like they're checking a box. They launch a pilot, declare victory at the demo, and wonder why adoption flatlines.
The companies that succeed – the 5% that actually reach production – treat AI like any other product development cycle. They start with measurable business outcomes ("reduce customer support resolution time by 40%"), build iteratively, and design for the end user from day one.
As Meyers notes in his analysis, successful implementations "start with clear business goals, invest early in clean, accessible data, and design for adoption with employees, not around them."
At VAULT, we've seen brilliant AI models fail because they were built on fragmented, inconsistent, or inaccessible data. The winning programs we've observed allocate 50-70% of their timeline and budget to data readiness – not model training.
This isn't glamorous work. It doesn't generate press releases. But it's the difference between a proof-of-concept that impresses stakeholders and a solution that actually ships.
The most sophisticated AI in the world is useless if employees don't trust it, understand it, or integrate it into their daily workflows. According to a McKinsey analysis, companies that fully integrate AI into their organizational structure see a 54% increase in productivity – but only when the integration is intentional and human-centered.
Change management isn't an afterthought. It's the entire game.
Over the past decade, VAULT has developed a framework that prioritizes integration from the start:
Start Small, Prove Value, Scale Deliberately
We resist the "big bang" approach. Instead, we identify one high-impact workflow, deliver a measurable win, and use that momentum to expand. As Meyers puts it: "Pick one workflow, prove value, and expand from there."
Build for Existing Workflows, Not New Ones
The best AI solutions feel invisible. They enhance what people already do rather than forcing them to learn entirely new processes. We design with employees, not around them – because adoption is everything.
Invest in the Unsexy Stuff
Data infrastructure, change management, and iterative testing don't make for exciting pitch decks. But they're what separate the 5% that succeed from the 95% that stall.
Measure What Matters
Vanity metrics don't move businesses forward. We anchor every AI initiative to concrete business outcomes – revenue growth, cost reduction, customer satisfaction – and track progress relentlessly.
Large Organizations: Success isn't about being everywhere – it's about being effective somewhere specific. Pick one platform, one workflow, one measurable outcome. Expand after you've proven the model.
Investors & Advisors: The strongest product strategies balance ambition with execution reality. Push your portfolio companies to demonstrate not just what they're building, but how users will actually adopt it.
Growing Companies: Your launch platform isn't permanent – it's strategic. Start where your users are most active, validate your core value proposition, then scale across channels with confidence.
AI fatigue is real because most organizations are exhausted from chasing shiny objects without seeing tangible returns. The antidote isn't to abandon AI – it's to approach it with the same rigor we apply to any other strategic investment.
At VAULT, we've built our reputation on exceeding expectations through cutting-edge technology and disciplined execution. We don't just build software; we build solutions that integrate into the messy reality of how businesses actually operate.
The 95% failure rate isn't inevitable. It's a choice. And the companies that choose differently – that prioritize integration discipline over technological novelty – will be the ones that actually realize AI's transformative potential.
About the Author
Jeffrey Dirrenberger is the CEO and Founder of VAULT Innovation Group, a Chicago-based custom software and digital product development company. With over 15 years in the tech industry, he has helped launch over 100 companies and built products across consumer applications, B2B software, and tech-enabled businesses. Learn more about VAULT's work at vaultinnovation.com/work.
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