Hey there,

2025 is shaping up to be the year where the AI hype meets reality—and the results are surprising. While 90% of developers now use AI daily, most organizations are still stuck in pilot purgatory. Here's what's actually happening in product workflows, and what we should be thinking about instead.

The Real Story Behind AI Adoption

The numbers look impressive on paper: 78% of organizations reported using AI in 2024, up from 55% the year before. But here's the uncomfortable truth—Gartner estimates that 30% of generative AI projects will be abandoned after proof-of-concept due to poor data quality or unclear business value.

My take: We're treating AI like a Swiss Army knife when we should be thinking about it as a specialized tool. The companies winning aren't the ones using AI everywhere—they're the ones who've identified 2-3 critical bottlenecks and optimized ruthlessly around those.

Workflow Optimization: Back to Basics

While everyone's chasing AI features, companies improving their core workflows are seeing 5-15% efficiency gains—without touching a line of AI code. The workflow automation market is projected to hit $70.9 billion by 2032, growing at 23.3% annually.

What's driving this? Three things:

1. Process debt is killing us. Most teams are running on pre-AI workflows trying to bolt on AI features. It's like adding a jet engine to a horse cart.
2. The trust paradox.24% of developers trust AI "a great deal", but 30% trust it "a little" or "not at all." We're using tools we don't fully trust—no wonder productivity gains are inconsistent.
3. Measurement matters more than features. Organizations that define clear KPIs before implementing AI are seeing real returns. The rest are just accumulating technical debt.

What Actually Works in 2025

After reviewing dozens of case studies, here's what separates the winners from the pilot-purgatory crowd:

Start with workflow mapping, not AI tools. Toyota's production system didn't succeed because of technology—it worked because they obsessively eliminated waste first. Digital workflows can reduce operating costs by up to 30% when you know what you're optimizing for.

Think in outcomes, not features. Companies like L'Oréal are using AI to analyze millions of conversations to detect emerging trends before competitors can react. They're not building AI features—they're solving specific business problems.

Embrace the 80/20 rule for automation.Hyperautomation is a priority for 90% of large enterprises, but the smart ones aren't automating everything. They're identifying the 20% of workflows that create 80% of the friction.

A Contrarian Thought

Here's what nobody's saying: Maybe we don't need more AI in our workflows. Maybe we need better workflows that happen to use some AI.

The companies reducing time-to-market by 50% aren't just throwing AI at problems. They're rethinking their entire product development process—from ideation to launch. AI has accelerated time to market by just 5% across six-month cycles, but product manager productivity is up 40%. The AI isn't doing the work—it's removing friction so humans can do better work.

What to Focus On This Quarter

If you're planning your 2025 priorities, consider this:

• Audit your process debt. What workflows were designed before AI? Which ones are actually holding you back?
• Pick one bottleneck. Not three. Not five. One critical workflow that's costing you time or money.
• Test with real metrics. Not vanity metrics. If you can't measure cycle time, error rates, or customer satisfaction scores before and after, don't start.

The future of product workflows isn't about having the most sophisticated AI stack. It's about having the clearest understanding of where your team loses time, energy, and focus—and being ruthlessly practical about fixing it.