AI is widening the product strategy/delivery divide

In new research from Modus Create, 550 product and technology leaders share how AI is reshaping product development as it moves from experimentation to deeper integration. One theme stands out: AI is widening the product strategy/delivery divide. Read the full report here.

“If only we could ship faster.”

For years, product teams believed speed was the missing ingredient. It was the center of agile philosophies built around faster releases, shorter cycles, and continuous delivery. Then AI came along.

Generative AI has dramatically accelerated the pace of shipping new features. Product teams are now prototyping UIs in hours instead of weeks, refactoring legacy code overnight, and pushing features that once took quarters in days or even same-day cycles. 78% of organizations delivered more than three major product releases in 12 months. 33% delivered more than six.

But this very acceleration has cracked open one of product development’s oldest fault lines: the gap between product strategy and delivery.

Speed doesn’t fix weak foundations

When product teams use AI, they run faster, but not always in the same direction. 75% of product leaders say executing product strategy is a major barrier to success for their organization.

More leaders report difficulty creating efficient processes, scaling technology strategically, and aligning departments around shared goals. In other words, as delivery speed increases, coordination challenges are not shrinking; they’re intensifying.

“Vibe coding is like one big party. You move fast, everyone’s buzzing, and something flashy gets built overnight. But when the lights come on, there are half-empty cups, a broken chandelier, and the cleanup sucks.” — Kevin McClelland, Chief Growth Officer, Modus Create

Almost at the same time that cracks in the foundations are showing, the pressure to show measurable ROI from AI initiatives has intensified. 91% of executives say the pressure to prove AI ROI has increased. Leadership is now asking a sharper question: if AI is helping teams ship faster, where exactly is the business impact?

This puts teams in a bind. Leaders are under pressure to prove ROI, while the same AI speed is exposing weaknesses in strategy execution, prioritization, and ownership. In many cases, teams are being pushed to show financial outcomes before the basics are in place (clear priorities, aligned roadmaps, and disciplined measurement).

Execs feel misalignment first

Though misalignment exists at all levels of an organization, it’s not felt equally. The higher you sit in the management chain, the more evident this gap becomes. 42% of executives strongly agree that following through on product strategy is a major barrier to success, compared with 31% of VPs/directors and 21% of managers.

Executives see how misalignment snowballs across budgets and teams. In large enterprises, even small disconnects between strategy and execution multiply, creating delivery issues that no amount of engineering speed can solve.

“Teams have figured out how to move fast. But they need to understand how that speed connects to business value. Boards and investors aren’t asking how many releases you did this quarter, they’re asking what it delivered.” — Sharon Lynch, Chief Executive Officer, Modus Create

Execution challenges do not look the same across industries. In healthcare, the bottleneck is structural. Critical data lives across disconnected EHR systems, labs, imaging platforms, billing workflows, and care-delivery tools that rarely integrate cleanly. These isolated data streams result in redundant manual work, delayed automation, and execution slowdowns that have little to do with team capability and everything to do with fragmented infrastructure.

Manufacturing organizations, by contrast, often operate with a far tighter strategy-to-execution loop. Clear constraints, disciplined workflows, and predictable operating environments allow them to turn strategy into results faster and more consistently.

In many cases, so-called “traditional” industries execute AI initiatives more effectively than digital-native companies because their internal system is stronger.

Product teams succeeding with AI were already succeeding before it

Teams that are getting real results from AI already had the basics in place: sharp priorities, fast decisions, modern infrastructure, and real ownership. That’s what turns AI speed into business results.

Conversely, teams lacking those fundamentals often experience a different outcome. AI increases release velocity, but the absence of alignment means more initiatives compete for attention, and success becomes harder to measure.

AI will continue to evolve. Tools will change, and practices that feel advanced today will eventually become outdated. The core work of product development will not. Understanding customers, making disciplined trade-offs, choosing architectures that endure, and protecting trust remain the foundation. The organizations that win in this era will be those that use AI to strengthen these fundamentals, not replace them.

This blog features findings from our latest report, AI in product development: A reality check, a comprehensive study of how 550 product and technology leaders are actually deploying AI in their organizations. Access the full report here.