Melissajeanperri Highlights AI’s Current Impact Across the Product Lifecycle

In a recent LinkedIn post, Melissajeanperri discusses the current, tangible impact of Artificial Intelligence (AI) within the product lifecycle, urging followers to consider where the technology is genuinely moving work, rather than where it is wished to be.

Melissajeanperri framed the inquiry by posing a direct question to their network: “Where in your product lifecycle is AI actually having the most impact right now?” This question sets the stage for a deeper exploration into the practical applications of AI, moving beyond theoretical potential to observable results.

“Not where you wish it was. Where it is actually moving the work.”

The post signals that Melissajeanperri is drawing on data from a new “State of AI in Product 2026 survey.” According to Melissajeanperri, the emerging shape of the answer from this survey was unexpected, prompting a desire to gather broader community input before revealing the specific findings. This approach highlights a commitment to both data-driven insights and community engagement.

The Unforeseen Impact of AI

Melissajeanperri’s focus on the *actual* impact of AI, as opposed to aspirational goals, suggests a critical evaluation of current AI adoption. This distinction is crucial for businesses seeking to understand the real return on investment and operational shifts driven by AI technologies. By asking participants to identify the stage where AI is “most true for your team today,” Melissajeanperri aims to pinpoint the areas experiencing the most significant, immediate change.

As Melissajeanperri explains the rationale behind the survey question:

“Before I share the numbers (by next Monday), I want to hear yours.”

This direct call to action encourages a collective reflection on AI’s role. Melissajeanperri intends to share the survey results, promising to “drop the survey result in the comments in a couple of days,” further fostering transparency and dialogue around the findings.

Gathering Community Insights on AI Adoption

The strategy employed by Melissajeanperri involves a two-pronged approach: leveraging new survey data while simultaneously engaging the professional community for their real-time perspectives. This method allows for a nuanced understanding of AI’s current standing in product development workflows.

Melissajeanperri’s emphasis on practical application is further underscored by the instruction:

“If two are close, pick the bigger one.”

This directive ensures that the data collected reflects the most dominant area of AI influence for each respondent, aiming for clarity and actionable insights. The anticipation of the survey results, coupled with the ongoing community discussion, positions Melissajeanperri as a keen observer and facilitator of conversations around AI’s evolving role in the product landscape.