In a recent LinkedIn post, Melissajeanperri discusses a critical disconnect she observes in how businesses implement Artificial Intelligence (AI) strategies. Melissajeanperri argues that the perceived failure of AI strategies often stems not from a lack of a plan, but from a failure to translate high-level executive vision into actionable guidance for product teams.
Melissajeanperri highlights a significant gap revealed in a survey conducted with product leaders. “In the survey we ran with product leaders coming out this week, one of the biggest gaps had nothing to do with tools or budgets. It was about who can actually see the strategy,” she writes. This observation is underscored by the data: 61.9% of product managers identified “no clear AI strategy” as a top challenge, while only 19% of C-level leaders shared this concern. This disparity, Melissajeanperri points out, is the largest observed across all analyzed categories, including industry, geography, and company size.
The ‘Untranslated’ Strategy
Melissajeanperri contends that both executives and the teams on the ground are, in a sense, correct. Executives believe a strategy exists, while the product managers executing the work feel it has not reached them. The core issue, according to Melissajeanperri, is that the strategy is established at the investment level but is not effectively translated into the operational rules and daily practices that teams follow.
“Sit with what that means. Executives believe a strategy exists. The people doing the work say it never reached them. Both are right,” Melissajeanperri states, emphasizing the disconnect. She posits that the true challenge lies not in devising a new vision, but in the unglamorous but essential work of translation.
Defining the ‘Real Work’ of AI Translation
Melissajeanperri elaborates on what this translation entails, moving beyond mere vision decks. She defines it as the “unglamorous specifics: what AI is used for and what it is deliberately not used for, who reviews the output, which decisions change, how you define a good outcome now, what happens to priorities when delivery suddenly gets faster.” This granular detail is what enables teams to operationalize a strategy effectively.
“That translation is the real work. Not another vision deck.”
She observes that leaders sometimes respond to this gap by attempting to create an entirely new strategy. However, Melissajeanperri suggests a more effective approach: closing the gap by diligently translating the existing strategy into practical guidance that teams can implement immediately.
Building the ‘Translation Muscle’
Melissajeanperri connects this concept to the development of organizational capabilities, mentioning her work with the CPO Accelerator. She shares a testimonial from an alum who found the program instrumental: “gave me the tools I needed to scale our product organization and align strategy across teams.” This highlights the practical, hands-on nature of building the skills needed for effective strategy translation.
A Simple Diagnostic Test
To gauge the effectiveness of their AI strategy communication, Melissajeanperri proposes a straightforward diagnostic. She advises leaders to ask their product managers to describe the AI strategy back to them. “If you set your AI strategy six months ago, ask your PMs to describe it back to you. What you hear is your actual starting point,” she concludes. This simple exercise, in Melissajeanperri’s view, provides an honest assessment of where the strategy truly stands within the organization.
📝 About This Content
This article is based on insights shared by Melissajeanperri on LinkedIn.
📅 Originally posted on June 9, 2026 | View original post on LinkedIn →