Human Judgment vs. AI Insight: Rethinking Strategy in an Automated World

Visionaries have given us products that disrupted markets, but they have always had a strategy to back up the vision. Steve Jobs gave us a cellular phone (the iPhone) with a touchscreen keyboard because he hated mechanical keyboards. It also played music like Apple’s popular iPod and offered a world of apps you could download from Apple itself.

When Herb Kelleher took Southwest Airlines nationwide, he had a vision for making air travel affordable for all: he would model it after Greyhound bus lines. For better or worse, that led Southwest to implement its less expensive point-to-point flight patterns, distinct from the other airlines’ hub-and-spoke patterns.

The vision drove the strategy, and, no doubt, many project managers and communications professionals made it work.

In recent months, I have heard a subtle but important shift in how professionals talk about strategy. Increasingly, teams are not just using AI to support execution; they are asking it to suggest direction. Prompts such as “What should our strategy be?” or “What is the best approach?” crop up more and more in both project environments and content strategy discussions.

This shift raises an important question: Are we improving strategic thinking, or are we outsourcing it?

This post explores the following:

  • What Strategy Really Is
  • Features of Experience-Based Strategy
  • Features of AI-Influenced Strategy
  • Comparison of the Two Approaches
  • The Blended Approach—And Its Risks
  • Caveat: HITL Is Not a Panacea
  • Conditions for Effective Blending
  • Structuring Strategy in an AI Environment: A Model
  • Practical Applications
  • Strategy Still Requires Human Ownership
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GenAI in Professional Settings: Adoption Trends and Use Cases

Some content and project professionals are making their GenAI wishes come true, some are still contemplating their first wish, and some feel trapped in the genie’s bottle. Such is the current state of GenAI use within organizational boundaries.

In the past few weeks, I have been engaging with practitioners through events and private discussions on the application of GenAI to everyday work. Most notably, I recently delivered a recorded presentation on Human-in-the-Loop for IPM Day 2025, set for release on November 6; led a virtual session for the PMI Chapter of Baton Rouge on September 17, 2025, titled “GenAI: The Attractive Nuisance in Your Project”; and participated in an October 2 webcast, “An Imperfect Dance: Responsible GenAI Use.”

What folks told me didn’t always surprise me.

What they told me matched, for the most part, some of the GenAI adoption patterns I’ve been researching. I’ll share those trends, as well as common and emerging use cases and persistent drawbacks, in this month’s blog post.

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Sprint but Iterate: How Product Content Pros Can Adopt/Adapt Agility (Part 2)

Sad as it is to say, self-directed, collaborative, and agile product development teams often don’t get content. That is, they don’t really understand where content comes from, how it is best developed, how to work with content creators, what’s required of the team as a whole, and why developing content can sometimes take longer than a 2-week sprint.

So it is often up to content professionals to educate (constantly), adapt (when necessary) and, above all, speak up about their requirements.

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Sprint but Iterate: How Product Content Pros Can Adopt/Adapt Agility (Part 1)

As product teams have adopted Agile development methodologies, product content professionals often find themselves stuck between agility and review cycles.

How can quality product content be developed in two-week sprints? Where do content strategy, content operations, and content standards fit into the constant evolution of software products? Where do the various disciplines within the content continuum fit in? (For example, UI, Help, API, and Services content?)  How can everyone work together to deliver product content that is consistent, useful, accessible – and agile?

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