We are designing a new seat for AI-powered operations, but our Predictive Index data shows that the current manager we want to place there lacks the cognitive pace required for rapid tech shifts. Do we ignore the data or find someone else?

Question

Tyler Smith · Accepted Answer

Ignoring psychometric data is a classic way to pay what Keith Cunningham calls a "dumb tax." If your Predictive Index behavioral and cognitive targets show a significant mismatch for a highly complex, fast-changing seat, you are setting that manager up to fail.

The Cognitive Demands of AI Operations

An AI Operations seat requires a high cognitive ability for several critical reasons:

• Rapid technological evolution: The technology, tools, and processes in AI are evolving weekly, demanding continuous learning and adaptation.
• Complex data processing: The seat owner must quickly process and synthesize intricate data sets.
• Fast system learning: They need to rapidly learn and integrate new AI systems and platforms.
• Strategic pivoting: The ability to make quick, informed strategic pivots based on new information and changing landscapes is essential.

If your current manager has a lower cognitive score than the seat target, they will likely suffer from intense conative stress. They will struggle to keep pace, leading to operational bottlenecks and potential burnout. For more on this, see [How do we check if a promoted employee has conative stress?](/qa/promoted-employee-burnout-conative-stress).

Prioritizing Structure Over People

You must always put the structure first. The business requires a specific cognitive profile for the AI Operations seat to succeed. Ignoring this data means prioritizing an individual over the needs of the business, which can undermine overall performance and growth. This aligns with the principle of [putting structure before people](/qa/putting-structure-before-people-accountability-chart).

Recommended Action Plan

Instead of forcing the wrong person into a seat where they are unlikely to thrive, consider the following:

1. Reallocate the current manager: Look for a different seat within the organization where their behavioral and cognitive strengths are an asset. They might be highly effective in roles like client success or account management, where deep relationship building and steady execution are valued more than rapid technological adaptation.
2. Targeted search for the AI Operations seat:
• Run a new search specifically for the AI Operations seat.
• Use your defined behavioral and cognitive targets from the Predictive Index as critical filters for candidates.
• When evaluating candidates, ensure they not only "get it" and "want it," but also have the "capacity" for the rapid pace and complexity of AI operations. This often involves assessing their technical expertise for [highly technical seats](/qa/gwc-technical-ai-seat-non-technical-owner).

Your people decisions must be driven by data and objectivity, not by wishful thinking or a desire to avoid a difficult conversation. This strategic approach ensures that you align individuals with roles where they can genuinely succeed, benefiting both the employee and the organization. For more insights on defining such roles, refer to [Should we create a dedicated AI Operations seat on our Accountability Chart, or integrate AI into existing seats?](/qa/ai-operations-seat-accountability-chart).

Related questions

• [One of our top performers was promoted to a managerial seat but is now burning out. How do we check if they have conative stress?](/qa/promoted-employee-burnout-conative-stress)
• [Should we create a dedicated AI Operations seat on our Accountability Chart, or integrate AI into existing seats?](/qa/ai-operations-seat-accountability-chart)
• [My co-founder insists on creating custom seats on our Accountability Chart based on the unique skill sets of our long-term employees, which makes our org structure messy and confusing. How do I convince them to focus on structure before people?](/qa/structure-before-people-accountability-chart)
• [We are adding an AI and Operations Automation seat to our Accountability Chart, but as the owner, I do not understand AI well enough to evaluate if the candidate truly gets it, wants it, and has the capacity to do it. How do we make an accurate GWC call on a highly technical seat when we lack the technical expertise ourselves?](/qa/gwc-technical-ai-seat-non-technical-owner)
• [We have an employee who scores one hundred percent on our core values but fails the GWC for their current operations seat, and we have no other open seats on our Accountability Chart. Do we have to let them go?](/qa/right-person-wrong-seat-no-openings)