Adapting to AI: Why Your Talent and Location Models Need a Refresh

I conducted a small workshop with SWP professionals and Talent Intelligence Professionals. The discussions yielded some interesting findings.  

• Understanding the impact of AI on jobs is very critical.
• We need post-AI location models as our models are a bit outdated.  The magnitude of savings in Globalization or setting up centers in lower-cost locations Post-AI impact on jobs may be less compared to Pre-AI models 
• Automation-Driven Deskilling: Routine tasks vanish, lowering wages
• Experience Level Shift:  Early Career may be able to do more with AI as a result 
• Infrastructure Dependency- More AI would mean more investments in Tech Infrastructure
• Skillset Shift: Demand pivots from traditional skills to AI-driven skills, data analysis, and system oversight, a skill that may not be available across all locations  

With AI, skill building in existing locations becomes crucial.  Or the locations you chose should be Resilient in handling skill changes.  To demonstrate this, we developed a simple model.. This is a very approximate model but one that will trigger your thinking (hopefully).  

Modeling Approach: 

The model is organized into three scenarios to assess cost impacts:

• Scenario 1: Current State (pre-AI, 5 years’ experience).  We chose the Supply Chain Function as an example
• Scenario 2: Impact of AI Adoption (30% headcount reduction, same experience).
• Scenario 3: Impact of AI + Reduced Experience (30% headcount reduction, experience drops to 3 years). Each scenario calculates costs, savings vs. NYC, and percentage savings for the five locations.

Modeling Assumptions 

Worksheet

Here is the detailed Worksheet that shows the three scenarios 

Impact Graph

Across scenarios, you can see the magnitude of savings shift downwards 

Model Interpretation 

AI Reduces Costs Universally: AI-driven headcount reduction and lower experience requirements significantly cut costs across all locations.

Low-Cost Locations Savings Persist but Shrink: Low-cost locations have high percentage savings, but absolute savings decrease.