How prepared are companies in Procurement & Supply Chain functions?
By asking a simple question, I try to build visibility on how far we have gone in preparing for the technological advancements driven by AI.
I ask Procurement & Supply Chain professionals in Stockholm the following question:
On the scale from 1 to 10 (where 1 is low and 10 is high), how do you assess AI readiness of your current or recent company?
Have a look at the results below.
AI Readiness Score
March-December 2025
Methodology
A Monthly Snapshot of Organizational Preparedness
“On a scale from 1 to 10 (where 1 is low and 10 is high), how do you assess the AI readiness of your current or recent company?”
How the AI Readiness Score Is Collected
Population: The survey targets mid- to senior-level professionals in Procurement and Supply Chain roles, primarily based in Stockholm.
Sampling: Participants are selected from ongoing candidate and client conversations within Talent Supply’s active network. Participation is voluntary and anonymous.
Confidentiality: Each response is treated with strict confidentiality. No individual responses or affiliations are disclosed.
Response Type: Numeric self-assessment (1–10 scale), capturing the respondent’s perception of organizational AI preparedness.
Data Collection: Responses are collected via direct outreach via calls and during structured screening interviews and via forms accessible by the link shared after the phone calls.
Frequency: Results are aggregated and published monthly, quarterly, and on an annual basis to identify directional shifts, trends, and patterns across the industry.
Limitations: The data reflects subjective perspectives and is not intended as a formal maturity assessment of systems or strategy.
How the AI Readiness Score is Calculated
To report monthly/quarterly/annual results, the median score is applied instead of the average. This approach is considered more appropriate for the following reasons:
Resilience to outliers: The average can be significantly affected by unusually high or low responses. By contrast, the median is determined by identifying the midpoint of the distribution, ensuring a more balanced representation.
Perceptions are more accurately reflected: Given that the data is collected through subjective, self-reported scores on a 1–10 scale, the median is regarded as a more reliable indicator of perceived organizational AI readiness.
Stability across smaller sample sizes: In months when fewer responses are submitted, the median is viewed as a more consistent and dependable measure of overall sentiment.
By relying on the median, a more typical experience is represented each month, while extreme views are prevented from distorting the overall insight.
This pulse survey is used as a recurring indicator of how AI integration is being perceived within organizations allowing gaps between ambition and execution in digital transformation to be surfaced over time.
