Explore KSACs by Pathway
In late 2025, the Partnership pulled together members of industry from across tech to share how the in-demand skillsets for entry-level roles in their fields have changed in the last two years. The Knowledge, Skills & Abilities and Credentials (KSACs) below reflect their feedback on entry-level expectations, especially in a tech workplace increasingly shaped by AI.
The below KSAs are cross-cutting skills identified as in-demand across tech specializations. In addition to core technical skills like basic data literacy and fluency in the fundamentals of generative AI, professional skills like communication, problem solving, and project management have been added given the increasing importance of these skillsets as technology rapidly evolves.
5. AI & Data Literacy (Foundational)
| Label | KSAC Description | Bloom's Taxonomy Level | |
|---|---|---|---|
| a | Define what data represent and describe how data are used to inform decisions and reduce uncertainty. | knowledge | 1 |
| b | Explain the difference between structured and unstructured data and why that distinction matters for analysis and AI systems. | knowledge | 2 |
| c | Explain foundational AI concepts, including probabilistic outputs, common failure modes, and appropriate use cases. | knowledge | 2 |
| d | Use basic data tools (e.g. spreadsheets or equivalent platforms) to organize, summarize, and explore information. | skill | 3 |
| e | Evaluate AI-generated outputs for accuracy, relevance, bias, and appropriateness before use. | skill | 5 |
| f | Apply AI tools as productivity aids while maintaining human accountability for final decisions and deliverables. | skill | 3 |