arXiv:2608. 12236v1 Announce Type: cross Abstract: We study how organizations use frontier generative AI by linking ChatGPT Enterprise account records to usage, worker roles, task classifications, and public-company financial data through March 2026.
By Aaron Chatterji, David Holtz, Neel Rakholia, Prasanna Tambe, Gawesha Weeratunga
arXiv:2308. 05201v4 Announce Type: replace Abstract: Large Language Model (LLM)-based generative AI systems are general-purpose tools capable of augmenting or even automating a wide range of job functions, positioning them to reshape labor market dynamics.
By Jin Liu, Xingchen Xu, Xi Nan, Yongjun Li, Yong Tan
arXiv:2604. 01363v2 Announce Type: replace Abstract: We propose that AI automation is a continuum between: (i) crashing waves where AI capabilities surge abruptly over small sets of tasks, and (ii) rising tides where the increase in AI capabilities is more continuous and broad-based.
By Matthias Mertens, Adam Kuzee, Brittany S. Harris, Harry Lyu, Wensu Li, Jonathan Rosenfeld, Meiri Anto, Martin Fleming, Neil Thompson
arXiv:2606. 07489v1 Announce Type: new Abstract: Frontier AI systems are bridging the gap between intelligence and utility by shifting from conversational assistants to autonomous agents that execute tasks end to end.
By Jeremy Yang, Kate Zyskowski, Noah Yonack, Jerry Ma
arXiv:2607. 28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI into system administration may involve deeper shifts in professional practice that are not yet fully understood.
By Rana Abou Khamis, Hala Assal, Ashraf Matrawy
arXiv:2605. 16283v3 Announce Type: replace-cross Abstract: Large-scale AI deployment data and controlled learning experiments characterize different consequences of the same technology.
By Aysa Xuemo Fan