Last Mile (artificial intelligence)

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The last mile in the context of artificial intelligence (AI) and large language models (LLM) is a metaphor drawing on last mile (telecommunications) to refers to the limit or "gap" of what an AI model "knows" and human knowledge. Attending to the last mile gap is a strategy also to address algorithmic bias.

The last mile concept was used prior to the public rollout of ChatGPT in 2022 [1] [2] and gained traction in 2024 from multiple sources simultaneously. [3] [4] and amplified by Forbes Magazine. [5] The "last mile" concept in AI entered common use in 2025 to refer to algorithm gaps [6] AI design gaps [7] and other gaps. [8]

References

  1. Coiera, Enrico. "The Last Mile: Where Artificial Intelligence Meets Reality". Journal of Medical Internet Research. National Library of Medicine (2019). Retrieved 10 November 2025.
  2. Ricadela, Aaron. "To make AI results more relevant, businesses turn to "last-mile" training". Oracle. Oracle (2023). Retrieved 10 November 2025.
  3. Fleming, Li, Thompson. "The last mile problem in AI". Brookings. Brookings. Retrieved 10 November 2025.{{cite web}}: CS1 maint: multiple names: authors list (link)
  4. Robbins, Hollis. "AI and the Last Mile". Anecdotal Value. Substack. Retrieved 10 November 2025.
  5. High, Peter. "Must Read Tech Articles of 2024". Forbes. Retrieved 10 November 2025.
  6. Peter, Hirst. "Beyond the Algorithm: Bridging the Last Mile of AI Adoption". MIT Management. MIT. Retrieved 10 November 2025.
  7. Raghavan, Vaidy. "AI's Last Mile: Why Manufacturing Is Its Hardest Test". Design News. Design News. Retrieved 10 November 2025.
  8. Leone, Andrew. "Delivering Intelligence: How AI is Redefining the Last Mile". The AI Journal. The AI Journal. Retrieved 10 November 2025.

Sources