Twelve months ago, most people had never used an AI system outside of a chatbot or a Spotify recommendation. By December 2023, your organisation probably had an AI policy, your IDE had an AI plugin, and you had used at least one LLM for real work.
The ChatGPT effect
ChatGPT crossed 100 million users faster than any consumer application in history. That single fact restructured the technology industry's priorities more than any product launch since the iPhone. Every major software company reallocated resources to AI in 2023. Products that had no AI roadmap in January had AI roadmaps in June.
The enterprise adoption pattern
Enterprise AI adoption in 2023 followed a recognisable pattern: leadership mandates exploration, engineering evaluates tools, procurement negotiates contracts, and security and legal review policies. Most large organisations are in one of the middle stages. The companies that finished all of them are seeing measurable productivity gains in developer tooling, content operations, and customer service automation.
The model capability leap
GPT-4 in March, Claude 2 in July, Llama 2 in July, Claude 2.1 in November, Gemini in December. The model capability curve in 2023 was steeper than any previous year. The practical implication is that applications built on GPT-3.5 at the start of the year are already running on a generation-old model. Model selection is now a recurring engineering decision, not a one-time choice.
What 2024 will test
The 2023 narrative was about capability. The 2024 narrative will be about reliability, cost, and integration depth. Applications that handle hallucinations gracefully, that know when to call a model and when to use a rule, and that have observability into model behaviour will outlast the applications that were built quickly on top of raw API calls.