AI could contribute up to $15.7 trillion to global GDP by 2030, according to recent McKinsey estimates. This represents a significant increase from the $2 trillion it contributed to global GDP in 2023. The potential impact of AI on the global economy is vast, and it is expected to transform multiple industries, including healthcare, automotive, and financial services.
The initial costs associated with AI adoption include license costs, infrastructure costs, and implementation costs1. These are day-zero expenses to even get started. These implementation costs range from relatively inexpensive with low usage via API cloud services or local implementations on servers for open-source large language models (LLMs) to escalating quickly with scale (pay for usage) and system resources to make sure the LLM can serve enterprise-grade needs.
AI impacts human decision-making abilities by providing accurate predictions and insights, reducing cognitive biases, and improving overall decision quality. It enables humans to analyze vast amounts of data, identify patterns, and make informed choices. However, over-reliance on AI can also lead to cognitive laziness and diminished critical thinking skills. Striking a balance between human intuition and AI-driven analysis is crucial for optimal decision-making.