limitedDistribution · Industry Research
Agentic AI vs. Generative AI: The Evolution of Decision-making | Publicis Sapient
Agentic AI offers power but complexity, while generative AI's ease of deployment ensures faster market adoption and diverse applications.
Stargo's Stardox leverages agentic AI to transform unstructured supply chain data, balancing power and complexity for optimal decision-making.
Executive Summary
Agentic AI offers greater potential power but brings complexity and integration challenges, slowing value creation and scalability. Generative AI’s lower deployment barriers make it more immediately valuable, ensuring faster adoption in the global market. Generative AI models, based on deep learning architectures, generate outputs that align with the statistical properties of their training data. These models have applications across various domains, from art and entertainment to healthcare and finance. Automated content generation is a prominent application, with tools like OpenAI's GPT-4o enabling human-like text generation.
Source: PublicisSapient
Authors: PublicisSapient
Original Article: https://www.publicissapient.com/insights/agentic-ai-vs-generative-ai
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