Tag: generative AI
AI in the public sector: the projects that actually worked in 2025
From Brazil to the UAE, through Taiwan and the UK: real-world government AI cases recognized in 2025 show what separates projects that deliver results from those that remain on paper.
Public sector contact centers and AI: what works, what doesn’t
Governments have been experimenting with generative AI in contact centers for two years. Results show where it's worth investing and where risks outweigh expected benefits.
Synthetic data is changing how AI gets trained
Synthetic data is artificially generated data used to train AI models, preserve privacy, and test systems. How it works, where it's used, and why adoption is growing in regulated sectors like healthcare and finance.
Companies fight back against low-quality AI content
By 2030, 80% of companies will adopt an antislop manifesto to combat the overload of poor AI content. What it is, how it works, and why it's becoming a matter of reputation and compliance.
When AI gets trapped inside individual applications
By 2027, 80% of companies will have AI siloed by application, limiting intelligence sharing across departments. What siloed AI is, why it forms, and how to break free.
RAG reduces AI model hallucinations
Retrieval-augmented generation anchors LLMs to verified sources, reduces hallucinations, and enables AI to respond with real, up-to-date data. How it works and why it has become the standard for enterprise AI applications.
Four GenAI skills every worker must master
Gartner has identified the four generative AI skills workers need to develop in 2025: recognizing use cases, understanding the technology, writing effective prompts, and evaluating results. A practical guide for CIOs and HR leaders.
How to write prompts that produce useful results
Prompt engineering is the skill that separates those who get real results from AI from those who get generic outputs. How the Gartner ReFLECT framework works and why prompt quality changes everything.
