Tag: generative AI
The AI competence center: is it really needed or just a bureaucratic layer?
Only 1 in 5 organizations is getting value from AI tools, and only 1 in 50 is seeing transformative value. Gartner recommends building an AI center of excellence that works like an air traffic controller. But building it wrong is worse than not building it at all.
Data, agents, and risks: security in BPA systems with generative AI
By 2027, over 40% of AI-related data breaches will be caused by improper use of GenAI across geographic boundaries. 57% of employees use personal GenAI accounts for work. Global cybersecurity spending will reach $240 billion in 2026. The problem is already inside organizations.
Agentic AI: what it really means and why most projects fail
Gartner predicts that over 40% of agentic AI projects will be canceled by 2027. 19% of organizations have already made significant investments, 42% conservative investments. The term is widely misused, projects are launched without clarity, and real costs surface too late.
Business Documents Are Not a Storage Problem
The Intelligent Document Processing market is worth $2.09 billion by 2026. Gartner counts over 100 vendors. The problem for companies is not finding a tool to archive documents: it is extracting useful data and feeding automated workflows reliably.
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.
