LUDA Research Group

Why AI Confidently Says the Wrong Thing

If you've spent any time with ChatGPT or an AI assistant, you've probably had an uncomfortable moment where the AI stated something completely made up — as if it were established fact. Experts call this the 'Hallucination' phenomenon.

So why does it happen? AI models are trained on massive amounts of data, and they generate responses based on what they've learned — a bit like a student who crammed hard for an exam. The problem is, they have no idea what happened after their training ended, and they know nothing about private internal documents within a company. Ask an AI about yesterday's news, and it has little choice but to fabricate a plausible-sounding answer.

In a business setting, this is more than just an annoyance — it can be genuinely damaging. When an AI is expected to accurately answer questions about the latest product specs, internal policies, or real-time customer data, getting a response based on two-year-old training data can quickly erode trust.

What Is RAG? Giving AI the Ability to Search in Real Time

RAG (Retrieval-Augmented Generation) was developed specifically to solve this problem. The name might sound intimidating, but the core idea is surprisingly straightforward.

A standard AI answers purely from what it has already learned. RAG, on the other hand, searches for relevant information before it responds. Think of it like an open-book exam — instead of relying solely on memory, you get to look things up first.

The process works in two key steps:

Retrieval: When a question comes in, the AI first searches through internal company documents, databases, and up-to-date sources to find relevant information.
Generation: Using what it found, the AI then crafts an accurate, context-aware response.

For example, if an employee asks, "What's our company's parental leave policy?" a RAG system will pull up the actual internal policy documents and answer based on those — not some generic information it learned during training. The difference in reliability is significant.

How RAG Is Changing Things for Companies in Korea and New Zealand

🇰🇷 In Korea, businesses across a range of industries have been quick to embrace RAG.

KB Kookmin Card integrated RAG into its LLM-powered chatbot to provide customers with accurate, up-to-date information on card benefits and promotions. A legal tech startup launched an AI chatbot trained via RAG on 4,360 pages of court rulings and legal guidelines from the past five years, dramatically improving efficiency for legal professionals. A major retail conglomerate reported cutting customer service response times by 40% within just six months of deploying a RAG-based AI assistant.

🇳🇿 In New Zealand, adoption is accelerating — particularly in the financial and public sectors. ASB Bank runs an AI virtual assistant that handles everything from account inquiries and transfers to loan guidance, boosting customer satisfaction by 30% while reducing support costs by 20%. Across New Zealand and Australia, there's growing momentum around 'data-sovereign RAG' — an approach that keeps sensitive data in-house while still benefiting from AI accuracy, especially in government and financial services.

The Global Outlook for RAG

The global RAG market is estimated at around $1.94 billion USD in 2025, with projections pointing to $9.86 billion USD by 2030 — an annual growth rate of 38.4%.

The performance numbers speak for themselves:

AI hallucinations reduced by 70–90%
Information retrieval time cut by 45–65%
Manual task costs reduced by 20–50%

In Korea, surveys show that companies using AI generate 7.8% more added value and 4% higher revenue than those that don't — a clear signal that the business impact of AI adoption is very real.

Key Takeaways

RAG gives AI real-time search capabilities, allowing it to pull from current sources before responding — drastically reducing errors.
It cuts AI hallucinations by 70–90%, enabling trustworthy answers grounded in internal documents and up-to-date information.
In Korea, companies like KB Kookmin Card and legal AI startups are using RAG to improve customer service and operational efficiency.
In New Zealand, the financial and government sectors are leading the charge with 'data-sovereign RAG' — leveraging AI power without compromising data security.
The global RAG market is expected to grow more than fivefold by 2030.

Wrapping Up