We discovered something surprising during our AI chatbot implementation…
When we introduced Gus, our AI-powered Marketing Guide, onto the 3G’s and MHO website, one of our objectives was to learn as much as possible before recommending similar solutions to our clients.
As with any new technology implementation, we expected to make a few discoveries along the way.
One of the most valuable lessons came from something that, at first glance, appeared to be a problem.
Gus didn’t know what MHO was.
That was surprising.
After all, MHO (Marketing Head Outsource) is one of our core service offerings.
It’s discussed throughout our website, appears in our marketing material and forms an important part of our business offering.
So why didn’t Gus recognise it?
The answer taught us something incredibly valuable about how modern AI assistants interpret information.
AI Doesn’t See Your Business Through Your Eyes
One of the biggest misconceptions about AI chatbots is that you simply upload a collection of documents and the AI magically understands everything exactly as you intended.
The reality is rather different.
Modern AI is exceptionally intelligent at recognising patterns, context and relationships.
But it can also make logical assumptions that are completely different from the assumptions we make as humans.
In our case, MHO has its own visual identity and logo.
From our perspective, that’s simply part of the 3G’s ecosystem.
From Gus’s perspective…
MHO looked like a completely separate company.
Because Gus had been instructed to focus specifically on 3G’s, he intentionally ignored information he believed related to another organisation.
He wasn’t malfunctioning.
He was following his instructions perfectly.
The problem wasn’t the AI.
The problem was our assumption that the AI interpreted our business structure the same way we did.
The Lesson Wasn’t About Technology
It Was About Knowledge.
This experience reminded us that implementing an AI assistant isn’t really a technology project.
It’s a knowledge project.
AI doesn’t simply read documents.
It builds relationships between pieces of information.
It creates context.
It identifies entities.
It classifies concepts.
If those relationships aren’t clear—or if they’re open to interpretation—the AI will make its own logical conclusion.
Sometimes that conclusion is exactly right.
Sometimes it’s not.
Every Business Has Its Own Language
As we reflected on our experience, we realised that almost every organisation has its own vocabulary.
Think about your own business.
You probably use:
- Product codes
- Internal abbreviations
- Acronyms
- Service names
- Department names
- Industry terminology
- Brand names
- Internal project names
- Nicknames for products or services
Your staff understand them instinctively.
Your customers often understand them after dealing with you for a while.
But an AI assistant encounters them for the very first time.
Without additional context, it has to determine:
- Is this a product?
- A service?
- A company?
- A department?
- A partner?
- A person?
- A location?
- An abbreviation?
Getting these relationships right makes all the difference.
AI Training Is About Context, Not Content
This was perhaps our biggest takeaway.
Many organisations already possess the information an AI assistant needs.
The challenge isn’t creating more content.
It’s providing better context.
For example, rather than simply uploading documentation that mentions “MHO,” we needed to explicitly tell the AI:
MHO stands for Marketing Head Outsource.
MHO is a strategic service offered by 3G’s.
MHO is not a separate company.
Questions about MHO should be answered as questions about 3G’s services.
That small amount of contextual information completely changes how the AI interprets every future conversation.
This Applies Far Beyond Marketing
The same principle applies in almost every industry.
A manufacturer may have hundreds of product codes.
An engineering firm may use technical abbreviations.
An accounting practice may refer to specialised tax legislation.
A law firm may use legal terminology unfamiliar to the general public.
A medical practice may use clinical abbreviations every day.
An agricultural supplier may use crop or chemical codes that are second nature internally but meaningless to outsiders.
None of these are problems.
They simply require context.
One of the strengths of modern AI is that, once these relationships are established correctly, the assistant can consistently explain terminology in plain language while still recognising the industry’s technical vocabulary.
Why Human Expertise Still Matters
Experiences like this reinforce an important point.
Deploying an AI chatbot isn’t just about choosing the right technology platform.
It’s about understanding how knowledge should be structured.
The implementation process includes questions such as:
- What does this acronym mean?
- Which services belong together?
- Which departments should handle which enquiries?
- What terminology do customers actually use?
- How do your staff describe your products?
- What language do your customers use instead?
These are business questions—not technology questions.
And they have a significant impact on the quality of the AI assistant.
The Good News? We Caught It Early.
One of the advantages of implementing Gus on our own website first is that we experienced these lessons ourselves before rolling out AI assistants for our clients.
As a result, our implementation process has already evolved.
Today, we don’t simply ask clients for documents.
We work with them to identify:
- Business terminology
- Acronyms
- Product names
- Internal language
- Brand relationships
- Service structures
- Customer language
- Frequently misunderstood terms
This additional knowledge allows the AI to produce more accurate, more helpful and more natural responses.
Every Lesson Makes the Solution Better
Artificial Intelligence is incredibly capable.
But like any new employee joining your business, it first needs to understand how your organisation works.
The better you explain your business, the better it represents your business.
Our experience with Gus reminded us that successful AI implementation isn’t about feeding the system more information.
It’s about feeding it the right information in the right context.
That’s a lesson we’re delighted to have learned early—because it ultimately helps us deliver better AI chatbot solutions for our clients.
Could Your Business Benefit from an AI Knowledge Review?
If your organisation has extensive product catalogues, specialised services, technical terminology, industry abbreviations or proprietary naming conventions, an AI chatbot can still become a powerful sales and customer engagement tool—but only when it’s trained with the right context.
At 3G’s and MHO, our AI chatbot implementation process goes beyond simply uploading documents. We work with you to structure your business knowledge so your AI assistant understands your organisation the way your team does.
Whether you’re a small business with a handful of services or a large organisation with hundreds of products, multiple departments and industry-specific terminology, we offer AI chatbot solutions and implementation packages to suit different business sizes, complexity levels and budgets.
Because the smartest AI isn’t the one with the most information.It’s the one that understands your business best.
So please, come and try out Gus. Gus hangs out on the bottom left of our website screen.
In our next article, we’ll share what we’ve learned and whether conversational AI genuinely improves business performance.
Access other series’ via our blog, as well as the balance of articles and posts access 3G’s other posts. Likewise you are welcome to reach out to us should you want to engage directly with us on this.
And…….. Expect more from your communication
#3Gs #3GsDigital #branding #consulting #digital #design #Content #development #maintenance #digicards #socialmedia #website #ecommerce #TraditionalMarketing #DigitalMarketing #DigitalStrategy #MarketingStrategy #DigitalMarketingStrategy #DigitalMarketingAgency #DigitalAgency #MarketingHeadOutsource #Results #DigitalResults #DigitalMarketingResults #Management #DigitalManagement #MarketingManagement #DigitalMarketingManagement #Website #WebsiteStrategy #DigitalStrategist #WebImplementation #Implement #WebBuild #SEO #SearchEngineOptimization #SEM #SearchEngineMarketing #AI #AISearch #Chatbot #AIChatbot #ConversationalSearch #Gus
