Rule-Based AI v Generative AI
Understanding the Differences Between Generative AI and Rule-Based AI
The rapid growth of conversational AI has revolutionised how businesses interact with customers.
While both Generative AI (Gen AI) and Rule-Based Intent-Led AI power communication systems, they differ significantly in capabilities, architecture, and use cases.
This is to provide a clear understanding of these technologies, helping users and organisations understand their different technologies.
What Is Rule-Based AI?
Rule-Based AI is a structured and deterministic approach to conversational AI.
This means that Rule-Based AI only gives users prior scripted answers. In many ways, you could say that the AI in Rule-Based AI is only used to understand the conversation that humans bring, not to generate answers.
It uses this vast intelligence trained on everything everywhere to understand our unique turn of phrase, our misspellings and to determine what we are really saying so that it can provide your customers and staff the exact response that we have worked out together is right, and delivers the right messages.
What Is Generative AI?
Generative AI ("Gen AI") is the type of AI that is ChatGPT, Claude and the other big AI platforms.
It uses its training to understand human comments just like Rule-Based AI, but where it differs is that it 'Generates' the response ITSELF. By 'Generate', it means the AI decides what to say and how to say it.
How does it do that?
Well, Gen AI understands patterns in language and uses this to sift through all the knowledge written down in the world and on the internet, chooses reliable, authoritative sources and puts it all together to create the response it gives to those it is talking to.
Both Rule-Based AI and Gen AI use AI to understand the input from users, but where Rule-Based AI uses this understand to respond as you want it to, Gen AI makes up it's own answers.
Which is better?
It depends on what it is being used for.
Gen AI is an extraordinary tool for understanding and communicating flexible topics and providing unstructured answers. It is excellent for research, and freeform discovery.
However it is prone to giving wrong answers very convincingly, known as 'Hallucinations', and so it is usual that it's answers need to be checked.
Also Gen AI creates it's own personality.
It is possible to nudge Gen AI to give specific messages and brand reinforcing comments through 'fine-tuning' but the costs of creating, customising and maintaining this can be eye watering and the results will always be unpredictable.
Rule-Based AI doesn't provide the free-roaming chatting capability that Gen AI does, but for companies the ability to directly control your brand voice, messages and content quickly and easily is hard to beat.
The costs of Rule-Based AI are also far more affordable, bringing AI customer care into reach for nearly all businesses including Micro yet can be scaled up to run deeply complex end to end processes.
It is also great that for Rule-Based AI with a Helpa, there is no need for any in-house or expensive technical staff.
Rule-Based AI:
- Predictable: Responses are consistent, approved and reliable.
- Natural: Good design creates human-like engagement.
- Simplicity: No need for technical support or management.
- Compliance: Ideal for environments requiring controlled outputs.
- Cost-Effective: Affordable for all.
Generative AI:
- Natural Conversations: Delivers human-like and contextually relevant responses.
- Adaptability: Handles diverse and unstructured queries, making it suitable for broad use cases.
- Scalability: Quickly scales to new domains with minimal retraining.
- Personalisation: Tailors responses based on user history, preferences, and context.
- Ethical Concerns: Risks of generating biased, harmful, or irrelevant content if not carefully managed.
- Complexity & Cost: Needs expensive technical development and maintenance to deliver custom content and brand voice.
In a Nutshell:
- Rule-Based for Core Tasks: Handles high-frequency, low-complexity interactions and transactions efficiently.
- Generative AI for Personalisation: Manages complex, dynamic conversations and unstructured queries.
Conclusion
Understanding the differences between Rule-Based AI and Generative AI is critical to deploying effective chatbot systems. While each has strengths and limitations, the choice should align with the intended use case, organisational requirements, and customer needs.
As things stand today, Gen AI is simply out of reach for all but really big organisations, and Rule-Based AI delivers in many ways more what businesses really need - controlled, safe, reliable affordable customer care and sales support.
This may change, but it will take a while at least for Gen AI to find a relevance and cost profile suitable to all businesses.
Until then, Rule-Based Helpa is here now, today, and affordable to all.
Get in touch if you'd like to discuss.