21 Min
Discover the key differences between Agentic AI and Generative AI, their real-world impact and how they can help you achieve new levels of CX success.
AI has evolved from simply generating content to actually making decisions and taking actions on your behalf.
Just a few years ago, ChatGPT could help you draft an email. Now, it can go a step further by sending you emails, too.
This shift marks the difference between agentic AI and generative AI, and it’s already changing how companies approach customer experience (CX).
In this guide, we’ll explore agentic AI vs generative AI, what sets them apart, how companies are using them in the real world today, and how you can use them to deliver better CX.
Table of contents
- What is Agentic AI?
- What is Generative AI?
- Agentic AI vs Generative AI: Key Differences
- Examples of Brands Using Agentic & Generative AI
- How does Agentic AI & Generative AI Ensure Better CX?
- Agentic AI & Generative AI: How They Work Together for Better CX?
- What’s in Future for Generative AI & Agentic AI
- How Knowmax Powers Better CX with AI
- FAQs
What is Agentic AI?
To have agency means to have the ability to make choices and take action to achieve a goal. Agentic AI is a type of AI that has agency, which means it can make decisions and actually take actions to achieve a given goal all on its own.
You probably use agentic AI every day without even realizing. When you tell Alexa, Siri or Google Assistant to turn off the lights or set the alarm, that’s agentic AI in action.
This is because these AI assistants understand what you want them to do, the steps they need to take to do the given task, and then they take action to complete the task without your help.
Businesses also commonly use agentic AI when they employ customer support chatbots to resolve support tickets by automatically resetting passwords or processing refunds.
What is Generative AI?
Generative AI is a type of AI that generates text, videos, images, and more based on the user’s prompts.
You use generative AI every time you ask ChatGPT to write an email, generate an image or explain a complex concept to you like you’re five.
And you’re not the only one, organizations are using generative AI to improve self-service by helping customers easily get answers to common queries from the company knowledge base.
See How Gen AI Can Elevate Your CX
Agentic AI vs Generative AI: Key Differences
| Agentic AI | Generative AI (Gen AI) | |
|---|---|---|
| What is it? | AI that does tasks for you autonomously | AI that generates content for you |
| How much do you need to be involved? | Not a lot. You just tell what you want, and it’ll work out how to do it | A lot. You need to give prompts and review the outputs |
| Can it use other tools? | Yes, can use other tools | No, can’t use other tools |
| What are the drawbacks? | Complex to set up | Creates content but won’t take any actions for you |
| How can it improve your CX strategy? | Resolves issues, updates customer information, and follows up with customers automatically | Creates personalized support replies, recommendations, or onboarding messages at a large scale |
Examples of Brands Using Agentic & Generative AI
This difference between agentic AI and generative AI becomes clearer when you look at how they are being applied by the biggest names:
1 Knowmax – Generative AI
Knowmax is an AI-powered knowledge management platform that helps CX teams to deliver error-free support across channels. It uses AI to help CX professionals create and translate support articles, decision trees, FAQs faster.
Its AI search also helps agents to quickly find answers from the knowledge base and even ask follow-up questions for more clarity.
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2 Stitch Fix – Generative AI
Stitch Fix is a personal styling service that combines AI and human expertise to help customers discover clothes they’ll love.
It uses generative AI to analyze a customer’s preferences, body type, and style history, then generate personalized clothing recommendations. Stylists review and refine these suggestions. It also uses predictive algorithms to spot fashion trends before they become mainstream, guiding inventory and design decisions.
3 Siemens – Agentic AI
Siemens is a global leader in industrial automation and smart manufacturing technologies. It uses agentic AI in factories to help machines make smart decisions on their own, without needing engineers to step in.
Siemens is doing this through its Industrial Edge platform, where machines can now automatically adjust settings like speed, temperature, or pressure based on what’s happening in real time. So, if a production line starts overheating, the AI can automatically cool it down or reroute tasks to prevent downtime.
4 Yoodli – Generative AI
Yoodli is a communication coaching platform focused on helping people become better public speakers.
It uses generative AI to analyze users’ speech in real time by flagging filler words, pacing issues, or awkward phrasing and then generates personalized coaching feedback and reworded suggestions. Think of it as an AI-powered speaking coach that helps improve communication.
5 Blue River Technology – Agentic AI
Blue River Technology builds precision agriculture solutions to make farming more efficient and sustainable.
It uses agentic AI in its See & Spray system, which identifies individual plants in real time and instantly decides whether to spray them with herbicide or not. Instead of just recognizing weeds, the AI acts autonomously on the spot, thus reducing chemical use, protecting crops, and requiring no manual decisions during operation.
6 Notion – Generative AI
Notion is an all-in-one workspace for notes, docs, and task management used by millions.
It uses generative AI to supercharge productivity by helping users write, summarize, and edit content directly inside their notes and documents.
For example, you can ask it to “turn meeting notes into a project plan,” and it’ll instantly generate a structured, readable output. It also helps translate, rephrase, or generate ideas based on rough inputs.
7 Inworld AI – Agentic AI
Inworld AI develops advanced tools for game studios to create emotionally intelligent, interactive non-player characters (NPCs).
Its agentic AI allows NPCs to remember past interactions, understand context, and make autonomous decisions about how to respond or behave. Instead of reading pre-written lines, these characters can adapt their actions and dialogue on the fly, creating more immersive and lifelike gameplay experiences.
How does Agentic AI & Generative AI Ensure Better CX?
Within CX both agentic AI and generative AI bring unique strengths to the table. Here’s how they empower your CX teams.
Generative AI improves CX by:
- Saving time by quickly creating help articles, step-by-step guides, and internal docs
- Powering self-service by helping customers quickly find answers from the knowledge base
- Making live support faster and smoother by suggesting CX agents’ replies, showing customer history, and offering helpful solutions
- Supporting global customers more easily by translating content instantly
Agentic AI improves CX by:
- Making decisions and executing multi-step workflows based on real-time customer inputs
- Guiding customers through complex troubleshooting or eligibility checks
- Resolving common issues like order modifications, plan changes, or account unlocks completely autonomously
- Adapting dynamically in real time by detecting sentiment, urgency, or potential failure points and adjusting its course to reduce friction
How AI Handled 73% of the Transactions Successfully for a Leading Telecom
Agentic AI & Generative AI: How They Work Together for Better CX?
Agentic AI and Generative AI are not mutually exclusive. In fact, they often collaborate to deliver faster human-free customer experiences.
1. Extremely personalized & proactive interactions
Generative AI is great at quickly creating personalized content like tailored product recommendations or responses. And Agentic AI is good at making decisions like when and how to deliver those responses based on customer behavior or context.
For example, if a virtual agent notices a user lingering on a checkout page. It uses Generative AI to create a friendly message with a discount code and autonomously sends it to the customer, giving him a slight nudge to complete his purchase.
2. 24/7 intelligent support
With agentic AI watching over conversations across channels, and generative AI handling the responses, customers can get helpful support 24/7.
For example, a customer asks about a billing issue via chat at midnight. The agentic system can pick up the intent and use generative AI to explain charges clearly, with links to relevant documents.
Provide Intelligent Support 24/7
3. CX support across channels and formats
Generative AI can generate various formats like text, voice, images, and more. Whereas agentic AI makes sure everything stays coordinated across all the channels your customers use, like chat, email, or even phone support.
You can combine their strengths in a scenario where a customer sends in a photo of a damaged item. Agentic AI can figure out what’s wrong, and generative AI can put together a kind message offering a replacement or refund. Then agentic AI can send the message via the same channel the customer uses and process the replacement or refund.
4. Makes the customer journey seamless
Agentic AI is great at seeing the bigger picture, like mapping the entire customer journey and spotting where people get stuck. Generative AI can then jump in to create content that guides them through those rough patches.
For example, if a new user is struggling to get through onboarding, the system might notice and offer a quick tutorial video or open up a helpful chatbot customized just for them.
What’s in Future for Generative AI & Agentic AI
Now that you know what Gen AI and Agentic AI are capable of, here’s a glimpse of what we think the future holds.
Generative AI has come a long way from writing emails to generating images and even designing products. And we think it’s only going to get more creative and context-aware.
- Expect talking to generative AI to feel even more like talking to a real person when it starts understanding tone, emotions, and subtle context better than ever.
- In the future, we think it won’t be limited to generating one content format at a time. Future Generative AI will fluidly combine voice, images, video, text and even code to deliver a more interactive experience.
- Also, you might be able to provide hyper-personalized support at scale. Like product descriptions, support replies, and marketing messages that are custom-tailored not just by segment, but down to the individual.
We feel that Agentic AI is going to evolve beyond just being the executor to acting with a sense of purpose.
- Agentic AI may get better at interpreting signals and making autonomous decisions in the moment, without always needing a predefined rule.
- We might see it handling more complex workflows across multiple systems. Like a digital employee who not only reacts but plans and executes.
- Future agentic systems may learn which strategies work best for each customer journey and improve the entire experience automatically.
How Knowmax Powers Better CX with AI
At Knowmax, we don’t just use AI. We use knowledge-backed AI.We use knowledge-backed AI that combines the strengths of agentic AI vs generative AI to deliver real results.
Our centralized knowledge base powers generative AI to ensure every response is accurate, consistent, and compliant. AI helps CX teams quickly create and translate support content like FAQs and SOPs across 25+ languages.
It turns your knowledge into action by reducing handling time, improving resolution rates, and delivering smarter CX at scale.
FAQs
Q1. What are the 4 types of AI?
The four types of AI are:
1. Reactive Machines: Basic AI that reacts to situations (e.g., IBM’s Deep Blue chess computer).
2. Limited Memory: AIs that use past data to make decisions (e.g., Self-driving cars using real-time traffic data).
3. Theory of Mind: A future AI that understands emotions and thoughts.
4. Self-aware: An advanced, theoretical AI that is conscious of itself.
Q2. What is the difference between GPT and agentic AI?
Generative AI, such as GPT, creates content like text, images, or code based on prompts. For example, GPT-4 generating blog posts or ChatGPT answering questions.
Agentic AI, on the other hand, takes actions, makes decisions, and pursues goals autonomously. For instance, AutoGPT planning and executing multi-step tasks like researching topics and booking appointments.
Q3. What is next after agentic AI?
After agentic AI, the next step is likely Artificial General Intelligence (AGI), AI systems capable of reasoning, learning, and solving a wide range of problems like a human, with autonomy and adaptability across domains.
For example, an AGI system would be able to learn a new profession from scratch, just like a human.
Q4. Is agentic AI the same as generative AI?
No. Agentic AI and generative AI are different. Generative AI focuses on content creation, while agentic AI involves autonomous decision-making and goal pursuit. Agentic AI may use generative models but extends their functionality with action-oriented intelligence.
For example, generative AI might write an email; agentic AI could write the email and send it, schedule a follow-up, and analyze responses all on its own.
