AI has transformed significantly even since its emergence, evolving from a rule-oriented system functioning in strict boundaries to more self-targeted and dynamic technologies. Businesses are getting more opportunities and superseding competitors with the advancement of AI technology. Agentic AI, the transformative AI player, can be the next big thing for SMEs to maximize their ROI. Agentic AI is expected to dominate in many industries in the future.
Many businesses aren’t still aware of what is Agentic AI. Some businesses think it is only AI’s another term, while other companies think it must be something different. Do you want to use this technology to grow your business? You should learn the differences between traditional AI and Agentic AI. But before that let’s discuss what they are with their salient features. Keep reading this post to learn the same.
What is Traditional AI?
Traditional AI is a robot, which performs the activities you ask it to do. It can nicely do certain tasks but lacks the brain to think about how to improve its functionalities and what things to do thereafter. Traditional AI processes data and specified rules to function perfectly. It may help in identifying trends in the previous data, predicting results, and giving recommendations. However, traditional AI functioning fails when unexpected things happen.
Features of Traditional AI
Here are the salient features of traditional AI:
- Task-centered : It can perform well-defined and narrow activities, such as sorting emails and predicting sales.
- Rules-Oriented : It follows rules depending on what it has been structured to do.
- Data-driven : It depends largely on historical data for functioning.
- Restricted Flexibility : Since it allows limited flexibility, a human is required to intervene and work as required.
Traditional AI Examples
- Predictive analytics : Detect fraud and predict sales.
- Recommendation systems : Recommend products depending on earlier user behavior.
- Customer service chatbots : Reply to primary queries with scripted replies.
Traditional AI performs the required activities, however it may not deliver the desired results. It is a tool that functions perfectly for solving certain issues. However, it doesn’t work well in other and changing situations without anyone’s assistance.
What is Agentic AI?
The innovative AI may think and take independent actions with no consistent human intervention. Agentic AI can make smart decisions depending on real-time data, understand its activities, and adjust to changing situations.
Features of Agentic AI
Here are the salient features of Agentic AI:
- Aware of Context : It understands the environment and modifies these actions as required.
- Autonomous : It can take the next step without human efforts.
- Adaptable : It learns well and improves depending on the surroundings and experiences.
- Non-deterministic : A similar condition may deliver different outputs depending on real-time data and previous experiences.
- Goal-centric : It works to deliver specific results, such as enhancing CX and boosting efficiency.
Agentic AI Examples
- Personal Assistants : AI finishes tasks, predicts what you will require next, and makes decisions depending on your patterns.
- Smart Manufacturing Systems : AI-activated production lines modify in a real-time environment to maximize efficiency and react to changes.
- Self-Driving Cars : Such vehicles follow specific rules and consistently make choices depending on traffic, road conditions, and hurdles.
Agentic AI can solve issues by being self-aware and doesn’t require to be given instructions. It adapts to the changing environment and keeps evolving to get better as time passes by.
Traditional AI vs Agentic AI – Key Differences
| Basis | Traditional AI | Agentic AI |
|---|---|---|
| Independence and Decision-Making | Functions as a calculator when asked to depend on the set rules without thinking for own. | Makes decisions depending on the latest happenings and gets flexible as situations change |
| Learning and Adaptation | Doesn’t learn by itself and requires human efforts and management updates for enhancement | Understand past experiences and modify their activities as required |
| Human Intervention | Requires human intervention in troubleshooting and guidance | Learns from past experiences and modify experiences accordingly |
| Problem-solving Strategy | Fix minor issues | Fix complex and dynamic issues |
| Change end Uncertainty Management | Functions well in a stable environment with precise data and rules | Functions well in a risky environment with uncertainties and real-time changes |
Here are the major differences between traditional AI vs Agentic AI.
1. Independence and Decision-Making
Traditional AI works as a calculator when you ask it to depend on pre-decided rules without thinking for itself. However, Agentic AI functions as a decision-maker and makes choices depending on the current happenings with adapting flexibility as situations change.
For instance, a traditional AI may respond to customer queries with a specific script. Agentic AI may change its responses depending on the customer’s voice tone, previous interactions, and time of the day.
2. Learning and Adaptation
Traditional AI does not learn by itself and requires manual updates and human input for improvement. On the contrary, Agentic AI learns from previous experiences and adjusts its activities accordingly. It is an AI, which consistently gets advanced without requiring the intervention of a programmer if something new occurs.
For instance, a traditional AI detects fraud and may flag illegal transactions depending on the last fraud incidents. However, Agentic AI architecture can keep adjusting the fraud detection models depending on the new kinds of fraud it experiences.
3. Human Intervention
Traditional AI requires humans to get involved in troubleshooting or guidance, mainly when things don’t happen as per the plan. However, human intervention is still crucial but is required less every day with Agentic AI. It may work almost independently, which frees up human beings to focus on other important strategic activities.
For instance, traditional AI may respond to queries without proactivity or context in the customer support environment. Agentic AI may evaluate customer emotions, give solutions, and suggest follow-up issues and questions.
4. Problem-Solving Strategy
Traditional AI can fix minor issues, such as differentiating emails and processing invoices. Unfortunately, it can’t do anything exceptional when new and sudden things happen. Agentic AI can manage complex and dynamic issues effectively, and make the right choices to meet the goals.
For instance, traditional AI may predict stock levels depending on previous data. However, Agentic AI may adjust to real-time if the product delivery gets delayed or the demand suddenly increases. It can also automatically negotiate with dealers.
5. Change and Uncertainty Management
Traditional AI functions most effectively in a stable environment with clear rules and data. Agentic AI dominates in risky environments that are created by uncertainties and changes in real time.
For instance, traditional AI solutions may depend on historical market data to make predictions. However, Agentic AI can modify its strategies in reaction to unexpected global events and market changes.
Why Should You Learn the Differences Between Traditional AI and Agentic AI for Your Business Growth?
You get new opportunities to grow your business in the ways below once you understand the differences between Traditional AI and Agentic AI.
1. Increase Efficiency and Save Costs
Using Agentic AI, businesses can automate more complex processes requiring flexibility and decision-making. This leads to better operational efficiency and cost savings. For example, a self-adjusting supply chain powered by Agentic AI could save a company significant labor and inventory costs.
2. Deliver Better CX
Agentic AI helps companies offer more proactive and personalized CX. Rather than responding to user queries, it understands their requirements and gives the best solutions. Such a personalized interaction satisfies more customers, which motivates them to come back.
3. Scale Consistently
Traditional AI systems tend to require consistent adjustments and maintenance during the scaling. However, Agentic AI may scale better. It adjusts and transforms without your additional efforts as your company grows and invades new marketplaces.
4. Get a Competitive Edge<
Businesses implementing Agentic AI Microsoft have a responsive and agile approach to changes in the marketplace. Such flexibility and speed may help you stay ahead of competitors and depend on more traditional AI systems.
5. Risk Management
Agentic AI helps in combatting risks with real-time adaptation in industries such as logistics, healthcare,, and finance. For instance, a financial institution may implement Agentic AI to modify investment strategies depending on real market data and diminish exposure to unexpected market changes.
The Bottomline
The key differences between Agentic AI and Traditional AI are not technical but strategic, as discussed above. Businesses implementing AI agents can be well-equipped to adapt to changing environments, automate competitive activities, and get a competitive edge in the consistently transforming scenario. Agentic AI offers vast opportunities to respond to and drive changes, be it in finance, eCommerce, healthcare, and any other industries. Businesses deploying Agentic AI can always stay ahead and use AI in smarter ways. Thus, you should start using it for your business if you haven’t yet.
