Artificial intelligence has rapidly taken over the digital world and different industries!
The major contribution in this broader expansion of AI goes to “Generative AI”, that has transformed the day-to-day lives of not just industries but common people as well. After generative AI, “Agentic AI” is coming as the new frontier in the AI industry, and is expected to drastically change the industrial operations, and more.
What Is Agentic AI?
In psychology, “agency” refers to a person’s ability to make choices and act independently. In simple words, agentic AI is an AI that can think, plan, and act on its own without human interference.
Agentic AI operates through AI agents and facilitate their interaction with human beings. This happens by merging different AI technologies like large language models (LLMs), machine learning, deep learning, to create AI agent analyse large data sets, and take actions based on the goals.
Agentic AI allows the model to take autonomous decisions and solve various problems while adapting to the fast-paced changing market changes.
Example of Agentic AI
Suppose you are looking to book flights, a traditional AI like ChatGPT can help you in your queries and might recommend you top websites to book flights. On the other hand, agentic AI books the flight for you, compares prices, checks for delays, and even reschedules if needed, all by itself.
Thus, Agentic AI is like a personal assistant who knows what to do, and how to do it in a way it suits you the best!
What is the Difference Between Agentic AI and AI Agent?
An AI agent works with predefined set of rules for a specific goal, while agentic AI is a more smarted version of AI that can see the running operations, and take required actions, all by itself. It can understand the user queries almost like humans and get the task done quickly and accurately.
To help you better understand the difference between AI agent and agentic, here is a table given below:
| Features | AI Agents | Agentic AI |
| Definition | AI systems that sense, process, and act based on predefined rules.
|
AI that can think, plan, and act autonomously, without step-by-step human guidance.
|
| Level of Autonomy | Follows instructions and reacts to inputs.
|
Can set its own goals, make decisions, and take action.
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| Example | A chatbot that answers customer queries based on a script.
|
A virtual assistant that books flight, compares prices, and reschedules automatically.
|
| Decision-Making | Predefined logic and fixed responses.
|
Dynamic reasoning adjusts its actions based on real-time data.
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| Learning Ability | Limited, only improves if retrained.
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Self-improves by learning from past actions.
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| Real-World Example | AI customer support bots, recommendation engines, self-driving car sensors.
|
AI research assistant that autonomously browses, summarizes, and makes reports. |
Features Of Agentic AI
These are some must-have features that any agentic AI model must have:
Smart Decision-Making
Agentic AI is well trained to analyse past and current data. Moreover, it closely adapts to users preferences, their habits, and changing market trends. Following all the predefined rules, and using such broader data analytics capabilities, agentic AI makes the best of the decisions that contributes to company’s or an individual’s quality of decisions.
Advanced Problem-Solving
Agentic AI can be the go-to solution for companies whenever they are looking to break down complex problems into understandable and concluding prospects. Moreover, with each decision the agentic AI improves its algorithm, ensuring more accurate decisions over time.
High-Level Autonomy
Unlike AI agents, agentic AI is highly self-dependant, and operates independently without need of preset rules, execution of tasks, or strategy adjustment. It automatically identifies what needs to be done, and how to handle the dynamic situations effectively.
Seamless Interaction
Agentic AI have the ability to naturally communicate with humans while understanding the context of the conversation. The software integrates seamlessly with the business systems and provide real-time assistance, execute actions without any constant supervision.
Strategic Planning & Execution
Beyond simple task completion, agentic AI formulates multi-step strategies, prioritizing tasks, optimizing workflows, and adjusting plans based on new data. This enables businesses to improve efficiency, streamline operations, and achieve long-term goals.
Adaptability and Self-Learning
Agentic AI has the true power to learn user behaviour, their purchasing habits, budget or brands they mostly prefer and more. Based on the same, the model quickly adapts to the user preferences, enhances its personalization, and recommends better-suited solutions over time.
Natural Language Processing
Agentic AI models must have the natural language processing ability like large language models (like ChatGPT). In today’s age any AI model is already expected to have NLP to easily understand the human language. When Agentic AI models integrate with NLP, they form a powerful combination. NLP enables the AI to understand user input and context, while Agentic AI processes this information to determine the best possible solution and take appropriate actions autonomously.
Industrial Applications of Agentic AI
Agentic AI models are much more dynamic and complex task handling ability than the LLM models that are used to get personal and professional assistance by people in their daily lives. Hence, agentic AI are expected to bring some mind-blowing transformations. Below given is a walk through:
Customer Service
Traditional AI chatbots had limited capabilities and worked according to already defined rules and regulations. Seeing other side, Agentic AI powered chatbots or customer service bots are like human customer service agents. They understand the problems, their intentions, and know what solutions can suit them the best. Using all the past customer problem cases, and organizations data, agentic AI can provide real-time and effective solutions to customers while keeping the company’s rules in check.
Manufacturing
Agentic AI for manufacturing can take over different duties like optimizing workflows, providing ultimate customizations to product, and assist in smart manufacturing. It can utilize data from machines, sensors, and other components in factories to provide different actionable insights like product design improvements, better inventory management, enhanced machine maintenance, and more.
Sales Support
Sales team in any organization is often made to do lot of manual tasks like sending mass emails, personalized messages, and other paperwork. Manually executing such tasks take lot of time and effort which can be utilized for more crucial tasks like provide enhanced customer experience to pitching hot leads (potential buyers). Agentic AI in this case automates all these repetitive tasks, thereby boosting efficiency and increase lead closers.
Health And Social Care
Agentic AI can be highly useful is boosting healthcare delivery and services. It not only provides the basic customer support, but can analyse patient’s past medical history, public healthcare data, and recommend best-suited treatments to the doctors. In the absence of any medical facility, agentic AI chatbots can help patients or their families in handling their emergency health conditions until proper medical care is provided. Healthcare institutions can use agentic AI to optimize workflows and automate the appointment scheduling process in such a way patients don’t must wait in long waiting queues. Hence, from providing first hand of medical help to enhanced healthcare delivery, agentic AI holds huge potential for the healthcare industry.
Automated workflow management
Be it in any industry, different tasks like data collection, data entry, or report generation, are done manually and repeatedly. The list of such tasks is never-ending, and they are time-consuming yet necessary. Agentic AI-powered business systems can automate all such tasks and get it done in very less time and without the human interference.
Financial Risk Management
For trading, and investment businesses, agentic AI is like an advanced finance manager that can analyse the real-time market data trends, different exchanges, to closely identify top potential opportunities. Agentic AI can make investment a continuous 24/7 operation and make high-quality investments at the right time.
Cybersecurity
Agentic AI is like high-power security guard to all your digital data, transaction information, user details, and funds. It can deeply analysed all the patterns of past and on-going cyber scams and be highly sensitive to any fraudulent activity or scam that takes place. Agentic AI can take all the necessary actions to prevent any security breaches at the earliest.
Business Benefits of Agentic AI
Greater Specialization
Agentic AI allows businesses to automate specialized tasks with greater accuracy and efficiency. Instead of relying on broad automation, companies can create AI agents for specific roles like research, analysis, and workflow management. These agents work together effortlessly, much like human teams, coordinating tasks and improving overall productivity.
Enhanced User Experience & Trust
Agentic AI is basically providing innovation at the fingertips to users. They get to experience utmost personalization, quick solutions to their problems, smart recommendations, and data-driven insights for better decision making. All of this directly improves the user experience and builds their trust on the business services.
Boosted Productivity
With AI driven automation, self-reliance, reduced manual errors, and fast task execution, the productivity of the business is dynamically boosted. Agentic AI optimizes processes, reduces bottlenecks, and ensures efficient resource utilization, leading to a significant productivity boost.
Cost-Efficiency With Quality Decision Making
By reducing labour-intensive tasks and automating decision-making, Agentic AI lowers operational costs while maintaining high-quality outputs. It enhances strategic planning by analyzing vast datasets, identifying patterns, and making informed decisions that drive business growth and efficiency.
Real World Examples of Agentic AI
AI Research Assistants
Tools like AutoGPT and AgentGPT autonomously research topics, summarize data, and generate reports without constant human input.
Automated Trading Bots
AI-driven trading bots in crypto and stock markets analyze trends, execute trades, and adjust strategies in real-time to maximize profits.
AI Customer Support Agents
Advanced chatbots like ChatGPT-powered support agents handle complex customer queries, provide instant solutions, and escalate issues when needed.
Autonomous Code Assistants
AI tools like GitHub Copilot X write, debug, and optimize code by understanding project requirements and improving over time.
Smart Personal Assistants
AI systems like Google Assistant, Siri, and Alexa are evolving into agentic models, managing schedules, booking appointments, and handling complex requests without step-by-step instructions.
AI-Powered Marketing Automation
Platforms like HubSpot and Marketo use agentic AI to personalize content, automate email campaigns, and optimize ad strategies dynamically.
Autonomous Business Workflow Management
AI agents in enterprise solutions like Salesforce Einstein automate sales forecasting, customer interactions, and workflow optimizations.
How To Develop Your Own Agentic AI Bot?
Define the Purpose & Use Case
Identify the tasks like workflow automation, data analysis, customer support, trading risk management etc., that AI bot must handle. Ensure it aligns with your business needs and improves efficiency.
Outline the AI Agent Architecture
AI agent architecture basically has 4 layers:
- Perception Layer – Collects and processes real-time inputs from users, external APIs, databases, or IoT devices.
- Cognition & Decision-Making Layer – Uses advanced reasoning (ReAct, Chain-of-Thought) and RAG (Retrieval-Augmented Generation) to analyze, strategize, and decide actions dynamically.
- Autonomy & Execution Layer – Executes tasks independently, manages workflows, and adapts actions based on real-time data.
- Self-Learning & Adaptation Layer – Continuously improves through reinforcement learning, user feedback, and historical data analysis.
Choose the Right AI Framework & Tools
Choose the right framework and tools, like the following:
- Use LLMs (Large Language Models) like GPT-4, Llama, or Claude for natural language understanding.
- Leverage ReAct (Reasoning + Acting) framework for autonomous decision-making.
- Integrate RAG (Retrieval-Augmented Generation) for real-time, context-aware responses.
Implement Autonomy & Interactivity
APIs and webhooks would be used to connect agentic AI with databases, CRM, and business tools. This will help in training the AI model with the past data for getting accurate outputs. This also allows the bots to different actions like sending email, placing orders, or updating records.
Test & Optimize Performance
The AI bot is tested through simulations and A/B testing to refine accuracy and decision-making. Continuous monitoring and feedback loops help it learn and improve, reducing errors over time. Performance metrics are analyzed regularly to ensure the bot adapts to changing user needs and business goals.
Deploy & Continuously Improve
After deployment, the bot integrates into business workflows and adapts based on user feedback. Regular updates, security checks, and fine-tuning ensure long-term efficiency and reliability. Ongoing improvements help the AI stay aligned with evolving market trends and operational demands.
Best Way To Create Agentic AI Solution For You!
The best way to create an agentic AI solution for you is by partnering with Blocktech Brew for Agentic AI development services. This will vanish your hassle of making a strategy, deciding tech stack, or ensuring proper execution. Our end-to-end agentic AI development services can provide you everything from consultation and planning to development and model integration right at your finger tips!
If you are just someone who wants to have a comprehensive consultation, then we have a dedicated agentic AI consultation team that will closely understand your business goals, and help you with an advanced agentic AI implementation strategy.
Reach out to us via email: business@blocktechbrew.com to know more.
I am the CEO and founder of Blocktech Brew, a team of blockchain and Web 3.0 experts who are helping businesses adopt, implement and integrate blockchain solutions to achieve business excellence. Having successfully delivered 1000+ projects to clients across 150+ countries, our team is dedicated to designing and developing smart solutions to scale your business growth. We are focused on harnessing the power of Web 3.0 technologies to offer world-class blockchain, NFT, Metaverse, Defi, and Crypto development services to businesses to help them achieve their goals.
