Agentic AI vs Generative AI - A Complete Guide for Businesses and Creators

Almost every business and creator around the globe believe in the unlimited potential of artificial intelligence solution. They have realised that if you want to be successful in today’s every evolving & competitive business landscape, you have to upgrade yourself to take complete advantage of this phenomenon. 

But the real question is which is the right approach for you or your business? With AI technology advancements, one should know what to prefer, what’s the difference between producing text and making selections. As we unfold the mysteries of artificial intelligence, two popular terms are highlighted, Generative AI and Agentic AI. What do these terms actually mean? What’s the point of difference between their capabilities, applications and most importantly impact on our business and in our daily lives? We have tried to explain them in this comprehensive guide, with insightful topics for deeper understanding. 

What is Generative AI & its characteristics? 

Gen AI model allows users to quickly generate fresh content based upon various inputs/prompts given by the user. The inputs could be of any form like text, images, sound clips, video clips or any other type of data. 

It utilizes neural networks to recognize the patterns and structures within the existing data to generate original & new content. Now let’s look at its characteristics. 

1. Content generation 

Gen AI excels in creating reasonable and relevant content. For instance, large language model like ChatGPT can compose long format content like, essays, answers, emails, e-books, etc, with the right & detailed inputs. 

2. Data analysis 

In this AI model, AI combines existing data and presents it in different & innovative ways. For example, AI ML tools like DALL-E can generate relevant images based on the text descriptions given by the user, mixing different styles and elements smoothly. 

3. Adaptability 

It has the capability to adapt its outputs based on the changes or feedback it receives from user prompts. This is a feature that helps AI learning process, ultimately helping AI to give improved outputs each time. 

4. Applications 

From automated journalism to creation of art, gen AI has the capability to find applications in different industries. Companies like Jasper are utilizing artificial intelligence to develop marketing content efficiently while consuming less time. 

Understanding Agentic AI & its attributes 

On the other hand, Agentic AI uses a completely different approach. In this type of model, AI has the ability to autonomously act in an environment and make decisions based on its objectives. Deep learning plays a vital role in improving its decision-making abilities. In other words, if Gen AI is primarily focusing on creation of content, Agentic AI focuses on action and interactivity within a specific context. Now let’s study the different attributes of agentic artificial intelligence. 

1. Independant function 

These systems have the power of operating independently henceforth making decisions based on already defined objectives and plans. This specific feature is what sets them apart from gen AI, which requires user prompts to give outputs. 

2. Decision making  

These systems have the ability to analyse and assess situations and identify the best course of action. Different algorithms are implemented to evaluate various components, considering potential outcomes to improve the decisions. 

3. Interactivity 

Agentic AI has the capability to interact within its environment, collecting data and modifying its action accordingly. The best real life example is self driving cars, they continuously analyze their environment/surroundings to make safe driving decisions. 

4. Applications 

Industries like healthtech, fintech and robotics are utilizing agentic AI for different purposes, from managing surgeries to complex trading in stock market. 

Generative AI vs Agentic AI – Which one to choose 

As we all now know, gen AI has the ability to produce original and new content, whereas agentic AI emphasises on carrying out tasks autonomously. This basic & functional difference highlights the definitive applications each AI model is suited for. Based on this fundamental difference, businesses can analyze, which AI model to go for! 

For creative businesses and creators 

If you are in creative industry, then opting for generative AI solution would work best for you. This will help you in creating content that is relevant for your target audience. This method boosts engagement by generating messages for particular demographics. 

For tech related businesses and professionals 

If you are in manufacturing industry or robotics, harness the power of agentic AI for its adaptive nature. It can accommodate to production scheduling, will give improved efficiency, less human-errors, and minimising downtime. As discussed, this model can learn and interact with its environment, it can adjust its actions based on real time data. 

Interesting Trends in Agentic AI & Gen AI 

Agentic AI trends to look out for  

1. Financial algorithms 

By evaluating market data and making transactions at fast speed, agentic AI is transforming trading methods in the finance industry. AI-powered algorithms are being utilized by hedge funds to identify patterns and make informed investment decisions. 

2. Robotics and automation 

For jobs requiring accuracy and efficiency, such industrial processes and warehouse automation, industries are increasingly implementing agentic AI. For instance, Amazon uses robots in its fulfilment centres to increase efficiency and streamline processes. 

3. Smart cities 

By improving energy use, transportation flow, and public safety systems, agentic AI is being included into urban planning and management. AI is being used by cities to improve public services and raise citizens' standards of living. 

Generative AI trends to look out for 

1. Deepfake technology 

The development of incredibly lifelike deepfakes is being led by generative AI solution. Although this has uses in entertainment, it also brings up moral questions with false information. The necessity for appropriate use is highlighted by the possible abuse of deepfakes in the media and in politics. 

2. Text-to-Image Synthesis 

By enabling users to create images from text prompts, platforms like Midjourney ai make art production more accessible. Users with different creative backgrounds are encouraged to innovate by this model of creativity.  

3. Art and music creation 

By assisting musicians and artists in creating original compositions, tools like AIVA are expanding the boundaries of conventional creativity. These technologies are being used by artists to experiment with new genres and styles, producing hybrid art. 

In a nutshell 

As we are witnessing the unlimited potential of artificial intelligence, understanding the difference between agentic AI & gen AI and utilizing them in a manner which will help us maximize our growth is essential. These technologies hold the power of improving our present while laying the foundation for our future innovations, which will ultimately redefining how we function with machines.