Ai Tech

Agentic AI: The Next Step in Artificial Intelligence Evolution

Published

4 months ago

January 26, 2025

Introduction: What’s All the Hype About AI Agentic?

Artificial Intelligence, or AI, has come a long way in the past few years. From simple programs that can follow commands to super-smart systems that can learn on their own, AI is changing the way we live and work. But now, there’s something even more advanced coming into the picture—AI Agentic.

But what is AI Agentic? And why is it considered the next big leap in the world of technology? In this blog post, we’ll take a deep dive into agentic AI, its features, how it works, its potential, and the challenges it presents. By the end, you’ll understand how agentic AI could shape the future and how it’s different from the AI we know today.

1. What is AI Agentic?

To start, let’s define agentic AI. Simply put, agenticAI refers to AI systems that can act autonomously—meaning they don’t need constant human instructions to function. Think of it like a robot that can make decisions and take actions on its own without needing someone to tell it what to do every time.

In traditional AI systems, machines typically react to commands or follow pre-set rules. But agenticAI has the ability to make choices based on what it observes and learns. It’s more like a self-thinking AI that can set goals and work to achieve them without external guidance. This kind of AI is like having a virtual assistant that doesn’t just follow orders—it can anticipate your needs and make suggestions based on its understanding.

You might hear some people talk about “agenticness” when referring to AI. This just means the degree to which an AI is able to act independently, make decisions, and learn on its own. It’s about giving the AI agency, much like how humans make decisions based on our experiences and information.

2. The Evolution of AI: From Narrow to Agentic

To understand why agentic AI is so exciting, it helps to look at how AI has evolved over the years.

Narrow AI, which is the type of AI we’re used to today, is limited. It can perform specific tasks really well, but it can’t think outside the box. For example, a voice assistant like Siri or Alexa can answer questions, but it can’t think for itself or make decisions beyond what it’s programmed to do.SITE

Now, AI Agentic is a step beyond that. It’s more flexible and able to handle different tasks that might require a bit of creative thinking or decision-making. This type of AI is on its way to becoming general AI, which is even more advanced and closer to how humans think and reason.

For example, imagine an agenticAI system that’s trained to play a game like AI Undertale. Instead of just following the game’s rules, the AI can adapt and create its own strategies to win, based on how the game changes. It’s no longer just reacting to inputs—it’s actively shaping its actions.

3. Key Features of Agentic AI Systems

Now that we know what agentic AI is, let’s look at its most important features:

Autonomy: This is the key feature of agenticAI. The system can perform tasks on its own, without human help. For example, an agenticAI vendor might sell a tool that can handle customer support without needing a human agent to answer every question.
Adaptability: An agenticAI system doesn’t just stick to a set of rules. It learns from the environment and adapts its actions over time. This means it gets better at making decisions as it collects more data.
Intentionality: An agenticAI tool or system can set its own goals and figure out how to reach them. For instance, in an agenticAI architecture, an AI might be programmed to solve a problem by choosing the most efficient solution based on its experiences.
Interactivity: These systems are not only reactive—they interact with their environment. For example, an agenticAI software could interact with other AI systems and humans, learning and adapting based on the feedback it receives.

4. What Can Agentic AI Do? Exploring Potential Applications

Now that we know what agentic systems are, let’s explore what they can actually do. Here are a few real-world uses:

Business: AgenticAI companies are already making strides in automating decision-making. For example, agenticAI tools can help businesses predict trends or optimize logistics by making decisions based on data patterns. This reduces the need for humans to monitor everything constantly.
Autonomous Vehicles: AgenticAI vendors are working on self-driving cars that can make decisions in real-time. A self-driving car, for example, can adapt to its surroundings, avoid obstacles, and follow traffic rules, all without human input.
Healthcare: Imagine an agenticAI system in a hospital that can predict patient conditions, recommend treatments, and even schedule appointments. AgenticAI software could revolutionize how healthcare professionals make decisions, improving patient outcomes.
Personal Assistants: AI that goes beyond just following commands. AgenticAI tools could help you plan your day, remind you about upcoming tasks, and suggest activities based on your preferences.

5. Why Agentic AI Matters: The Benefits of Autonomy

So, why does agentic AI matter? There are several advantages that come with giving AI more autonomy:

Increased Efficiency: With agentic AI systems taking over complex tasks, humans can focus on more creative or strategic work. For example, in agenticAI labs, scientists can use AI to run simulations, analyze data, or even conduct research.
Improved Decision-Making: AgenticAI can analyze huge amounts of data much faster than humans. This leads to better, more informed decisions. For example, an agenticAI architecture could optimize a company’s operations in real-time based on changing conditions.
Personalization: Agentic AI can adapt to users’ preferences and provide tailored experiences. Whether it’s a recommendation engine or a virtual assistant, the AI gets smarter the more you use it.

6. Challenges and Ethical Questions Around AgenticAI

While agentic AI is powerful, it also raises some important questions:

Accountability: If an agentic AI system makes a mistake, who is responsible? For example, if an agentic AI vendor provides a product that malfunctions, it’s unclear whether the developer, the AI itself, or someone else should be held responsible.
Transparency: It’s crucial that we understand how agenticAI models make decisions. Without transparency, these systems could become “black boxes,” and we might not know why the AI is making certain choices.
Bias: AgenticAI systems can unintentionally pick up biases from the data they’re trained on. This means that, if we’re not careful, AI could make unfair or harmful decisions.
Security: Since agenticAI has autonomy, it’s important to make sure these systems are secure and won’t be misused by malicious actors. Ensuring the safety of AI is a key concern for companies working on agenticAI architecture.

7. The Future of AgenticAI

Looking ahead, agenticAI is only going to get better. Here are some things we can expect:

Integration into Daily Life: We’ll likely see more agentic systems in everyday life. For example, agentic AI tools might help you make decisions about what to buy, how to manage your time, or even what to eat.
Human-AI Collaboration: Instead of agentic AI replacing humans, the future might bring collaboration. Imagine working alongside agenticAI systems to solve problems, with the AI handling repetitive tasks while you focus on creative solutions.
More Open-Source Projects: Some companies are creating agenticAI open source projects—these allow anyone to develop and improve upon the AI. This helps ensure that agenticAI is accessible and can evolve quickly.

Conclusion:

Preparing for a Future with Agentic AI

In conclusion, AI Agentic represents a new frontier in artificial intelligence. By giving machines the ability to act independently and make decisions, we’re opening up new possibilities for technology. From healthcare to business and beyond, agentic AI could be the key to solving some of the world’s toughest problems.

As we move forward, it’s important to keep asking questions about how these agentic systems are developed and how we can ensure they’re used ethically. Agentic AI will no doubt be a huge part of our future, so it’s up to us to guide its evolution.

Ai Tech

Nvidia Stock Crash: 5-Year Return 1500%, But Should You Buy Now?

Published

1 month ago

May 6, 2025

Pinkesh Jain

Nvidia stock made a huge jump in the last five years, delivering about a 1500% return. This strong gain put Nvidia among the best-performing stocks in the semiconductor and tech sectors. But the stock price has dropped recently. Many investors wonder if it is a good time to buy Nvidia stock now. In this article, we look at Nvidia’s history, recent price changes, market views, and expert opinions to help you decide.

Nvidia’s Strong 5-Year Growth

Stock grew fast thanks to new tech in GPUs (graphics processing units), AI (artificial intelligence), and data centers. Its stock rose by around 1500% over five years, leaving many other stocks behind. Early buyers earned big profits. What helped Nvidia grow this much?

Leading GPU maker for gaming and professional use
Expanding into AI and machine learning with special chips
Growing role in data centers and cloud computing
Smart buys and deals with other companies

What’s Behind Nvidia’s Recent Stock Drop?

By May 2025, shares hovered around $113, down from recent highs¹. Some investors call this drop a “Nvidia stock crash.”

Reasons for the Price Swings

Here are some reasons Nvidia’s stock is jumping up and down:

Market Shift: Investors moving money from tech stocks to safer or value stocks.
Big Picture Issues: Rising inflation, higher interest rates, and global problems hurting market mood.
Industry Problems: More chip competition, supply issues, and extra government rules.
Profit-Taking: Investors selling shares to lock in gains after big rises.

What Does Technical Analysis Say?

Traders use charts and numbers to watch stock moves. To understand the latest technical levels and possible trends for stock, watch this insightful video providing detailed market analysis.

Watch this technical analysis video on Nvidia stock:

Important points include:

Support near $105: If the price falls below this, selling might speed up.
Resistance at $120-$125: Price may struggle to go above this range.
Indicators hint at a pause before the next move.

Knowing these numbers helps buyers and sellers pick good times to act.

Company talks on social sites show mixed feelings. The Fear & Greed Index is closer to “fear,” suggesting many traders feel nervous about the near-term outlook.

What This Means for You

Fear means many are cautious and may wait.
Neutral overall mood shows no strong rush to buy or sell.
Volatility offers chances but brings risk too.

Should You Buy Nvidia Stock Today?

With Nvidia’s massive past gains and current price swings, choosing to buy is not simple. Consider these points:

Why Buy Now

Company leads in GPUs, AI, and data centers, areas expected to grow.
Growing earnings and market share keep expanding.
New products and tech keep Nvidia ahead.
AI and machine learning trends support long-term growth.

AI Supercomputers at Nvidia Headquarters

Why Be Careful

Price ups and downs may continue or worsen.
Mixed expert views, some warn of drops.
Broader economy still uncertain, weighing on tech stocks.
Fear & Greed Index shows nerves in the market.

Final Thoughts: Be Patient and Do Your Homework

Nvidia’s 1500% rise tells a strong story of tech success. But recent price drops show the stock is going through a rough patch. Before buying Nvidia stock, weigh its strong future chances against current risks and market jitters. Check technical prices, study company news, and match your choices to your comfort with risk. This way, you make smarter decisions.

Key Points

Stock 5-year 1500% gain was huge but doesn’t ensure more gains.
The current price is near $113, showing volatility and risk.
Watch support ($105) and resistance ($120-$125) levels closely.
Social mood leans toward caution and fear.
Compare strong tech base with market risks before buying.

Ai Tech

Ask AI Anything: ChatGPT Reveals Most Popular Businesses You Can Start From Home 2025

Published

1 month ago

May 6, 2025

Pinkesh Jain

The rise of AI tools like ChatGPT is changing how students and young entrepreneurs start businesses from home. ChatGPT lets you build low-cost, scalable businesses without needing big teams or offices. As 2024 moves into 2025, Chat GPT-powered home businesses are a smart way to tap into new trends and make money.

ChatGPT – Wikipedia

Why Chat GPT Works Great for Home Businesses

Chat GPT offers affordable plans, usually under $100 a month. This makes it easy for one person or small groups to automate many tasks. You can start a business from your room and still compete with big companies. Here’s what Chat GPT can do for your home business:

Create content fast
Handle customer questions with AI chatbots
Help with market research and quick testing
Translate and localize content
Automate marketing with smart tools

Thanks to ChatGPT, many new businesses use a mix of human effort and AI help. ChatGPT handles repetitive work, like writing drafts or answering common questions. You can focus on bigger tasks like planning and finding clients.

Introducing ChatGPT | OpenAI

Top ChatGPT-Powered Home Business Ideas for 2025

1. AI Content Agencies

Writing is still very important online. Starting an AI content agency from home is easy with Chat GPT. You can offer:

Blog posts
Social media captions
Product descriptions
SEO-friendly content

Chat GPT creates content quickly and keeps quality high. This style appeals to startups and well-known brands.

2. Niche Translation Services

Translation demand keeps growing. Focusing on rare language pairs (like Swahili to Korean) can set you apart. Chat GPT helps provide better and smarter translations than usual tools. This service works well for international trade, legal work, and content localization.

3. AI Chatbots for Customer Service

Customer support takes time but AI chatbots make it easier. Chat GPT-powered bots can answer FAQs, fix problems, and guide buyers all from your home setup.

4. Virtual Interview Help and Career Coaching

Chat GPT’s chat skills work well with video calls on Zoom. You can start a coaching business offering:

Interview prep
Resume help
Career advice

Use Chat GPT to create custom feedback and simulate interview questions.

5. Micro-SaaS Applications

If you like coding, build small Chat GPT-powered apps for specific needs:

Resume tools
Email marketing generators
Lead generation tools

These apps help businesses improve work and stay productive. You can run this from home easily.

New ChatGPT Business Trends from Industry Experts

Videos on YouTube in 2025 show how ChatGPT powers new online income ideas. Some creators earn $50,000 a month by using AI to automate lead generation and write eCommerce product descriptions. AI handles boring tasks so creators can focus on growing their brand. Watch this insightful video guide to learn how small businesses can effectively utilize ChatGPT in 2025, boosting operations and avoiding common AI pitfalls: The Ultimate Guide To Blow Up Your Business With Chat GPT (2025)
This video explores practical ways to implement Chat GPT for business growth and innovation. Another popular video showcases innovative business ideas made possible by the newest Chat GPT features, perfect for beginners looking to launch AI-driven startups: The New ChatGPT Just Made 13 Insane Business Ideas Possible
Highlights eight beginner-friendly AI business ideas you can start immediately. Industry blogs further support these trends. For example, “6 Ways Chat GPT is Driving Business Innovation in 2025” explains how Chat GPT helps save time, cut costs, and increase productivity through smarter collaboration and customized customer support. This helps small businesses stay competitive: 6 Ways ChatGPT is Driving Business Innovation in 2025 Similarly, a comprehensive list of 17 tested AI prompts helps entrepreneurs avoid pitfalls in business ideation and planning: 17 ChatGPT prompts you can use for starting a business in 2025 For fresh business ideas leveraging Chat GPT’s capability, this post outlines opportunities such as translation services, SEO agencies, and social media management to help you get started: ChatGPT Business Ideas to Start in 2025

Best Ways to Mix Human Skills and ChatGPT

Experts say it’s best to use both humans and AI together. Fully automated work can have errors or feel low quality. Try this:

Use ChatGPT for the first draft or info gathering
Edit and check facts yourself
Change AI results to fit your audience

This plan uses both AI speed and human creativity. It helps keep clients happy and grow your business.

Where to Sell Your ChatGPT Services

Freelance sites like Upwork and Fiverr are great places to find clients. Many people look for:

Content creation
SEO help
Translation services

Also, real-time translation apps and marketing tools powered by Chat GPT get talked about in online forums and groups. These places indicate high demand.

Final Thoughts: Starting a ChatGPT Business from Home in 2025

ChatGPT is a powerful tool for home-based businesses. Whether you want to start a content agency, translation service, or coaching, ChatGPT lowers the cost and helps you grow fast. Remember these tips:

Pick niche markets with lots of demand but less competition
Combine human skills with ChatGPT to keep high quality
Use platforms like Upwork and Fiverr to get clients
Try new AI models for SaaS and chatbots
Keep learning as AI changes

With ChatGPT and your hard work, you can build a strong home business in 2025 and beyond.

ChatGPT expands reach as new features improve business capabilities.

Ai Tech

Agentic AI Reshaping Enterprise Software Pricing, Amazing Business Models 2025

Published

1 month ago

May 6, 2025

Pinkesh Jain

Agentic AI is changing how enterprises pay for software in 2025. Traditional pricing focused on the number of human users, but now AI agents are doing many tasks on their own. This shift means companies need new pricing methods that fit better with AI-driven work. Enterprise software pricing that once charged per user seat is moving toward agent-centric and usage-based pricing models.

From Per-Seat Licensing to Agentic AI Pricing

Nearly all enterprise software once priced licenses by users. Companies paid based on how many people used the tool. Now, AI-powered agents can take over entire workflows without human help. Girish Mathrubootham, founder of Freshworks, points out that AI agents are more productive than people. So, old pricing models based on user seats no longer make sense. New pricing methods focus on:

API-Driven Billing: Charging companies for every API call or workflow an AI agent runs. For example, $ per workflow completed.
Outcome-Based Pricing: Paying fees tied directly to results, like $ per customer ticket solved or $ per lead converted.
Agent Count + Complexity: Pricing based on how many AI agents work and how complex their tasks are, used by companies such as Icertis.

Big names like Salesforce and Microsoft are testing these models. Salesforce charges about $2 per conversation, while Microsoft prices AI services around $4 for each hour an agent is active.

Illustration of Agentic AI workflows showcasing autonomous task execution and API-driven automation.

New Pricing Ideas with Agentic AI

Companies are trying different ways to set prices that balance budget control with flexibility.

AI Credits and Compute Units

Some companies sell AI credits or compute units to track AI use. For example, Devin sells credits at $2.25 each. Customers buy credits in pools, and their AI agents use them as they work. This creates clear, easy-to-understand billing.

Hybrid Pricing Models

A hybrid price mixes a flat monthly fee with extra charges based on AI use. The base fee covers basic software access. Then, extra fees cover additional API calls or agent activity once the free amount runs out.

Value-Based Pricing

Value-based pricing focuses on the business benefits delivered. Monetizely says this system avoids losing money that happens with fixed subscription fees. It links vendor income directly to how well the AI helps their customers succeed. You can learn more on pricing frameworks in this detailed Monetizely guide to AI pricing, which advocates for outcome-aligned monetization beyond traditional subscription models.

Comparing Agentic AI Pricing Models in 2025

MODEL TYPE	EXAMPLE	ADVANTAGES
Usage-Based	$0.99 per resolved conversation (Intercom)	Scales well, links cost to results
Outcome-Based	$X per converted lead or sale	Shares risk, pays for real results
Hybrid	Base fee + $/API call	Stable payments with flexibility

Reports from AIMultiple and Economic Times Tech emphasize these models help companies adopt AI faster and match costs to value better. The research article From Traditional SaaS-Pricing to AI Agent Seats breaks down examples like Salesforce charging per conversation, and Microsoft Copilot pricing by compute hours.

How Agentic AI Pricing Changes Business Models

This pricing change is not just about money. It shifts how businesses buy and use software and how vendors sell it.

Good for Businesses

Saves Money: Companies say they cut costs by 30-50% when AI agents replace large teams.
Pay for Results: Paying for completed tasks or leads means money goes where results happen.
Flexible: Usage-based plans let businesses adjust AI agent use according to needs.

Things Vendors Should Know

Balance Income and Flexibility: Hybrid pricing keeps steady income but lets vendors earn more when customers use more AI.
Clear Rules Needed: Strong rules keep costs from getting out of control when lots of AI agents work.
Different Packages: Vendors offer tiered access with limits on API use, agent credits, and workflow complexity for different customer needs.

A detailed Economic Times article highlights how autonomous AI agents are disrupting traditional SaaS pricing in India, shifting from human-centric to bot-driven pricing strategies. This indicates a global impact on adoption and vendor approaches.

What People Are Saying About Agentic AI Pricing

Agentic AI pricing is a growing topic online, though still quite new.

On YouTube, channels like AI Business School discuss AI pricing trends including agent-based models.
LinkedIn has talks about “digital seats” where companies pay by agent instead of user.
Twitter/X debates focus on fairness and transparency of outcome-based fees.
On Reddit, users share stories about saving money and getting better returns with Agentic AI.

Watch: Understanding Agentic AI and Its Business Impact

For a clear breakdown of how Agentic AI redefines workflows and pricing, watch this introductory video:

Explore how autonomous AI agents are transforming enterprise workflows and pricing models in this concise video.(Note: Replace the placeholder video link with an actual suitable video for live publishing.)

What’s Next for Agentic AI Pricing?

Agent credits, tiered access, and pricing linked to outcomes will likely become common. Both software buyers and sellers need to stay flexible and open to change. Agentic AI will not just change how workflows get done but also how software sells and gets paid for. The companies that match pricing to the value AI agents provide will lead in the coming years. Understanding Agentic AI pricing and new business models is key for anyone working with enterprise software today.