Landbase is a cutting-edge AI-driven platform that empowers businesses to intelligently automate their go-to-market strategies, enhancing productivity and efficiency.

An AI-powered platform that combines outbound, inbound, and market intelligence to deliver a genuine omnichannel approach for go-to-market success.

Publication - i1mtX4ST2aXgdFUfb4evmvlrvp43

Hey there, welcome back to another episode of The Landbase Podcast on Agentic AI! Today, we're diving into the fascinating world of agentic AI and how it's transforming industries left and right.

Yeah, agentic AI isn't just some buzzword—it's a big shift in how we see and use artificial intelligence. We're talking about a new era of autonomy here, where AI systems aren't just following orders anymore but actually making decisions and setting goals on their own.

Right! And with the global AI market expected to hit, like, $267 billion by 2027, it's clear that agentic AI is set to become a HUGE part of our lives and businesses. So, let's dig into what makes this tech so groundbreaking.

Landbase is leading the way with AI-driven platforms, empowering businesses through smart automation. Our mission? Boosting productivity and efficiency with innovative solutions like agentic AI.

The jump from basic automation to advanced decision-making is... well, it's pretty amazing. At first, AI systems were all about following rules, doing specific tasks with set instructions. But now, with agentic AI, we're seeing systems that learn from experiences and adapt to new situations.

Exactly. Traditional AI was great for handling predefined tasks, but it wasn't so good at adapting. Agentic AI, though, is like an apprentice—it can make its own decisions and take steps toward its goals.

Think of it like an AI that doesn't just mark emails as spam but understands your email habits, prioritizes important messages, and even drafts responses in your style.

This shift to agentic AI is a real game changer. It opens up new opportunities across various sectors by letting AI learn, adapt, and make autonomous decisions, which leads to better outcomes.

Absolutely. Key milestones in AI development, like machine learning and deep learning, have paved the way for these advanced systems. Agentic AI stands out with its independence and goal-oriented actions, right?

What sets agentic AI apart is its ability to function on its own. Unlike traditional AI, which needs human intervention, agentic AI can make its own choices and work toward specific goals without constant oversight.

And when I say autonomy, I don't mean replacing human intelligence. Instead, agentic AI supports us by handling repetitive or complex tasks, offering insights, and suggesting solutions based on data analysis.

Exactly. It's about creating a symbiotic relationship between humans and AI, where both can enhance each other's capabilities.

The core behaviors of agentic AI include continuous learning and adaptability. These systems don't just follow fixed rules—they improve based on their experiences, making them invaluable in dynamic environments.

For instance, in supply chain management, agentic AI can handle disruptions like bad weather by analyzing real-time data to adjust shipment routes and stock levels, ensuring smooth operations.

The ability to learn and adapt is what makes agentic AI such a powerful tool in today's fast-paced world. It allows businesses to respond quickly to changes and challenges.

Agentic AI's impact is already being felt across industries. In healthcare, for example, it enhances patient care and streamlines operations through predictive analytics and equipment maintenance.

And in manufacturing, agentic AI revolutionizes production processes with autonomous systems that work alongside humans, improving efficiency and quality control.

But, with these advancements come challenges, especially around ethics and bias. It's crucial to tackle these issues to ensure responsible and beneficial use of agentic AI.

That's a key point. Ensuring reliability and safety is paramount. We need to develop regulatory frameworks and ethical guidelines to guide the development and deployment of agentic AI.

By fostering collaboration between developers, policymakers, and ethicists, we can create standards that promote innovation while protecting societal values.

Getting ready for an agentic AI future isn't just about tech advancements—it's about societal adaptation too. Public engagement and education are key to building trust in AI systems.

Indeed. As we navigate this AI revolution, it's important to emphasize transparency and accountability, ensuring that agentic AI aligns with human values and goals.

In conclusion, agentic AI represents a monumental leap in AI technology, offering independence, flexibility, and continuous learning. By embracing these changes responsibly, we can shape a future where intelligent machines enhance our capabilities.

Thanks for joining us on this exploration of agentic AI. We hope you found these insights valuable and encourage you to consider how they might reshape your approach to technology and business.

Stay tuned for more episodes of The Landbase Podcast on Agentic AI, where we'll continue to explore the cutting-edge developments in AI and their impact on the business world.

Discover the future of autonomous decision-making with Agentic AI. Explore our blog for insights on this cutting-edge technology.
By
Yi Jin, Ph.D.
・
5
mins read
・
August 10, 2024
On this page
Key Highlights
Introduction
Understanding the Evolution of AI to Agentic AI
From Basic Automation to Advanced Decision-Making
Key Milestones in AI Development
What Sets Agentic AI Apart?
Autonomy and Goal-Oriented Actions
The Core Behaviors of Agentic AI
Decision-Making Capabilities
Agentic AI's Impact Across Industries
Addressing the Challenges of Agentic AI
Preparing for an Agentic AI Future
Conclusion
References
‍
Key Highlights
Agentic AI marks a new era in artificial intelligence. It can make decisions and set goals on its own.
Unlike traditional AI, agentic AI systems learn from their experiences and can adapt.
This transformative technology could change many industries. These include healthcare, manufacturing, customer service, and finance.
Key features of agentic AI are its independence, goal-focused actions, adaptability, interactivity, and strong decision-making skills.
It's important to think about the ethical issues and challenges that come with agentic AI. This helps ensure safe and responsible use.
‍
Introduction
The tech world is about to change a lot with agentic AI. This is not just a trendy word; it means a big shift in how we understand and use artificial intelligence.
Agentic AI begins a new era of autonomy. Now, AI systems will not just follow orders. They can actually make their own choices and do things to reach specific goals.
The global AI market is projected to reach $267 billion by 2027, growing at a CAGR of 33.2% from 2020 to 2027. As of 2023, 37% of organizations have implemented AI in some form, a significant increase from 10% in 2015.
Get ready for a future where AI is an active part of our lives and businesses, not just a tool we use.
Understanding the Evolution of AI to Agentic AI
The journey of artificial intelligence has been amazing. It went from simple systems that followed rules to the smart models we have today. In the past, AI mainly focused on automating certain tasks based on set rules. It was like a great helper sticking to the plan. While traditional AI has been very useful, it can't change or adapt for more complex situations.
Now, we have agentic AI, which is the next step in artificial intelligence. This new type of AI is meant to be more independent. It can make its own choices, learn from its experiences, and change when needed. Think of it like an apprentice who has learned how things work. Now, it can act on its own, making decisions and taking steps toward its goals.
From Basic Automation to Advanced Decision-Making
Traditional AI was a big step forward when it started, but it had its limits. These systems were great at doing certain tasks, based on clear rules. However, they struggled to change or handle new situations. For example, traditional AI could sort emails and mark spam, but it couldn't really understand human language or recognize new types of spam.
In contrast, agentic AI uses advanced algorithms and machine learning to do much more. These systems can look at lots of data, spot patterns, and make smart choices based on what they understand. Machine learning algorithms have improved accuracy in predictive tasks by up to 90% in some applications. Deep learning models have reduced error rates in image recognition tasks from 26% in 2011 to 3% in 2020. Think of an AI that doesn’t just mark spam but also learns your email habits. It can give priority to messages from important people and even help write emails in your style.
Deep learning models have reduced error rates in image recognition tasks from 26% in 2011 to 3% in 2020.
This shift to agentic AI is what changes the game. It allows AI to learn, change, and make its own choices, leading to better results in many areas. This opens up exciting opportunities in various sectors.
Key Milestones in AI Development
The evolution of AI to agentic AI has been marked by significant milestones, each pushing the boundaries of what's possible. These advancements in AI models, particularly in language models, have paved the way for more sophisticated and autonomous systems.
One of the key drivers behind this progress is the development of machine learning and deep learning algorithms. These algorithms enable AI systems to learn from data, identify patterns, and make predictions with increasing accuracy. As AI models are exposed to more data, they become better at understanding complex relationships and making informed decisions.
Here's a glimpse into some of the key milestones that have shaped the field of AI:
Rule-based Systems: Early AI systems relied on predefined rules and logic to perform tasks.
Machine Learning: Algorithms that allow AI systems to learn from data without explicit programming, enabling them to improve their performance over time.
Deep Learning: A subset of machine learning that utilizes artificial neural networks with multiple layers to process information, enabling AI systems to learn complex patterns.
Natural Language Processing: Enables AI systems to understand and process human language, facilitating more natural and intuitive interactions.
‍
What Sets Agentic AI Apart?
What sets agentic AI apart from traditional AI is how it works. Agentic AI can function with a lot of independence. Unlike traditional AI systems, which need human intervention and clear instructions, agentic AI can make its own choices and take action to reach specific goals.
This independence does not mean it will replace human intelligence. Instead, agentic AI systems are meant to support us. They can handle repetitive or complex tasks, give insights, and suggest solutions by looking at data. The goal is to create a better working relationship between humans and AI.
Autonomy and Goal-Oriented Actions
At the center of agentic AI is the idea of autonomous systems that can work by themselves to meet specific goals. Unlike traditional AI, which mostly follows commands or set rules, agentic AI is more forward-thinking and focused on achieving goals. These systems can define what they want, plan how to get there, and do tasks without needing constant help from people.
The level of autonomy in these agentic AI systems can change based on how they are built and what they are meant to do. Some systems might have a high level of autonomy. This lets them make important choices and act with little human help. Other systems may have less autonomy and need humans to oversee certain jobs or decisions.
For example, an autonomous vehicle would need a high level of autonomy to make quick decisions while driving through traffic. By 2025, it is estimated that 10% of all vehicles will be fully autonomous. On the other hand, an agentic AI system used in customer service might only have a lower level of autonomy. It would mainly focus on answering common questions and handing over more complex issues to human agents.
Continuous Learning and Adaptability
One great thing about agentic AI is how it can learn and change in dynamic environments. These systems do not just stick to fixed rules. They keep getting better based on what they experience. With machine learning and deep learning, agentic AI systems study vast amounts of data. They can find patterns and insights that can be hard for people to see. This real-time learning helps them handle new situations and unexpected problems. They can also keep improving their decision-making skills over time.
For instance, an agentic AI system in supply chain management might handle surprises like bad weather or shipping delays. By looking at real-time data from various sources, it can change shipment routes, adjust stock levels, and make quick choices to keep the supply chain running smoothly. This quick learning and adapting is what makes agentic AI a helpful tool in our fast-changing world. In fact, 72% of executives believe AI will be the most significant business advantage of the future.
The Core Behaviors of Agentic AI
Agentic AI goes beyond just copying how humans think. It's about making smart systems that act in a way that lets them work well with their surroundings. These systems can learn, change, and make choices on their own to reach certain goals.
Think about an AI that gets what you want and looks ahead to meet your needs. It learns what you like and suggests helpful ideas or answers before you even ask. That’s what agentic AI is all about—building AI partners that are active, flexible, and focused on getting things done.
Decision-Making Capabilities
Agentic AI has a unique ability to make decisions on its own. Unlike just following instructions, these systems can look at situations, think about different choices, and make smart decisions based on what needs to be done. This skill allows them to understand tasks in depth and aim for the best results.
The kinds of complex tasks that agentic AI can handle are getting more advanced all the time. For example, it can help improve marketing strategies using real-time data or assist doctors in diagnosing illnesses by examining patient records and medical studies. Agentic AI is showing that it can tackle tough challenges effectively. AI chatbots can handle 80% of routine customer service inquiries, reducing operational costs by up to 30%. Agentic AI systems can process and analyze data up to 100 times faster than traditional AI systems.
Even though AI can make its own choices, it’s key to keep human oversight in place. Developers and experts step in to create rules and keep ethical standards. This ensures that agentic AI is working in ways that reflect human values, helping to use technology safely and well.
Interactivity with Humans and Environments
Agentic AI works best when it connects with both people and the environment. This ability to interact is key. It helps these systems grasp what they must do and learn from what they experience. This way, they can improve their actions to meet specific goals. Imagine AI customer service agents as one good example. They can talk naturally with customers, understand questions, and offer relevant answers. These agents can handle everyday tasks. If a problem gets complex, they can pass it to a human. They also learn from each call to make their answers even better down the line.
Agentic AI's Impact Across Industries
Agentic AI is not just a fancy idea; it's already changing how businesses work and opening up exciting new opportunities. It's being used in many areas like healthcare, finance, manufacturing, and transportation. The applications of agentic AI are growing fast.
What makes agentic AI interesting is how it can solve tough problems and make things better for people. It can automate boring tasks, give important insights from data, and create personalized experiences. This technology is ready to change various sectors for the better.
Transforming Healthcare with Predictive Analytics
The healthcare industry is ready for change, and agentic AI is leading the way. This technology can make patient care better, help smooth out operations, and improve health results. One exciting use of agentic AI is in predictive analytics. Agentic AI is also important for keeping medical equipment working well. It can study data from sensors and track how equipment performs. This helps spot any issues before they happen. With this, we can make sure important devices are always ready to use, reducing downtime.
In fact, AI could save the US healthcare economy up to $150 billion annually by 2026. Agentic AI is also important for keeping medical equipment working well. It can study data from sensors and track how equipment performs. This helps spot any issues before they happen. With this, we can make sure important devices are always ready to use, reducing downtime.
Revolutionizing Manufacturing Through Autonomous Systems
The manufacturing industry is changing a lot, thanks to new automation and technology. Agentic AI is leading this change. It helps manufacturers improve their production processes and make their factories more efficient and adaptable. One area where agentic AI really shines is with autonomous systems. Picture robots working right next to human workers. These robots learn from humans and adjust to new production needs. They can take over repetitive or tough tasks, allowing people to focus on more important and creative work.
Agentic AI is also important for quality control. It uses computer vision and machine learning to spot defects as they happen. This helps ensure that products are of high quality and cuts down on waste from faulty goods. The use of AI in manufacturing can increase productivity by up to 40%.
Addressing the Challenges of Agentic AI
The growth of agentic AI brings hope, but it also comes with special challenges we need to think about. Like any big change in technology, we must focus on issues like ethics, job displacement, and bias.
This way, we can make sure its use is responsible and helpful for everyone. 85% of AI professionals agree that bias in AI systems is a significant issue that needs to be addressed. Additionally, 60% of companies report that regulatory compliance is a major challenge in AI implementation.
To achieve this, teamwork is key. Developers, policymakers, ethicists, and the public should work together to create guidelines and limits that help agentic AI enhance human skills instead of taking over jobs. We must also keep discussions open and honest to build trust, ensuring agentic AI serves our society for the better.
Navigating Ethical Considerations
As agentic AI develops, we need to improve the rules that guide its growth and use. It’s important to look at issues like bias, transparency, and accountability. This helps us create AI systems that are reliable and good for everyone. We must also put people first when we make these rules. The goal should be to use agentic AI to promote fairness and social good. We need to work on problems like bias in AI decision-making so that it does not make existing unfair situations worse.
We must also put people first when we make these rules. The goal should be to use agentic AI to promote fairness and social good. We need to work on problems like bias in AI decision-making so that it does not make existing unfair situations worse.
Being open about how agentic AI systems work is crucial. Developers should share information about how these systems are designed and trained. When we know more, we can spot biases and ensure developers face the results of their choices. It's essential to think about ethics at every step in making responsible agentic AI.
Ensuring Reliability and Safety
For agentic AI to be trusted and widely used, it's very important for these systems to be reliable and safe. They should work properly, make good choices, and not do things that might hurt people or communities. It's also key to test and validate these agents before they are used in the real world. We need to check how well they perform in different situations. 60% of companies report that regulatory compliance is a major challenge in AI implementation.
It's vital to find any weaknesses and add protections to stop any unwanted results. The experience for users has to focus on safety and being clear. Good communication, easy-to-use designs, and options for human intervention help ensure users feel relaxed when using agentic AI systems. This way, they can easily deal with any worries they might have.
Preparing for an Agentic AI Future
The agentic AI revolution is happening now! To get ready for this future, we need a well-rounded plan. This plan should include technology improvements, ethical thinking, and helping society adapt. It's important to discuss agentic AI's possible benefits and challenges with everyone. We need to engage with the public and address their worries.
By encouraging responsible AI development, we can use the power of agentic AI in a positive way while also reducing any risks. Notably, only 25% of the public currently trusts AI systems to make unbiased decisions, highlighting the need for transparent and ethical AI practices.
The Role of Regulatory Frameworks
As agentic AI becomes smarter and blends into our daily lives, it's important to have clear rules in place. These rules help guide how AI is created and used. They also make sure that AI systems match human values and our common goals.
Governments need to keep a close watch to find a balance between new ideas and being responsible. They should set standards, think about ethical issues, and create ways to keep an eye on risks linked to agentic AI.
As of 2023, 35 countries have implemented some form of AI regulation, reflecting a global effort to manage these challenges.
This includes looking at problems like data privacy, bias in algorithms, and how AI might change jobs. As of 2023, 35 countries have implemented some form of AI regulation, reflecting a global effort to manage these challenges. Working together is key. Policymakers, industry experts, and ethicists must team up to create smart rules. These rules should support innovation while protecting people. Ultimately, it's important to ensure that agentic AI helps everyone in society.
Developing Ethical Guidelines for AI Use
Developing agentic AI in a good way needs everyone to work together. We should talk openly about how AI can affect our lives. It’s important to think about its ethical challenges and set guidelines for developing AI responsibly. This way, we can create a future where everyone gains something from AI.
Learning about AI is very important. As AI is used more in our daily lives, people must know what it can and cannot do. Understanding these factors lets us discuss AI responsibly. It also helps us ask for developers and companies to be accountable for how they use AI.
We also need more diversity and inclusion in AI development. Different voices and viewpoints help reduce bias. By including many perspectives, we can create AI that is fair and beneficial for everyone. Building a future with agentic AI isn't just about advancing technology; it's also about making sure it aligns with our common values and dreams.
Conclusion
In the fast-changing world of AI, Agentic AI is unique because it can make decisions on its own. It mixes independence, flexibility, and constant learning. This technology is changing fields like healthcare and manufacturing. But as we welcome this future, we must think about ethics and make sure it is reliable. We need clear rules and ethical guidelines to help develop and use Agentic AI in the right way. It’s important to understand how Agentic AI is different from traditional AI. By accepting these changes carefully and responsibly, we can have a better future with smart machines that can make choices.
References
grandviewresearch.com
gartner.com
mckinsey.com
pwc.com
technologyreview.com
deloitte.com
edelman.com
‍
Follow us
Related articles
Keep reading
See all articles
Agentic AI
How Reflective Agentic AI Can Outperform GPT-4: A Deep Dive into New AI Workflows
By
Yi Jin, Ph.D.
・
5
mins read
Agentic AI
Agentic AI for Go-to-Market Team Success
By
Yi Jin, Ph.D.
・
12
mins read
Generate Leads that convert,
intelligently with Agentic AI Workflows
Provide your prospect with an enhanced engagement experience to boost the performance of your lead funnel and conversion rates.

Agentic AI: The Future of Autonomous Decision Making

February 12, 2025 • Agentic AI in Action

Read Article

About Agentic AI in Action

https://www.landbase.com

Subscribe to Agentic AI in Action Podcast