Agentic AI is an advanced form of artificial intelligence (AI) that uses autonomous AI “agents” to carry out complex tasks without direct human supervision.
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Artificial intelligence (AI) is defined as computers or machines that mimic how the human brain works to plan, reason, make decisions, and learn from experience.
Agentic AI is an emerging form of AI that uses machine learning (ML) algorithms, large language models (LLMs), natural language processing (NLP), and other advanced technologies to create “AI agents”—autonomous, self-directed AI systems that can accomplish complex tasks without needing constant human input or direction.
Agentic AI versus traditional AI
While traditional AI models can generally only follow prompts or other instructions given to them by a human user, agentic AI is fully autonomous. This enables it to make decisions, solve difficult problems, work with other AI agents, carry out tasks, and learn from past interactions without being prompted and with little to no human oversight or supervision.
Agentic AI can also simulate human behaviors and personality traits much more closely than traditional AI. This lets it interact with people in a human-like way, whether in automated customer-service chatbots, self-driving cars, or smart assistants like Amazon’s Alexa, Google’s Assistant, and Apple’s Siri.
As the technology continues to evolve and become more widespread, agentic AI has the potential to revolutionize entire industries ranging from finance, manufacturing, and healthcare to customer service, software programming, and cybersecurity.
How does agentic AI work?
Most agentic AI systems follow a clear five-step process:
- Perception—the agentic AI uses sensors, open and proprietary databases, application programming interfaces (APIs), and other sources of information to gather vast amounts of data and learn about its environment.
- Reasoning—next, it analyzes the data to identify patterns, understand what it’s being asked to do, and plan the best course of action.
- Making decisions—based on those patterns, the agentic AI uses algorithms to make decisions, predict possible outcomes, and create strategies to achieve its goals.
- Taking action—the system takes a series of actions to implement its strategies and carry out tasks, such as generating text or responding to a customer inquiry.
- Learning from experience—lastly, the agentic AI evaluates how well it achieved its goals to improve its efficiency and accuracy in the future.
What are the benefits of agentic AI?
Agentic AI offers a number of benefits over traditional AI. These include:
- An autonomous and proactive approach to carrying out tasks
- Enhanced speed, accuracy, and flexibility
- Greater capacity to evolve, adapt, and learn from experience
- Ability to personalize behaviors and mimic human personality traits
- Increased productivity by freeing up human teams to focus on more strategic tasks
- Long-term savings of time and money through reduced operational costs and greater efficiency
What are the risks and challenges of using agentic AI?
As the use of agentic AI becomes more widespread, there are several key issues and challenges organizations must keep in mind.
For example, the data used to build agentic AI models can include gaps, inaccuracies, or biases that could influence how the AI reacts or limit its effectiveness. There is also a need to safeguard private, sensitive, and confidential information when developing or using AI to ensure compliance with all laws and regulations, including the General Data Protection Regulation (GDPR).
AI agents with too few safeguards can go overboard carrying out their tasks, with unintended consequences. For example, a stock-trading AI agent might use risky or illegal practices to maximize profits for clients, making decisions without human intervention. Because they operate autonomously, some AI agents can also repeat or self-reinforce errors in how they reason, plan, or interact with customers.
To address these challenges, organizations must make sure their use of agentic AI is open, ethical, and transparent. They need to give instructions that are clear, careful, and include as much context as possible. And they should make sure their AI security and AI cybersecurity measures are robust, proactive, and up to date.
Examples of real-world applications of agentic AI
Agentic AI is already being used in a variety of industries, including:
- Healthcare—AI agents monitor patient data and provide recommendations for different diagnoses and treatment options.
- Financial services—agentic AI bots analyze stock prices, provide recommendations to human traders, and carry out trades measured in fractions of a second.
- Customer service—agentic AI chatbots respond to inquiries, resolve client complaints, and create a smoother and more efficient customer experience.
- Self-driving vehicles—agentic AI uses GPS and other sources of “live” information to monitor traffic conditions, avoid hazards, and devise the safest and most efficient routes.
- Supply chain management—autonomous AI agents automate supply chain and manufacturing processes, track inventories, and manage suppliers.
- Cybersecurity—AI agents continuously scan for vulnerabilities, automate threat detection and response, and defend against cyberattacks in real time.
What is the future of agentic AI?
As agentic AI continues to become more intelligent, adaptive, and autonomous, it will almost certainly become an even more ubiquitous part of our daily lives than it is today.
Innovations in the ability of agentic AI to reason, learn, and integrate seamlessly with other technologies will doubtless speed up its adoption across a broader range of industries and make individuals and businesses more efficient and productive.
Agentic AI could also lead to a profound shift in the workforce, taking on routine tasks previously handled by human beings while humans adopt new roles that require greater creativity, critical thinking skills, and human-machine collaboration.
How can I get started with agentic AI?
Organizations that want to use agentic AI should begin by identifying their core goals and prioritizing investment in AI applications that can help them achieve their objectives as efficiently as possible.
They should look for agentic AI solutions that can adapt, evolve, and scale to take advantage of the latest innovations, including cloud-based platforms and open-source frameworks. They should also offer ongoing support and training to help their employees work more effectively with AI agents and take full advantage of all the benefits agentic AI has to offer.
Where can I get help with agentic AI for cybersecurity?
The cybersecurity platform Trend Vision One™ is a complete AI security solution that uses advanced agentic AI technology to stay on top of the latest cyber threats and stop even the most sophisticated cyberattacks before they occur.
Incorporating the full AI capabilities of Trend Cybertron—the world's first truly proactive cybersecurity AI—Trend Vision One can transform an organization’s security posture from reactive to proactive, improve the speed and accuracy of their threat detection and response, and dramatically enhance the efficiency and effectiveness of their cybersecurity defenses.