These AIs are sophisticated tools that respond to prompts rather than act independently, which is why a new term has emerged in the artificial intelligence development community: “Agentic AI.” It’s stipulated that Agentic AI can undertake the challenges of a growing competitive business landscape and revolutionize how companies operate. But what is it? And why should business leaders be interested in this specific AI advancement? All of it will be uncovered in this blog to demystify the idea of Agentic AI, incidentally, whose expected market valuation by the end of 2033 will hit USD 367.68 Billion.
What is Agentic AI?
Agentic AI attributes to an Artificial intelligence system created to operate autonomously, making data-driven decisions and taking actions to achieve preferred business goals with minimal human intervention.
There are several components of Agentic AI, and they are as follows;
- Reinforcement Learning: Authorize the AI to acquire knowledge from its interactions with the environment.
- Multi-Agent System: Allows competition and coordination between multiple AI agents.
- Goal-Oriented Planning: Assist the AI in mapping out and executing plans to attain the desired goals of the organization.
- Adaptive Decision-Making: Permit the AI to adjust its strategies based on changing circumstances and new information.
Beyond these Agentic AI component, there is an Agentic AI foundational element, “AI Agent.” It seamlessly integrates with specialized agents, such as Agent Assist, which is proficient in handling day-to-day tasks and fostering collaboration. Other agents are dedicated to upholding stringent compliance frameworks, ensuring that all actions are in line with the most rigorous standards.
The true power of Agentic AI lies in its unique structure, which integrates and coordinates both human-driven and AI-based agents. This ensures that AI agents remain aligned with the cohesive AI strategy, amplifying the growth of the entire business.
These agents can be categorized into four types, each with a significance different from the others but contributing to superior outcomes.
- Generative Information Retrieval Agents: Agents responsible for knowledge serving for less-regulated topics/environments.
- Prescriptive Knowledge Agent: Agents for knowledge serving highly regulated topics/environments.
- Dynamic Workflow Agents: Agents that can familiarise to new data and take decisions to optimize operations.
- User Assistant Agents: User AI assistant can help individual users directly with their day-to-day tasks.
These fundamentals highlight that agentic AI goes beyond simple automation, as it is capable of handling dynamic, complex situations and making nuanced decisions. To further understand how the functionality of Agentic AI differs from traditional AI and Generative AI, go through the table below.
Most Impactful Agentic AI Use Cases in an Enterprise:
The Autonomous nature of agentic AI can learn from its environment, reason, and adapt. It even breaks down problems into sub-problems to simplify the process of resolving issues and attaining certain goals. These founding principles, based on which Agentic AI is developed, are reshaping how businesses approach automation.
Agentic AI denotes a significant growth in artificial intelligence, offering a new level of autonomy that is already in use. Below, we will take you through those use case scenarios with an enterprise that will immensely benefit from deploying Agentic AI systems.
- 1. HR Departments: The human resource department is often burdened with numerous tasks, from work allocation to payroll, onboarding, benefits management, etc. Agentic AI can be an ally for handling complex workflows, automating administrative subtasks, and even providing guidance for other HR operations, freeing up HR’s time to focus on work that requires human intelligence, potentially leading to better resource management. After all, 80% of HR specialists believe HR technologies enhance their professional relationship with the organization.
- 2. IT Teams: Considering that 90% of the world’s data is generated from 2019 to the present, it’s no wonder IT teams have to take care of a staggering amount of work. This is exactly why agentic AI is perfect in this scenario: it can look after common repetitive work. Being autonomous can help by providing reminders, searching through the system for diagnosing issues, provide data security and lastly, analyze and take action based on data-driven awareness. This enormous support not only frees up IT staff to focus on complex tasks but also makes them feel more supported and less overwhelmed.
- 3. Customer Service Team: When customer support is combined with agentic AI, organizations have a conversational assistant for phone calls and web chats. Agentic AI is empowered to understand escalating situations and guide the person on the other side of the chat/call with the right solution. This empowerment not only improves the resolution time of large volumes of customer enquiries across channels but also makes the customer service team feel more capable and efficient. As per statistics, 56% B2B customer service specialists value AI automation, another good reason to consider Agentic AI integration.
- 4. Healthcare Diagnosis: The healthcare sector is already understaffed, and it is estimated by 2026, there will be a critical shortage of 2 million healthcare workers. One way of dealing with this concern is to reduce the workload of every healthcare worker. For example, before treating a patient, doctors have to do an extensive search of medical history and patient symptoms and analyze the diagnostic results. When agentic AI takes over the process, the technology will transform the future of healthcare by highlighting the health risks, explaining the logic behind the suggestion, and also providing preventative measures, reducing some of the burden on the healthcare worker.
- 5. Fraud Monitoring in Finance: In the year 2023, customers have lost $10 billion to fraud challenges, which is a 14% increase in the fraud amount to the previous year. The threats are increasing every year, and so is the number of transactions creating a demand for a top-notch system to identify fraudulent activity. Enters Agentic AI, with it, the accounts can be constantly monitored, reducing false positives and fraud losses, as its data-driven insights can identify patterns of anomalous transactions and flag them.
- 6. Content Creation: Agentic AI, with its ability to autonomously create, edit, and publish content, is a powerful tool for businesses. These AI advancements not only assist human writers but also produce content independently and personalize writing styles for specific target audiences. Content is of enormous significance to 90% of all businesses as it helps educate their audience, generate leads, create a brand image, and improve SEO. By leveraging Agentic AI, businesses can ensure that their content is not only engaging but also highly relevant to their target audience, enhancing the overall user experience.
These were only some of the instances of Agentic AI’s use cases. Nonetheless, several other areas of business can benefit from this recent AI development, such as operation, supply chain, marketing, sales and more.
Go through the table below to check out the real-world example of Agentic AI.
How Will Leveraging Agentic AI Transform Your Business?
Considering that nearly 48% of companies are already adopting agentic AI solutions, it is a good time to learn how using Agentic AI will transform your organization for good.
1. Upgraded Complex Task Automation:
Agentic AI is proficient in automating complicated procedures, as it divides difficult jobs into smaller manageable steps. Human teams are freed from the burden of keeping constant oversight. Moreover, it’s predicted that in the upcoming four years, 15% of day-to-day work will be autonomous with the help of agentic AI, thus helping organizations increase productivity and operational effectiveness. Additionally, Agentic AI, being capable of following pre-set guidelines, offers consistency in task execution. Helping organizations to maintain operational procedures with high standards of quality.
2. Scalability for Future Growth:
Agentic AI comprises modular architecture, making it easier for organizations to add new features and manage major work overload without many changes in the existing process. For example, Agentic AI can modify algorithms by taking into account the organization’s diversification (entry into new markets or different types of product offerings), enabling the organization to focus on expansion rather than worry about outgrowing the organization’s IT infrastructure.
Agentic AI’s ability to scale creates room for organizations’ data to be used effectively, which is why, by 2028, 33% of enterprise software applications will include Agentic AI.
3. Flexibility in the Face of Changing Situation:
The versatility of Agentic AI is one of the best qualities, helping this particular AI development to stay useful and relevant. Agentic AI is well-built with machine learning capabilities, enabling the processing of data in real real-time. Additionally, Agentic AI can automatically modify particular queries and prioritize them, update the knowledge base to provide the most recent information, and modify its response tactics. Hence, agentic AI is proactive and reactive at the same time, continuously optimizing operations based on circumstances.
Possible Challenges Associated with Agentic AI Adoption?
The contribution of Agentic AI is significant, but it also demands us to make a meticulous effort to learn about the potential risks of transformative technology. Mostly because the Agentic AI is autonomous, ascertaining an ethical and responsible use of the technology is paramount. So here are three areas of keen concern.
- Autonomy: The autonomous nature of Agentic AI should make organizations consider the implications of granting decision-making authority to machines. It is always best to balance the autonomy of Agentic AI with human oversight to prevent the unintended consequences of AI, which doesn’t align with ethical and legal standards.
- Transparency: The complex reasoning process of Agentic AI won’t always be understandable to human beings. The lack of transparency in the process will raise concerns about the reliability and fairness of AI-driven outcomes, eroding users’ trust in Agentic AI.
- Security: When Agentic AI is integrated with enterprises’ sensitive data, the security concern is valid. As autonomous mechanisms drive Agentic AI, the system becomes more interconnected, and the risk of cyberattacks and security breaches increases.
What Best Practices Organizations Should Follow to Integrate Agentic AI?
According to Forbes advisors, 47% of organizations use AI as a digital personal assistant, 51% use AI for fraud management and cybersecurity, and 56% leverage AI to improve business operations. Therefore, the rise of Agentic AI will be embraced warm-heartedly. Only the organization needs to follow the best practices while implementing it.
- Governance: Define ethical guidelines for AI use and the roles and responsibilities of stakeholders in the deployment of Agentic AI systems. Ensuring the complete process is in alignment with relevant regulations.
- Security Compliance: Organizations should have clear guidelines regarding data usage; it will mitigate the risk while preserving ethical standards. Furthermore, the organization should also inculcate security measures such as access control, regular vulnerability assessment, etc., to maintain the integrity of agentic AI systems.
- Testing: Conduct vigorous and comprehensive testing for both expected and unexpected scenarios to address unintended consequences and potential flaws before deploying the system for usage.
- Continuous Monitoring: The Agentic AI systems should be continuously monitored and updated to elevate their effectiveness. The process of continuous monitoring should be supplemented with user feedback, performance metrics, and feedback loops. Empowering continuous learning and improvement process maximizing the ROI of the agentic AI investments.
What Does the Future Look Like for Agentic AI?
Here are two major areas that ought to be considered when the future of Agentic AI is discussed, and they are as follows.
1. Improved Advancement in Machine Learning:
The advancement of machine learning will power the capability of agentic AI. As it will enhance the computational and algorithmic capacity of Agentic AI.
2. AI and Internet of Things (IoT) Integration:
The coming together of the Internet of Things (IoT) and AI will have a significant impact on the evolution of Agentic AI. This particular advancement will enable businesses to leverage Agentic AI workflows, process data from numerous interconnected devices, and enable real-time decision-making.
Wrapping Up
While challenges remain, the potential benefits of Agentic AI are substantial. The estimated valuation of the Agentic AI market highlights the prominence of this technology in the business world. Moving forward, the businesses that triumph in business growth are the ones that integrate Agentic AI into their operations. At the same time, they maintain a balance between human insight and technological advancement. Hence, by fostering continuous learning and adaptation processes, companies can leverage the benefits of Agentic AI to unlock worthy business output.
The adaptability of Agentic AI is a key factor in its success. Therefore, if you are offering agentic AI products, promote them to numerous industries and expand your business outreach.
