Current AI systems largely depend on human-written algorithms to make data-driven decisions for large and small enterprises. With its deep learning models, even Generative AI models are largely simulating human-like decisions by processing massive data volumes.

As AI technology continues to evolve, we are beginning to expect advanced capabilities like autonomous decision-making from AI models. As the next-gen AI technology, Agentic AI is designed to function autonomously and achieve business goals without any human intervention. Agentic AI marks the transition from “automation” to “autonomy.”

Unlike traditional AI that is designed to provide feedback to humans, Agentic AI adopts a proactive approach by independently:

•    Evaluating the business need. 
•    Setting need-based goals.
•    Executing the necessary actions to achieve the defined goals.

What makes Agentic AI unique is this shift from a "reactive" to a "proactive" form of decision-making. Let's understand further.

The Role of Agentic AI in Modern Enterprises

Here’s how Agentic AI systems in modern enterprises can transform the following traditional AI capabilities:

1.    Predictive analytics

With the development of Agentic AI, enterprises can use predictive analytics with a more proactive approach to improve their decision-making process. By analyzing historical data from more data sources, Agentic AI models can accurately forecast business trends and opportunities. 

This enables business leaders to optimize their business strategies proactively using data-driven insights. For example, in the financial sector, Agentic AI systems can continuously monitor user behavior to detect fraud and avoid the consequences.

2.    Automated workflows

While traditional AI systems could automate specific business tasks or processes, Agentic AI can automate the entire enterprise workflow. Besides that, it can work with minimum human input, thus bringing more autonomy into workflow automation. Here are some of the additional capabilities of Agentic AI in enterprise workflows:

•    Critical reasoning and problem-solving: By analyzing real-time data, Agentic AI for enterprises makes smart decisions based on achievable outcomes.
•    Adaptability: Agentic AI systems are more adaptable to external change, thus updating their actions based on data inputs and business goals.

3.    Strategic planning

Besides autonomy, Agentic AI elevates strategic planning across enterprises by breaking down and simplifying complex tasks into smaller simpler tasks. For instance, in the manufacturing domain, Agentic AI can enhance maintenance planning by breaking it down into simpler functions like:

•    Predicting equipment failure using real-time data insights.
•    Automating routine maintenance work.
•    Improving utilization of manufacturing assets.

Next, let’s understand the core technologies that are powering Agentic AI.

Core Technologies and Tools Behind Agentic AI

An Agentic AI system is powered by multiple technologies at its core, including the following:

1.    Advanced capabilities with Large Language Models (LLMs)
Agentic AI leverages Large Language Models to enhance natural language understanding and generation capabilities. These models provide advanced text comprehension, enabling the AI to analyze vast amounts of unstructured data, generate human-like responses, and support applications such as virtual assistants, sentiment analysis, and content creation.

2.    Supporting libraries and frameworks
Agentic AI utilizes a host of self-learning frameworks that operate through trial and error. This means they are capable of redefining their strategies based on feedback from previous interactions. Agentic AI frameworks are mostly used in complex business functions like financial trading, which require dynamic strategies for the best results.

3.    Integration with existing systems
Depending on the specific business use case, Agentic AI systems are also seamlessly integrated with existing systems like CRM and customer service tools. This level of integration gives Agentic AI applications more intelligence to address complex business problems and automate decision-making.

Enterprise Use Cases: Agentic AI in Action

Here are some of the enterprise use cases or applications of Agentic AI:

1.    Enhancing supply chain predictability
Through predictive modeling, Agentic AI can reduce the unpredictability of global supply chains. By analyzing historical supply chain data along with current trends, Agentic AI systems can accurately predict any supply chain disruptions – and detect any seasonal demand changes. 

2.    Revolutionizing customer support with proactive chatbots
Traditional AI systems fail to meet the current demand for personalized and proactive customer service. Agentic AI can transform customer support through its proactive and autonomous approach. Instead of simply responding to customer queries, Agentic AI-powered chatbots can proactively anticipate customer needs and solve problems even before they occur.

3.    Optimizing financial risk management
With Agentic AI systems, banks, and financial services companies can optimize their financial risks caused by fraud or non-compliance to data protection regulations. By automating manual operations, this AI system can perform real-time data processing for immediate risk detection and response. Additionally, they can support financial decision-makers with the best strategy for mitigating these risks.

Overcoming Barriers to Adoption

Despite the multiple benefits, enterprises can face multiple barriers to adopting and implementing Agentic AI including the following:

1.    Implementation challenges
As compared to traditional AI, Agentic AI is more complex with its sophisticated algorithms and data processing capabilities. To develop Agentic AI models, enterprises need human resources with advanced AI and domain expertise. The shortage of skilled AI professionals can hinder implementation – and also add to overall costs.

Additionally, Agentic AI systems need high-quality data feeds to arrive at autonomous outcomes and decisions. Enterprises need to maintain data quality metrics – such as accuracy, consistency, and completeness.

2.    Ethical concerns
There are also growing ethical concerns about autonomous decision-making, enabled by Agentic AI systems. Enterprises adopting Agentic AI need to address questions about transparency and accountability. For instance, the AI system designed to lower energy consumption can increase operational expenses in critical applications.

3.    Lack of trust in AI-powered decision-making
Can organizations trust Agentic AI-powered systems to make critical business decisions? Without absolute transparency, it’s difficult to trust the process that Agentic AI systems follow to arrive at their decisions. Enterprises can build trust among their stakeholders by explaining the reasoning behind how these AI systems implement their decision-making.

Future Trends in Agentic AI for Enterprises 

Despite the challenges, Agentic AI can seamlessly transform how humans and industries interact with “intelligent” machines. Going ahead, Agentic AI systems will develop more “human-like” capabilities such as:
•    Emotional intelligence
•    Improved understanding of natural human language
•    Ability to accurately interpret facial expressions and other cues.

According to Deloitte, autonomous AI technology has the potential to make future workers more productive – and also automate business processes at multiple levels. By 2027, 50% of enterprises using Generative AI will launch pilot projects in Agentic AI technology.

Among other future developments, Agentic AI can power the deployment of specialized agents for industry-specific tasks – from healthcare to manufacturing. For instance, in the healthcare domain, AI-powered diagnostic agents can provide accurate medical diagnoses. Similarly, legal agents can help organizations with specific legal knowledge – and address complex legal regulations.

Similarly, Agentic AI can power human-AI collaboration in business services previously performed by human professionals. This includes areas like customer support, personal counseling, and individual learning.   

Action Plan: How Enterprises Can Get Started

Enterprises need an efficient action plan and strategy to get started with implementing Agentic AI. Here’s the action plan:

1.    Assessing readiness
As the first step, enterprises need to assess if they are ready to implement Agentic AI across their business process. This includes a comprehensive infrastructure assessment to check if it can meet the computational requirements of this AI system. Along with a scalable infrastructure, enterprises must have robust data processing capabilities.

Additionally, enterprises need an efficient data management system to feed high-quality data to AI models. Data management must include data mapping & integrity, integrated data sources, and metadata management.

2.    Identify high-impact areas of deployment.
This next step focuses on identifying the high-impact business areas ready for immediate deployment of Agentic AI modules. While some AI modules may need to be built specifically for the business area (for example, customer support), other AI modules require retraining to integrate seamlessly with the focus area.

Additionally, enterprises need to upskill or reskill business teams to manage their AI systems.

3.    Build a roadmap.
Beyond the initial implementation, enterprises need a strategic roadmap to build their Agentic AI capabilities over time. This roadmap can focus on objectives like building:
•    Intelligent data orchestration
•    Adaptive workflows
•    Human-AI collaboration

Conclusion
As an AI-powered tool, Agentic AI enables autonomous decision-making across enterprises. For an efficient deployment, business leaders must redefine their Agentic AI success metrics to performance, scalability, autonomy, and proactivity. With these metrics, Agentic AI can drive long-term business outcomes around business growth, operational efficiency, and innovation.

With its innovative AI agent development services, Xoriant believes that collaboration is the future of AI technology. With intelligent agents (powered by Agentic AI), enterprises can explore new frontiers in their specific industry domain. With our Data and AI services, we can partner you in your business transformation journey. 

If you are looking for the best AI agent service provider, contact us now.