Over the past couple of years, AI has made renewed inroads into the enterprise technology landscape. From redefining customer experiences to reshaping operational characteristics, the use cases have multiplied considerably, and applications have multiplied in concert with executive support. 

The magic of AI is that the pace of evolution is so fast that enterprises barely have time to get acquainted and adapt to a new AI capability. The next big thing arrives sooner than many think.

First came the onset of Generative AI which fueled a range of new capabilities that businesses of all sizes began to pursue. That was swiftly followed by the rise of Agentic AI. More transformations seem to await us soon. No wonder that Gartner estimates that enterprise spending on AI software will surpass USD 297. Billion by 2027.

What is Agentic AI?

In simple terms, Agentic AI is an AI system that can autonomously pursue complex tasks and execute them with minimal human supervision. It is seen as the next dimension of generative AI capabilities for enterprises. For example, Generative AI can be used to generate images and text that a person can use to further structure and create a book. An Agentic AI system can, however, create an entire book filled with relevant images, and text, and structured in the exact way it is needed for the end-audience.

It can run several sub-routines or tasks in parallel to execute a full workflow rather than just a specific singular task output. With limited human intervention or supervision, it can understand and autonomously run complex and multi-layered tasks having several sub-processes and even make autonomous decisions by itself to achieve the intended outcomes or objectives of the situation.

How will Agentic AI reshape enterprise operations?

With an estimated market size of over USD 47.1 billion by 2030, Agentic AI will transition into a critical enterprise asset in the coming years. There are several areas in which Agentic AI can bring about revolutionary changes in the way enterprises operate. Let us explore some of the key ones:

Build fully autonomous decision-frameworks

Despite having a vast treasure trove of data, enterprises often lack critical insight generation capabilities owing to delays and biased human intervention in data-driven operations.

With Agentic AI, human intervention can be minimized significantly, and vast amounts of data can be processed simultaneously and systematically by Agentic AI systems. The processed insights are then leveraged by the Agentic AI system to execute a series of highly complex tasks that jointly deliver value to all stakeholders involved. A simple example would be Agentic AI systems studying demand patterns of the market in a season and placing inventory orders in a retail organization aligned with calculated demand.

Enhance security capabilities

With an overwhelming increase in the adoption of digital business models, enterprises are highly concerned about the measures they take to securely safeguard their tech landscape. One of the key challenges in this regard is the availability of skilled resources who have expertise in monitoring and securing key digital services often running in the cloud. Studies show that nearly 93% of enterprises face a skill shortage when it comes to cybersecurity initiatives. Agentic AI can help navigate this core challenge.

Traditional AI tools help in identifying threat agents effectively. But Agentic AI, with its ability to understand and reason, can go further by executing steps that neutralize the threat dynamically, check for any impacts, take measures to repair any damages identified, and use the learnings to fortify enterprise networks from future attacks from similar threat sources. This entire security routine can be run autonomously and continuously by Agentic AI agents.

Autonomous customer interactions

Taking a step further from Generative AI-powered chatbots and support agents, Agentic AI can’t just answer queries from customers but also engage in conversations to understand deeper context and develop solutions or recommendations that best fit potential customer objectives and business interests.

For example, an Agentic AI chatbot can engage with a loan applicant, understand their needs, assess their credit-worthiness, execute loan appraisal workflows, calculate loan terms and repayment schedules, and facilitate disbursement of the loan amount, and even set monthly payment deductions based on the customer’s financial profile. Such a granular level of understanding and task execution autonomously makes Agentic AI the perfect digital companion for customers seeking intuitive self-service options in different sectors.

Enhance engineering and product development

Today, most enterprises allow their engineers to leverage no-code or low-code tools to accelerate application development cycles and lower quality issues with more resilient code engineering and following of best practices. Agentic AI can be a great addition to the enterprise technology stack in this regard.

An Agentic AI code assistant can understand specific business objectives, requirements, and intended outcomes and create the end-to-end code for solutions that imbibe all operational aspects. Agentic AI can also perform quality checks in parallel with the development workflow, thereby ensuring faster product engineering cycles.

Taking the next big AI step with Agentic AI

Agentic AI opens the door to limitless possibilities for enterprises in all business sectors. However, building Agentic AI systems is not without challenges. From getting the right models to training and integration with existing business systems for workflow execution, several heavy-duty transitions must be made. This is where guidance and support from an established partner like Recode can be a major game-changer. Get in touch with us to learn more.