How Software Developers Can Prepare for Agentic AI

Artificial intelligence (AI) is leaps and bounds ahead of where it was just five years ago. When OpenAI launched ChatGPT in 2022, it grew to one million users in less than a week. AI has evolved from simple rule-based systems to more sophisticated machine-learning algorithms.

In the software development realm, AI has already made big strides—especially within enterprise content management applications. It’s streamlining workflows, enhancing data processing, and improving decision-making capabilities.

With the emergence of agentic AI, we’re on the cusp of a new era. This transformative technology promises to take AI from a human-dependent tool to an autonomous business partner. Agentic AI represents a leap forward in artificial intelligence that will undoubtedly revolutionize the software industry.

What is Agentic AI?

Agentic AI, or agent-based artificial intelligence, consists of AI systems that can act autonomously to achieve goals. These systems go beyond simple task execution to independently solve problems and make decisions like a human agent would.

Agentic AI is goal-driven. These systems are designed to meet specific objectives and can create plans to achieve them. They go beyond responding to inputs, proactively working toward desired outcomes. Agentic AI systems can learn and adapt. They improve their performance over time by learning from experiences and adjusting their strategies.

One of agentic AI’s most impressive features is its advanced reasoning capabilities. It can process complex information, draw insights, and make logical inferences. Agentic AI can not only tackle difficult problems and understand nuanced instructions, but it can also explain its decision-making process.

Let’s say an AI agent receives a complex customer inquiry about a missing delivery. It analyzes the situation by accessing order tracking systems and verifying shipping status. Without human intervention, the agent can identify delivery issues and initiate the appropriate actions autonomously.

Agentic AI vs. Traditional AI

Traditional AI typically operates within predefined parameters. It excels at pattern recognition, data analysis, and performing programmed instructions. But it’s unable to adapt to new situations or make autonomous decisions beyond its initial programming.

Agentic AI demonstrates a higher level of autonomy and flexibility. These systems can:

• Make independent decisions based on complex inputs and changing environments
• Set and pursue goals, adapting strategies as needed
• Learn from experiences and improve performance
• Engage in advanced reasoning

While traditional AI is an efficient tool, agentic AI is more like an intelligent assistant that can formulate plans and take initiative.

Agentic AI Real-World Applications

Agentic AI will touch every industry, offering innovative solutions to complex challenges. Here are some examples of how agentic AI has already been applied to real-world scenarios.

IT Incident Response

IBM manages and analyzes massive amounts of data on its network systems. To quickly identify threats, phishing attacks, and ransomware without overwhelming security teams, IBM developed Watson for Cyber Security. This cognitive IT system processes unstructured data like blogs and research reports. Then it correlates the unstructured data with structured data from security tools to identify threats.

Implementing Watson for Cyber Security has allowed IBM to single out and respond to threats more quickly. It’s made the process more efficient and helped IBM protect itself and its clients from cyber attacks.

Customer Service Routing

Verint, a leader in customer experience automation, uses multiple agentic AI solutions to improve interactions with customers. With help from AI, Verint’s CX/EX Scoring bot monitors customer calls, evaluating conversation flow and emotional cues. It immediately notifies supervisors when agents need support.

The company also leverages an Agent Virtual Assistant. Powered by agentic AI, the Verint Agent Virtual Assistant takes an agent question and analyzes the context using third-party applications and systems of record. From this information, it can provide personalized information to answer the agent’s question.

Software Development

Agentic AI has simplified how software teams work. Since agentic AI systems are remarkably autonomous, they can understand context and execute complex development tasks.

One example is GitHub Copilot for Pull Requests, which goes far beyond basic code review. Agentic AI independently analyzes code changes to understand their broader impact across the entire codebase. It flags potential issues and proposes specific fixes, explaining its reasoning much like an experienced senior developer would.

Amazon CodeWhisperer exemplifies how agentic AI can transform code optimization. It understands project context and independently suggests architectural improvements. It can analyze codebases holistically, identifying opportunities for performance optimization and flagging potential security issues before they become vulnerabilities.

What Does Agentic AI Mean for Independent Software Vendors (ISVs)?

For independent software vendors, agentic AI isn’t just another tech buzzword. Working with agentic AI is like having a highly capable member of your team who can work independently, handle routine tasks, and make smart decisions without needing constant direction.

Development teams often get bogged down with time-consuming tasks like testing, code review, and documentation. Agentic AI can tackle these responsibilities without breaking a sweat. It frees up developers to focus on solving complex problems and creating innovative features that set their products apart. For teams with limited resources, this means getting more done without having to hire staff.

Greater efficiency is just one of the perks agentic AI brings to the table. It can also help improve product quality by continuously monitoring code, spotting potential issues, and suggesting improvements. This translates into more reliable products, fewer customer support issues, and reduced maintenance costs. The system learns from every project it works on, ensuring teams apply successful approaches consistently across the entire product.

Agentic AI is a valuable tool that enables ISVs to move faster in a competitive market. When you can develop and test your own features more quickly, you can respond to customer needs and market opportunities at a pace not previously possible. This speed advantage is critical in the software market, where being the first to introduce new capabilities can make a huge difference in market share.

How Accusoft is Preparing for Agentic AI

The future of software development is intertwined with agentic AI. Staying competitive means finding ways to apply these capabilities efficiently.

Accusoft is at the forefront of incorporating new technologies like agentic AI with features like context-based redaction. In partnership with IBM, Accusoft has integrated watsonx.ai technology into our PrizmDoc product to help ECM software organizations reduce document processing times. We continue to explore bringing cutting-edge AI capabilities to content processing and document management applications.

With PrizmDoc, developers can access sophisticated AI-powered content processing capabilities without investing months or years of development time to build them from scratch. This allows ISVs to focus on their core product while leveraging Accusoft’s expertise in content processing and AI integration.

Ready to see what PrizmDoc can do for your application? Start your free trial today!