Agentic AI is the combination of different AI approaches, techniques, and models that create a new series of autonomous agents to analyze data, establish goals, and create action plans to achieve them.

What is the difference between Agentic AI and Generative AI?

Agentic AI acts independently and can make decisions, perform tasks, and interact with its environment without human intervention. Generative AI creates new content, such as images, text, music, or code, in response to user prompts.

Will Agentic AI be the new trend in Generative AI?

Agentic AI is a type of AI that can make decisions and take actions independently to achieve goals. Compared to traditional AI models, Agentic AI can make employees more productive and automate multi-step processes.

How will the Agentic AI testing system shape the future of the testing process?

Agentic AI testing systems will upscale the QA process by automating complex tasks, improving accuracy, and enhancing efficiency. These systems can autonomously generate test cases, detect real-time issues, and adapt to dynamic software environments.

What is the impact of Agentic AI?

It enables faster decisions, reduces manual work. It also helps businesses scale by automating complex tasks with minimal human input.

Why should organizations use Agentic AI to process and analyze large volumes of data?

Agentic AI can analyze data, detect patterns, and work on real-time insights, improving efficiency and reducing errors.

Why should I choose TestingXperts (Tx) for Agentic AI solutions?

Tx offers AI-driven QA services to ensure reliable, scalable, and efficient AI implementations. We use tools like Tx-SmarTest and Tx-HyperAutomate.

Agentic AI TestingXperts

Agentic AI

All Blogs

Select Category

Mobile Testing Cloud Testing Analytics Manual Testing Infrastructure as code Engagement Models Data Engineering Uncategorized Accessibility Testing API Testing Insurance Industry Edtech App Testing testing for Salesforce LeanFt Education Automation Testing IOT Internet of things SRE Salesforce Testing Cryptojacking Test Advisory Services End-to-End Testing Infographic IoT Testing Selenium QSR app testing Database Testing Kubernetes Samsung Battery Regression Testing Digital Transformation Digital Testing Non functional testing Hyper Automation Testing for Banking Events DevOps QA Functional Testing Bot Testing Integration Testing Test Data Management Scriptless test automation STAREAST Continuous Testing Software Testing AI Unit Testing ML CRM Testing Data Analytics UAT Testing Black Friday Testing Exploratory Testing Testing in Insurance App modernization EDI Testing MS Dynamics Test Automation Penetration Testing Data Migration Load Testing Digital Assurance Year In review ISO 20022 Agile Testing Big Data Testing ETL Testing QA Outsourcing Quality Engineering Keyword-driven Testing Development Selenium Testing Healthcare Testing Python Testing Compatibility Testing POS Testing GDPR Compliance Testing Compliance Smoke Testing QA testing web app testing Digital Banking SAP testing Web applications Agentic AI eCommerce Testing Quality Assurance FinTech Testing Wcag Testing User Testing IaC Data Quality Cyber attacks Beta Testing Retail Testing Cyber Security Remote Testing Risk Based Testing DevOps Security Testing RPA Usability Testing Game Testing Medical Device Testing Microservices Testing Banking Performance Testing Artificial Intelligence UI Testing Metaverse IR35 Containers Autonomous AI