Artificial intelligence (AI) is rapidly transforming the business world, and Application testing is no exception. AI-powered testing tools can help businesses to automate tasks, improve accuracy, and reduce costs. One of the most important benefits of using AI for Application testing is that it can help automate repetitive tasks. This can free up testers to focus on more complex and strategic tasks. For example, AI can automate creating test cases, executing test cases, and analyzing test results.

In the present digital period, Artificial Intelligence (AI) is impacting the future of various aspects of Quality Assurance (QA). This evolution has resulted in strategies for ensuring quality is effectively integrated into development processes.

Interoperability in banking and finance is multifaceted, uptight, and fraught with many menaces, risky projects, and prominent vendors. One such solution is Open banking. Open banking is a mode where banks provide a set of consistent and standardized interfaces to permit service providers and third parties into their banking services. It is about opening up large banks’ banking services to third-party providers, application developers, and end users.

Platform engineering is a discipline that addresses organizations’ need to expedite developing and managing cloud-native applications. This focus on internal development involves creating “Golden Pathways” to save time and encourage creativity.

Staying ahead of the curve is paramount in the vigorous scope of software testing and quality assurance. The collaborative effort between industry leaders Cigniti and Katalon has given rise to The State of Software Quality Survey 2024-25, a groundbreaking initiative aimed at unraveling the latest trends, challenges, and innovations shaping the future of software testing.

The digital engineering and assurance landscape is swiftly changing, propelled by technological strides, sustainability initiatives, and shifting industry needs. With 2024 on the horizon, distinct trends are surfacing, demanding attention from sector experts and companies aiming to maintain their competitive edge.

In recent years, cybersecurity has faced increasingly sophisticated threats, making it crucial for organizations to develop robust systems for threat detection and response. One emerging technology that holds promise in this domain is ChatGPT, an advanced natural language processing model developed by OpenAI. In this blog post, we will explore how ChatGPT can be leveraged to enhance threat detection and response in cybersecurity.

The heightened demand for agile scaling across enterprises in contemporary times is underscored by several key factors, including the rapid pace of product changes within organizations, evolving customer expectations and market dynamics, the imperative of digital transformation and innovation, the risks associated with falling behind in competition, the inherent advantages of adopting agile methodologies, and the pressing need to adapt or face the consequences of obsolescence.

A catastrophe hazard is a severe and widespread event that causes significant damage and financial loss. These events are frequently natural disasters or large-scale human-made incidents that affect expansive and contemporary claims. Catastrophe hazards pose substantial trouble to insurers, as they can lead to a high volume of claims within a short period, potentially impacting insurance companies’ financial stability.