Generative AI has recently emerged as a groundbreaking technology and businesses have been quick to respond. Recognizing its potential to drive innovation, deliver significant ROI and add economic value, business adoption is rapid and widespread. They are not wrong. A research report by Quantum Black, AI by McKinsey, titled "The Economic Potential of Generative AI”, estimates that generative AI could unlock up to $4.4 trillion in annual global productivity.

While AI and machine learning have been industry buzzwords for a while, they are now becoming fundamental to software testing. Machine learning algorithms are making it easier to sift through logs, identify patterns, and even predict where bugs are most likely to occur. As these technologies mature, the role of AI in software testing will undoubtedly expand.

Setting up and running a successful ecommerce store has never been easier. Tools like Shopify have always kept things simple, but the rise of AI has made it extremely straightforward for anyone to create various assets required to run a successful ecommerce store. These include landing pages, images, ads, and so many other things. The rise in AI has led to the introduction of hundreds and thousands of new SaaS tools.

Artificial intelligence (AI) has taken the world by storm. ChatGPT was the ultimate proof of concept, demonstrating the power of large language models and AI in easy-to-understand terms. So naturally, business leaders are eager to unlock the productivity benefits that come from integrating AI into business operations. But despite their eagerness, organizations still need to do some work to prepare for AI integration.

First published on the BSA site along with DXC Technology Data analytics and generative AI are revolutionizing the approach organizations take to software development, testing, and delivery, enabling standardization and scalability across the board, including test automation and management. Like other sectors, financial institutions struggle to match the rate of transformation necessary to maintain a competitive edge.

Although it might seem a little early, I was just thinking: what will 2023 be remembered for? For many it will be the year that Beyonce and Taylor Swift took to stages around the world and pushed the boundaries of live music (I’m a confirmed Swiftie if you didn’t know). It is also the year of AI. When I speak with customers, they all talk about how they are steering towards AI adoption.

NLP is a field of AI that enables machines to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. Recently, ChatGPT and similar applications have created a surge in consumer and business interest in NLP. Now, many organizations are trying to incorporate NLP into their offerings.

We're delighted to unveil Choreo TestGPT, Choreo's innovative approach to API testing powered by Generative Pre-trained Transformer (GPT) 3.5 large language model (LLM) from Azure OpenAI. This allows users to test APIs running or proxied via Choreo using natural language, serving as a complementary tool to traditional testing methods. It offers a convenient way to quickly test endpoints without delving deeply into API specifications or crafting intricate JSON payloads.

Generative AI seems like it's shaking things up for process automation, like other industries. But in reality, artificial intelligence is less of a shake-up and more of a natural complement to the capabilities that support a process automation initiative. Imagine a world where AI can turn a PDF into a digital interface, or sort all the emails in an inbox and generate responses for an employee to review.