Using email to communicate with consumers, sell new items, connect with future customers, and much more is crucial for running a successful business. Despite the numerous communication options available today, such as social media platforms, chatbots, and collaboration tools like Slack, email remains a viable and effective option. In fact, Internet Live Stats reports that 2,641,007 emails are received per second.

For decades, the sci-fi dream of simply speaking to your device and having it perform tasks for you seemed far-fetched. In the realm of test automation and quality assurance, this dream is inching closer to reality. With the evolution of generative AI, we’re prompted to explore what’s truly feasible. Embedding AI into your quality engineering processes becomes imperative as IT infrastructures become increasingly complex and integrated, spanning multiple applications across business processes.

For the banking and financial services industry, artificial intelligence (AI) isn't just a new tech trend. It's a powerful tool that will have a wide range of impacts, from risk management to operational efficiency and customer experience. According to Deloitte, the world’s top 14 investment banks could potentially boost their front-office productivity by 27% to 35% by leveraging generative AI.

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It’s not hyperbole to say that generative AI (gen AI) is radically transforming the advertising, media and entertainment industry. There has been widespread excitement about the potential of gen AI to open brand-new creative opportunities and unlock unprecedented efficiencies. At the same time, there has been understandable concern about issues such as inherent bias, deep fakes and the impact of gen AI on jobs.

Delivering transformational innovation and accurate business decisions requires harnessing the full potential of your organization’s entire data ecosystem. Ultimately, this boils down to how reliable and trustworthy the underlying data that feeds your insights and applications is. This applies to modern generative AI solutions that are particularly reliant on trusted, accurate, and context-specific data.

As technology advances, so do user expectations. Advanced analytics has emerged as a hot topic and a key area of focus for buyers looking to provide higher quality analysis to inform business decision-making in a turbulent market. Furthermore, the era of cheap money is over. Funding is scarce and Independent Software Vendors (ISVs) must ensure their offer is seen as an essential expense for financially constrained buyers, delivering quick value, quality, and innovation.

The concept of time-to-market has emerged as a pivotal factor in determining success. Bringing new products, services, or features to market can make the crucial difference between seizing opportunities and falling behind. But faster tech advancements, changing consumer preferences, and global market dynamics meant that businesses need a paradigm shift in their approach to strategy. The adoption of APIs has surged, fundamental to rapid development and innovation.

AI automation involves leveraging artificial intelligence (AI) to automate repetitive tasks within operational workflows, thereby enhancing efficiency and productivity. This not only streamlines routine tasks within core business processes but also enables companies to scale growth efficiently by integrating a broad range of digital tools such as robotic process automation, APIs, and software robots.