Design: Artificial Intelligence Design

In February 2024, Fast Company [1] reported on the rise of conversational AI search engines. Large language models (LLM) power these tools, which can answer users’ questions by retrieving and summarizing information from the Internet.

Since the rise of generative AI, several conversational AI search applications have cropped up online. Academic and scientific research is spearheading a wave of experimentation in this field. [2] Frenzied enthusiasm exists around what seems to be a new way of searching for content that provides an alternative to the Google model of search to which we’ve all become accustomed. Read More

Artificial intelligence (AI) is the simulation of human intelligence in machines that we’ve programmed to perform tasks that typically require human intelligence. In recent times, AI has successfully carried automation to the next level with its wide range of capabilities. AI is bringing about the transformation of industries across diverse domains. The information technology (IT) industry is no exception. In fact, the IT industry has enthusiastically embraced the immense potential of AI to transform virtually every aspect of its operations. Professionals within the IT sector have engaged in extensive discussions regarding the potential benefits and drawbacks of AI-driven technologies.

Although market analysts have connected the rapid rise and widespread adoption of AI to recent downsizing at major IT firms, it is crucial that we harness the potential of AI to benefit the IT industry. Highlighting the positive aspects of AI-driven technologies is of the utmost importance. Read More

Usability testing has long been a cornerstone of the design and development of software products, ensuring that user interfaces meet the needs and expectations of users. Traditionally, the testing process has relied heavily on human insights, often involving UX research methods such as usability studies, A/B testing, user interviews, and surveys. But these approaches, while effective, are time consuming and often limited in their scope and scalability.

Enter the age of artificial intelligence (AI) and machine learning (ML). These technologies are revolutionizing the field of usability testing, offering new dimensions of efficiency and accuracy. Through the integration of usability testing with AI and ML, the software industry is witnessing a paradigm shift from conventional, manual testing to more sophisticated, data-driven approaches. Machine learning—with its ability to analyze vast amounts of user data and learn from user interactions—is not just enhancing usability testing; it’s reshaping it. AI and ML are also empowering product teams to create more personalized user experiences and making software more user centric than ever before. Read More