Business Intelligence in the Era of AI

Svetla Yankova, Business Intelligence Director at Progress, explores some of the ways Artificial Intelligence (AI) impacts Business Intelligence and explains why AI is so important to her, and to all of us.

Svetla, tell us about your speaking engagement at the Data, AI and Analytics Conference Europe 2024 on October 14-17 in London, UK.

I discuss the future of Business Intelligence (BI) in the AI era, focusing on the skills data professionals need to remain relevant and excel, with a goal of providing an overall framework for thinking about AI augmentation and to highlight the high-value-added areas specific to data work. The session begins with an overview of how AI drives automation in BI and its impact on jobs in the technology sector. Then, we dive deeper into the concept of “AI Karma,” examining the unintended adverse consequences of AI implementation and how this influences our decisions on which tasks to automate and how. We apply these learnings to perform a high-level business analysis of the BI workflow to identify suitable augmentation through task automation, AI and human effort. We then dive deeper into the specific skills that will continue to rely predominantly on human reasoning and creativity.

You are also pursuing an Executive Diploma in AI for Business at the Said Business School at Oxford University in the UK. What does this experience mean for you?

The Said Business School’s motto, “Impact from within,” perfectly summarizes my experience so far. I pursued this diploma because I wanted to experience education at one of the world’s most esteemed universities, to learn alongside a diverse and brilliant group of people, and to dive deeper into how AI will impact businesses and society as a whole. I got all of this and even more – a complete shift in my mindset and the way I think about the world, myself and those around me. It’s akin to moving from a monochrome view to a vibrant, full-spectrum perspective.

How do you put into practice what you are learning at Said Business School in your work at Progress? Can you give us several examples about your BI team at Progress using AI?

The program is structured in modules, each ending with a graded paper on a specific topic. Each paper has been directly applicable to my work as the leader of the data and analytics organization here at Progress. For example, one was focused on evaluating the AI readiness of companies, which resulted in a complete revamp of our data strategy.

Why are you so passionate about AI – when and how did your interest spark and what keeps you motivated to continue to explore AI?

I have been passionate about machine learning for the past ten years because it is the intersection of statistics, data and business - areas I enjoy individually and collectively. However, my interest towards AI stems not only from passion but from necessity. I envision a future where AI is integral to our very existence, whether we want it or not.