Getting to know our global leaders in Data & AI, Siraj and Melissa-Anne
Hear from Siraj and Mel on their perspectives, passions, and experiences in AI!
Q1: Tell us more about your background and what led you to develop an interest in Data & AI.
Siraj: I started my career where engineering teams were passionate about developing database management systems that could store and retrieve data efficiently. When I began to work in Business Intelligence, or Management Information Systems as they were known before, I realised that the real value of Data lies in understanding the stories they have to say. I don’t think I’ve ever had enough of working with Data & AI since…
Melissa-Anne: I have a background as an actuary with an additional major in Statistics, so data and its interpretation have always fascinated me. Over the years, I've developed a genuine curiosity about how new technologies can help us become more informed and make smarter, faster decisions. As my husband likes to say, it often pays to be "lazy smart" because there must be a more effective way to do things that can lead to amazing discoveries.
Q2: What aspects of Data & AI are you most passionate about right now?
Siraj: I love that the pace of innovation in this space is absolutely mind-blowing. Just think about where we were 10 years ago - storing and processing a few terabytes of data was a massive challenge, and AI was still mostly about basic automation and predictive models. Fast forward to today, and we’re talking about billions, even trillions of data points being processed in real-time, thanks to cloud computing and high-speed data pipelines.
The way we handle data has completely transformed. Storage has become practically limitless, and processing power has exploded - what used to take hours or even days can now be done in seconds. And then there’s AI, which has taken a giant leap with large language models (LLMs), deep learning, and real-time decision-making. It’s exciting because we’re not just collecting data anymore—we’re making sense of it at an unprecedented scale. AI isn’t just predicting trends; it’s creating, optimising, and even reasoning in ways we never thought possible. And the best part? We’re only getting started.
Melissa-Anne:
WHY I DO IT: To understand how the explosion of data available can be wrangled to support practical and actionable insights and growth.
WHAT I DO: Driving data-led decision-making to enable people and organisational growth and transformation.
WHAT DRIVES ME: Seeing how people can innovate to solve some of the most challenging problems when provided with the right data evidence.
It's not just about one technical aspect but the outcomes we can achieve with the right solutions.
Q3: What is one of the biggest misconceptions about AI that you have encountered, and how do you address it?
Siraj: I think one of the biggest myths about AI is that it’s some kind of magic – people that you can just plug it in, and boom, it knows everything, like in movies or those overhyped ads. In reality, AI is only as good as the data it’s trained on, and getting it to work well takes a ton of effort. People don’t realise how much behind-the-scenes work goes into cleaning data, training models, and making sure the outputs make sense. Without good data, it is really hard to get good AI. It’s powerful, but it’s definitely not a shortcut to instant genius!
Melissa-Anne: Many people fear that AI will replace their jobs. While this is less likely in most roles right now, it's crucial, however, to understand how you can leverage AI to become more effective and upskill yourself. Otherwise, someone else might take that position ahead of you. Start by reading and educating yourself in small ways. AI itself can help you upskill but help you learn concepts quicker, and it is great fun to interact with GenAI specifically. The more you understand and test AI, the more you can trust its ability to support you.
Q4: What have you seen companies struggle most with when embarking on their AI journey?
Siraj: Good quality data - hands down. So many companies jump into AI thinking they can just throw a model at their data and get instant results. But if the data is messy, incomplete, or just not the right kind, AI won’t magically fix it. A lot of time gets wasted trying to make sense of bad data instead of actually building useful AI solutions. The companies that get it right focus on cleaning, structuring, and understanding their data first - because without that, even the best AI is just guessing.
Melissa-Anne: We'll dive deeper into this during the session, but many companies rush to get started with AI without a clear view of where it makes the most sense based on their business and goals. Haphazard initiatives can lead to quick wins but often make it difficult to determine ROI and impact on the top or bottom line when not aligned with their overall business goals.
Keen to leverage AI for business success? Tune in to our webinar on 6th March for practical strategies and insights from our Data and AI experts alongside our global FMCG client, Campari Group!
Sign up for our webinar here: https://content.lanciaconsult.com/unlock-ai-potential
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