A Conversation Between Dr. Naira Musallam and Priscilla McKinney on AI, Design, and Defying the Odds

In a recent episode of the podcast Digital Transformation Success, SightX co-founder Dr. Naira Musallam sat down with Little Bird Marketing’s Priscilla McKinney for an inspiring conversation about the evolution of data science, building inclusive technology, and the very human side of innovation.

Below are some of the most insightful moments from their conversation.

Q: What led you to start SightX?

“In 2012, there was an HBR article that referred to data scientists as having ‘the sexiest job of the 21st century’, but 70% of their time was spent on prep work. What a waste of human potential. After all, the only commodity you can't get back is time."

Naira shared that SightX was born from a personal frustration: watching highly skilled data scientists and researchers waste time cleaning and formatting fragmented data. That realization led to a mission to eliminate the fragmentation in research workflows and give people back their time to focus on meaningful work. The vision was to create an all-in-one streamlined consumer insight platform, with research methodologies that are easy to set up, with automated yet flexible analytics.

Q: What's keeping your customers up at night?

"They’re expected to do more with less."

Whether in insights, strategy, or product roles, SightX customers are under pressure to produce smarter, faster research, on tighter timelines and with fewer resources. That’s why automation and streamlined workflows have become core to the platform’s value.

Q: Let's talk about AI. How do you separate the hype from the real opportunity?

AI isn’t just a buzzword for Naira, it’s a toolset that’s evolving rapidly. But she’s candid about where it excels and where it falls short.

“What you’re trying to do is enable a machine to do what a human once did. But can it now generate something I couldn’t predict myself?”

At SightX, that meant embracing both automation and AI, but doing so with intention.

While AI may hallucinate or feel like a black box, it’s transformative for qualitative inputs like text, transcripts, and images; areas where NLP and generative tools thrive. For quant, however, SightX continues to rely on its own automated library of validated formulas. Accuracy still matters, and no one can afford blackboxes in quantitative analytics.

“We decided to disrupt our own code and build on what we’ve mastered.”

Q: Why build your own code from scratch?

It all comes back to scaling expertise and making what is complex, simple. That’s why design is central to the SightX experience.

“We wanted methodologies that were smart and sophisticated… and easy to use. If people feel uncomfortable using the platform, it doesn’t scale anything.”

Inclusivity means anyone, from a statistician to a brand marketer, should be able to extract meaningful insights with confidence.

Priscilla reflected: 

“We like to interact with beautiful things, and your platform is a beautiful thing. The simplicity and user experience really matter.”

Q: What advice would you give to up-and-coming data scientists?

Naira reflected on how quickly the field has evolved:

“Ten years ago, it was ‘you need to code.’ Now it’s about writing prompts.”

But the most important skill?

“Curiosity. Flexibility. A hunger to learn. That mindset matters more than any hard skill. We’re looking at the future through the limits of our imagination. Things will change in ways we can’t even anticipate. Being open to change is essential."

Q: What about advice for women in tech?

“Don’t get disheartened. There are challenges, yes, but also incredible stories of people defying odds and forging new futures. Focus on that. Let it energize you. Nothing great comes from focusing on the negative.”

And above all, she emphasized the power of connection:

“Human relationships, genuine ones, go a long way, especially when you least expect them to.”

Listen to the full episode: “What Sexy Data Scientists Are Doing These Days” with Naira Musallam and Priscilla McKinney
 

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