I recently had the opportunity to sit down with Glen McCracken, Head of Data Analytics and Automation at the billion-dollar fintech giant, ION Analytics. Glen’s career is remarkable, tracing the evolution of data science and technology over decades. However, what truly stood out were his candid insights on AI and unstructured data.
Glen’s journey began with an undergraduate degree in statistics and corporate finance, followed by a brief period in actuarial science—a path he quickly realised wasn’t right for him. It was at PriceWaterhouseCoopers, where he worked on data-centric projects like forestry valuation models and spam filters for Yahoo, that he found his stride. These early experiences were a crash course in the power of data and its limitless applications.
However, it wasn’t until Glen led the creation of a new tech infrastructure at Eden Park for the 2011 Rugby World Cup that his perspective on digital transformation truly evolved. This project wasn’t just about implementing technology; it was about achieving key goals: ensuring the safety of spectators and securing vital revenue, both crucial for the success of the tournament. The project also underscored the importance of a central management system that could be efficiently managed by one person, rather than relying on a large IT team. The strides in technology made during this project expanded Glen’s understanding of how data and AI could integrate into daily operations and decision-making processes. What began as a focus on statistics and modelling grew into a broader vision of how these tools could enhance operational efficiency and strategic planning on a global scale.
This pivotal project led to an invitation to work at the 2012 Olympics in London—a move that took Glen from New Zealand to the heart of global tech innovation.
After relocating to London nine years ago, Glen joined ION Analytics and wasn’t just given a job—he was handed a monumental challenge. Merging the datasets of two billion-dollar companies is the kind of task that would make even seasoned professionals pause. “How do you even begin merging two billion-dollar companies’ data?” I asked, genuinely curious.
Glen didn’t hesitate. “It was actually four companies,” he corrected, with a hint of a smile.
“We were dealing with over 50 different systems across these companies, each with its own complex tech stack. The key wasn’t to start with the easiest integration but to tackle the hardest one first. When you start with the most complex, you learn the most. If you begin with the simpler tasks, you often have to backtrack and make changes later because you haven’t accounted for the requirements of the more difficult integrations. By starting with the toughest challenge, we laid the foundation that made the subsequent integrations much smoother. Once we had the first one down, the groundwork we laid made it possible to handle the remaining three integrations simultaneously. It turned out to be quicker and smoother than we had initially imagined because all the hard work and learning had already been done.”
Against the backdrop of a recent wave of high-profile CEO departures—a phenomenon some have dubbed the “Big CEO Exodus”—Glen offered a nuanced perspective on the evolving demands of leadership in today’s rapidly changing tech landscape. He identified two archetypal leaders: the “master orchestrators,” like Elon Musk and Jeff Bezos, who disrupt industries by breaking down problems to their most fundamental components through a “first principles approach,” and those who have risen through the ranks by learning and adhering to established norms.
Glen explained that while the latter group—leaders who’ve climbed the corporate ladder—brings valuable experience, their deep ties to traditional methods can make them slower to react to the monumental changes unfolding in the industry. “These leaders often rely on how things have always been done, which can hinder their ability to adapt quickly,” he noted. In contrast, the tech-driven world increasingly demands leaders who can navigate unprecedented challenges with fresh thinking and agility.
This, Glen believes, is why we’re on the cusp of seeing a new kind of CEO emerge. These future leaders will need to be “master facilitators,” adept at bringing together diverse teams, integrating various technological disciplines, and managing complex systems. They won’t be confined to a single domain but will understand how to leverage technology across multiple fronts to steer their companies through rapid transformation.
“As advancements in AI, data lakes, and automation continue to reshape industries,” Glen pointed out, “boards of directors will start seeking leaders who are not just tech-literate but also capable of guiding their organisations with a forward-thinking mindset, unencumbered by outdated practices.”
As our conversation continued, Glen’s passion for unstructured data was clear. While much of the AI conversation focuses on structured data, where significant advancements have already been made, Glen sees enormous potential in unstructured data.
“Think of churn prediction models that go beyond just structured behavioural and firmographic data,” he suggested. “There’s a wealth of unstructured data—like online news, meeting conversations and phone call recordings —that could provide crucial insights”
However, Glen quickly emphasised a critical issue that is often overlooked in the rush to adopt AI: the quality of the data. “All the companies that want AI need good data. You can’t build a house on unstable foundations. Bad data means bad AI,” he stressed. This is a core belief that drives Glen’s approach to data analytics and automation. For him, it’s not just about collecting data but ensuring that the data is accurate, relevant, and integrated in a way that truly supports AI-driven decision-making.
He envisions a future where AI can analyse every aspect of a business, from internal communications to external news, offering predictions with unprecedented accuracy.
“Imagine salespeople completely freed from admin work, thanks to AI tools that automatically generate CRM updates, call notes, meeting summaries, and highlight key positive or bad feedback. That’s where the future is headed.”
Glen’s social media presence has become a source of entertainment and insight for many. Curious about how it all started, I asked him about his unexpected rise as a LinkedIn personality.
“It actually began as a way to vent,” Glen confessed. He recounted an incident at a private equity event in Austin where a young speaker boldly claimed that AI began in 2020. “That really annoyed me,” Glen admitted. Frustrated by the lack of historical awareness, he took to LinkedIn to share his thoughts. What followed was a year-long journey of candid, often humorous posts that resonated with a large audience. For Glen, it wasn’t just about venting—it was a form of therapy, a way to navigate the corporate world’s often bizarre realities.
Glen’s optimism for AI’s future is infectious, especially when he talks about the concept of personal AI. During our conversation, Glen mentioned how Sam Altman recently discussed with Mark Zuckerberg the vast potential of personal AI—an idea that has captivated many in the tech world. Glen is particularly excited about the possibilities, so much so that he’s planning to fully embrace the idea with the “Limitless Pendant.” This wearable device is designed to record everything in your life, automatically make notes, and summarise your day, creating a comprehensive digital memory that can enhance productivity and decision-making.
But Glen also pointed out why AI is not advancing as quickly as it could. “The reason AI is moving slowly right now is because of privacy concerns, the opaqueness of algorithms, and the lack of clear explanations about how AI actually works,” he explained. Glen noted that while these issues are slowing down public adoption, they are being actively addressed behind the scenes. Researchers and developers are working tirelessly to make AI more transparent, explainable, and privacy-respecting, which Glen believes will lead to wider acceptance and integration of AI in our daily lives.
He expressed his belief in a future where AI plays an even more integral role in our lives—beyond just improving efficiency and enabling better decision-making. In this future, AI could become a seamless part of our personal and professional lives, offering insights and assistance that we can scarcely imagine today.
However, to truly harness these possibilities, organisations will need leaders who are not only adept with technology but also capable of guiding their teams through this transformative era with a clear vision and a deep understanding of both the potential and the challenges of AI.
Glen’s insights serve as a powerful reminder that while AI and emerging technologies are crucial, the human element—leadership, vision, and the ability to bring people together—remains more important than ever. It’s this combination of technological prowess and human leadership that will define success in the AI-driven future.
