Afleveringen
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In this episode of AI at Work, I sit down with Juan Orlandini, CTO North America at Insight, to unpack the often-overlooked side of AI adoption: regulation, data strategy, and governance. While much of the recent conversation around AI has focused on speed, productivity, and experimentation, Juan brings the discussion back to fundamentals. Before you scale that shiny new AI tool across your business, have you classified your data? Have you considered your compliance obligations? And do you understand the different responsibilities that come with being an AI creator, adapter, or consumer?
Juan walks us through Insight’s perspective on the current state of enterprise AI, including how they’ve used their own internal tools like InsightGPT to stress test both opportunities and risks. We discuss why internal use cases are often the best place to start, and how leaders can avoid repeating the mistakes of past tech waves, like the race to cloud or mobile apps without a clear strategy.
We also explore the patchwork of US regulations, with California leading the way, and compare this to the EU’s more prescriptive approach. Juan explains how these emerging policies are shaping real business decisions right now, and what business leaders can do to stay ahead. Throughout our chat, his advice is grounded and practical, offering a steady counterpoint to the noise and hype.
Whether deep in deployment or just starting to explore how AI fits into your business, Juan's insights offer a roadmap to thinking bigger while avoiding costly missteps. How do you keep your organization agile enough to adapt, but stable enough to deliver? And what does it really take to treat AI as an enterprise tool rather than a passing trend?
Tune in to hear Juan’s advice on managing risk, reimagining processes, and building a culture that is ready for what comes next.
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What if AI could help us discover new medicines faster, more accurately, and with greater impact for patients?
In this episode of AI at Work, I speak with Dr. Chris Austin, Head of Research Technologies at GSK, to explore how artificial intelligence is changing the way new treatments are developed. Chris brings a unique perspective shaped by decades of experience across academia, biotech, government, and now big pharma. His mission at GSK is clear: to bring science, technology, and talent together to radically improve human health.
We unpack how AI, combined with massive clinical and genetic datasets, is enabling GSK to target disease with unprecedented precision. From identifying the right molecular pathways to simulating clinical trials using digital twins, Chris walks us through how technology is helping reduce development timelines and increase the chances of success. He shares powerful examples including a promising asthma treatment that moved from first-in-human testing to Phase 3 trials across four diseases in record time.
We also explore how GSK uses AI to improve patient selection in clinical trials, design oligonucleotide-based therapies for hard-to-treat conditions like hepatitis B, and incorporate generative AI into everything from drug design to safety prediction. According to Chris, the key isn't just having better algorithms. It's about generating the right data, at scale, to make those algorithms meaningful.
If you're curious about how AI is being applied to some of the most complex problems in healthcare, this episode offers a rare inside look. Chris also reflects on his journey from medicine to data science, and why this is the most exciting time he’s seen in drug development.
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Zijn er afleveringen die ontbreken?
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How do you transform a century-old creative institution into a future-ready force without losing sight of its roots?
In this episode of AI at Work, we spotlight Dr. Joyce Brown, President of the Fashion Institute of Technology (FIT), who has spent 26 years leading a quiet revolution in fashion education. As the first woman and first African American to hold the role, Dr. Brown has reimagined what it means to prepare students for creative careers in a digital world.
She shares how, when she took the helm in 1998, FIT was operating with outdated systems and a siloed approach to education. Through strategic planning, bold hiring decisions, and a commitment to change, she reshaped FIT into a collaborative, interdisciplinary, and forward-looking institution.
Under her leadership, FIT quadrupled its use of technology in teaching and launched the DTech Lab, a hands-on innovation hub where students work directly with brands like Netflix, Adidas, Girl Scouts, and Tommy Hilfiger to solve real challenges using emerging tech like AI and advanced materials.
This episode also explores how FIT is fostering a new wave of sustainable design. Students are using kombucha, mycelium, and pineapple fibers to rethink fashion from the ground up, while also cultivating a natural dye garden on campus. We unpack how the school integrates innovation, science, and sustainability without losing the soul of design.
Dr. Brown reflects on how FIT has responded to social and global shifts, from the pandemic to social justice movements, and how students are using creative work to make sense of the world. Her insights offer a compelling look at what education can achieve when it embraces experimentation, diverse voices, and emerging technologies.
Whether you're in fashion, tech, education, or simply interested in how institutions evolve, this conversation offers a masterclass in visionary leadership and what it takes to truly modernize without losing meaning.
How are you preparing your team or organization for a future shaped by creativity, technology, and purpose? Join the discussion.
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What if the limitations of search engines and conventional AI tools are holding back your ability to truly understand the world? In this episode of AI at Work, we welcome Mel Morris, founder and CEO of Corpora.AI, to explore how artificial intelligence is reshaping the way we research and consume information across industries and professions.
Mel, known for his pivotal role in the early success of Candy Crush creator King, has now set his sights on transforming how individuals, businesses, and institutions discover knowledge. With Corpora.AI, he has created a powerful research engine that processes two million documents per second and delivers comprehensive reports containing up to 500 cited sources per query. The platform ingests over 100 petabytes of open-source intelligence in real time, offering unparalleled speed, scale, and accuracy.
During our conversation, Mel explains why traditional search methods no longer scale for human users and how Corpora.AI addresses this by using real-time data ingestion, multilingual capabilities, and dynamic content summarization. We discuss how the platform is being used by academics, journalists, legal professionals, and even medical researchers to uncover deeper insights and verify claims quickly.
Mel also breaks down how the platform avoids common AI pitfalls such as outdated information, source ambiguity, and bias. Every report produced through Corpora.AI is transparent, traceable, and backed by robust citations, allowing users to make informed decisions with confidence. We also touch on the impact this could have on democratizing access to advanced research, especially in underserved regions.
With the future of work demanding faster, more credible, and more comprehensive access to information, can AI-powered research engines like Corpora.AI redefine how we learn and make decisions? Tune in to hear how this technology is setting a new benchmark for speed, transparency, and trust in research.
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Artificial intelligence is no longer a distant ambition, it is actively reshaping how businesses operate, innovate, and compete. But what does AI truly mean for the workplace of today and tomorrow? And as the pace of advancement accelerates, are organizations truly ready for what comes next?
In this episode of AI at Work, we explore these questions with Louis Landry, newly appointed CTO of Teradata. With over two decades of experience in software architecture, engineering leadership, and technology innovation, Louis brings a grounded and insightful perspective on how businesses can harness AI responsibly and effectively.
Together, we unpack some of the defining trends for 2025: the maturation of retrieval-augmented generation, the evolution of large-scale personalization, and the rise of agentic AI systems that blend generative AI with traditional software architectures. Louis explains how enterprises are moving beyond experimental AI projects to focus on outcome-driven deployments that deliver measurable business impact.
Throughout our conversation, Louis stresses a recurring theme: trust. Building trusted AI, grounded in transparency, human accountability, and high-quality data, is essential for sustainable success. He shares practical strategies for managing emerging challenges such as vector data governance, navigating regulatory uncertainty, and balancing innovation with responsible risk management.
We also explore the vital role of data harmonization in achieving faster, more confident decision-making, and how open-source technologies are enabling more accessible and customizable AI solutions across industries. Louis highlights why data quality, explainability, and clear business outcomes should be the North Star for any organization looking to thrive in an AI-driven future.
As businesses face an increasingly complex digital environment, what strategic investments should they prioritize? How can they build AI systems that remain trustworthy, scalable, and truly transformational? And what leadership mindset is needed to unlock the next era of workplace innovation?
Tune in to hear Louis Landry’s insights on the future of AI, and join the conversation: How do you see AI shaping the future of work in 2025 and beyond?
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What happens when artificial intelligence moves beyond assisting individual developers and solves problems across thousands of codebases simultaneously?
In this episode of AI at Work, we explore how AI is being used to tackle one of the most complex challenges in modern software development: large-scale code migrations. Justine Gehring, AI research engineer at Moderne and author of AI for Mass-Scale Code Refactoring and Analysis, joins the show to explain how she and her team are helping enterprises rethink how they approach code changes across massive environments.
While many are familiar with tools like GitHub Copilot and ChatGPT that assist with writing or suggesting code snippets, Justine shares how mass-scale refactoring calls for a very different set of tools and methods. At Moderne, AI is applied with precision inside an open-source framework called OpenRewrite, which enables consistent and verifiable code changes while maintaining enterprise-level reliability and security.
We discuss how Moderne's approach blends deterministic automation with targeted machine learning to make code migrations faster and more trustworthy. From onboarding new developers to simplifying upgrades across legacy systems, the real-world impact of this work is becoming increasingly visible in sectors like banking and insurance, where complexity and risk have historically slowed down innovation.
This episode also dives into how AI enhances collaboration between developers and machines. Justine highlights the potential for AI to become a quiet partner in understanding, searching, and maintaining vast repositories of code and why this shift may help organizations reduce technical debt and increase maintainability over time.
For business leaders evaluating how AI fits into their development strategy, this conversation offers a practical look at how to make meaningful progress without cutting corners. Whether you're leading a digital team or managing critical systems, Justine's insights reveal what it truly takes to put AI to work at scale.
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In this debut episode of AI at Work, part of the Tech Talks Network, we sit down with Gautam Singh, Head of the Business Unit at WNS Analytics and co-founder of The Smart Cube, to uncover how analytics and AI are helping organisations navigate a rapidly evolving digital-first business world. With decades of experience in data strategy and management consulting, Gautam brings a grounded yet forward-looking view on integrating intelligence into the enterprise.
We explore how WNS helps clients cut through the noise of AI hype by anchoring innovation in practical use cases and structured strategy. Gautam shares a compelling example of a global retail client achieving a 13.5x return on analytics investments, and unpacks why businesses should start small with “data ponds” rather than aim for comprehensive “data lakes” from day one.
He also challenges popular misconceptions about AI, explaining why not everything needs a model and how Excel sometimes still does the job. We examine the importance of traceability, regulation, and a “maker-checker-consumer” framework that ensures human oversight remains central to AI implementation.
Looking ahead, Gautam discusses how collaboration across industries, adaptability, and a clear North Star are key to staying resilient and competitive. This is a conversation for leaders who want to move beyond buzzwords and make meaningful progress with AI and analytics.
How can your business approach AI in a way that delivers real outcomes instead of just more complexity? Tune in to hear Gautam’s adv
