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PODCAST

DataFramed

Welcome to DataFramed, a weekly podcast exploring how artificial intelligence and data are changing the world around us. On this show, we invite data & AI leaders at the forefront of the data revolution to share their insights and experiences into how they lead the charge in this era of AI. Whether you"re a beginner looking to gain insights into a career in data & AI, a practitioner needing to stay up-to-date on the latest tools and trends, or a leader looking to transform how your organization uses

technology

All Episodes

51:43

#342 The Secrets to High AI Adoption with Stefano...

DataFramed ·

2026/01/19

AI tools are becoming part of daily work for more professionals than ever before, yet adoption rates vary significantly across functions and company sizes. What separates organizations that successfully integrate AI from those that struggle? How do psychological factors like identity and autonomy shape how workers respond to AI implementation? And what role does corporate culture play in determining whether AI becomes a source of innovation or a point of resistance?Stefano Puntoni is the Sebastian

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50:42

#341 Our Data Trends & Predictions of 2026 with...

DataFramed ·

2026/01/15

2026 is shaping up to be a pivotal year for data, AI, and how we work. From step-change improvements in foundation models to AI-native workflows reshaping careers, commerce, and education, the pace of change shows no signs of slowing. After revisiting and scoring their previous predictions, Richie, Jo, and Martijn turn their focus to what’s coming next in 2026.Building on last year’s discussion, we explore how AI will transform hiring and career progression, why personal AI tutors could become the

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39:17

#340 Reviewing Our Data Trends & Predictions of 2025...

DataFramed ·

2026/01/14

2025 was another huge year for data and AI. Generative AI continued to reshape how we work and interact with technology, with organizations moving beyond experimentation and pushing AI firmly into production. We saw major progress in foundation models, the rise of long-running AI agents, production-ready generative video, and wider adoption of synthetic data. At the same time, AI literacy, adoption, and ROI became central concerns for boards and executives, not just technical teams.This time last

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44:54

#339 Modern Analytics with Mike Palmer, CEO at Sigma

DataFramed ·

2026/01/05

Self-service analytics has been a goal for data teams for years, but recent advances in AI are accelerating progress in unexpected ways. The combination of natural language interfaces and spreadsheet-like tools is lowering barriers to data access across organizations. But how do you balance the freedom of self-service with the need for governance and accuracy? What skills do analysts need to work effectively with AI systems that don't always produce the same results twice? And when AI-generated

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58:51

#338 The New Paradigm for Enterprise AI Governance...

DataFramed ·

2025/12/29

AI governance is becoming critical as organizations deploy more intelligent systems across their operations. With predictions of over a billion AI agents entering the workforce in the coming years, traditional governance approaches simply cannot keep pace. How do you ensure your AI systems are using data responsibly without slowing down innovation? What happens when an AI agent makes decisions that were never explicitly programmed? And how do you build governance processes that scale alongside

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18:52

#337 DataFramed, Distilled. The Best Moments of 2025...

DataFramed ·

2025/12/22

2025 was the year AI stopped being a curiosity and started reshaping real work. From data analysts speeding up entire workflows in minutes, to managers learning how to lead hybrid teams of humans and agents, the pace of change has been relentless. Across DataFramed this year, one theme kept surfacing: AI isn’t replacing data professionals—it’s raising the bar on what good looks like. Skills are shifting, careers are becoming more fluid, and organizations are being forced to rethink how they build

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01:11:50

#336 From City Sewers to Sovereign AI with Russ...

DataFramed ·

2025/12/15

The concept of sovereign AI is becoming increasingly critical in our interconnected world. Nations and organizations are grappling with who controls the data, infrastructure, and technology that power artificial intelligence systems. But what does this mean for your work in data science and AI implementation? How do you navigate the complex landscape of data ownership when building AI solutions? As geopolitical tensions influence technology development, understanding the nuances of AI sovereignty

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01:02:45

#335 Rebuilding Trust in the Digital Age with Jimmy...

DataFramed ·

2025/12/08

The internet has transformed how we access information, but it's also created unprecedented challenges around trust and reliability. How do we build digital spaces where collaboration thrives and quality information prevails? What separates toxic online environments from productive ones? The principles of neutrality, transparency, and assuming good faith have proven essential in creating sustainable knowledge communities. But these same principles extend far beyond the digital realm—they're

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43:24

#334 The State of Data & AI with Tom Tunguz, VC at...

DataFramed ·

2025/12/01

The AI landscape is evolving at breakneck speed, with new capabilities emerging quarterly that redefine what's possible. For professionals across industries, this creates a constant need to reassess workflows and skills. How do you stay relevant when the technology keeps leapfrogging itself? What happens to traditional roles when AI can increasingly handle complex tasks that once required specialized expertise? With product-market fit becoming a moving target and new positions like forward-deployed

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44:40

#333 Creating an AI-First Data Team with Bilal Zia,...

DataFramed ·

2025/11/24

Data science leadership is about more than just technical expertise—it’s about building trust, embracing AI, and delivering real business impact. As organizations evolve toward AI-first strategies, data teams have an unprecedented opportunity to lead that transformation. But how do you turn a traditional analytics function into an AI-driven powerhouse that drives decision-making across the business? What’s the right structure to balance deep technical specialization with seamless business

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01:05:13

#332 How to Build AI Your Users Can Trust with David...

DataFramed ·

2025/11/17

The relationship between data governance and AI quality is more critical than ever. As organizations rush to implement AI solutions, many are discovering that without proper data hygiene and testing protocols, they're building on shaky foundations. How do you ensure your AI systems are making decisions based on accurate, appropriate information? What benchmarking strategies can help you measure real improvement rather than just increased output? With AI now touching everything from code generation

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58:24

#331 The Future of Data & AI Education Just Arrived...

DataFramed ·

2025/11/12

The future of education is being reshaped by AI-powered personalization. Traditional online learning platforms offer static content that doesn't adapt to individual needs, but new technologies are creating truly interactive experiences that respond to each learner's context, pace, and goals. How can personalized AI tutoring bridge the gap between mass education and the gold standard of one-on-one human tutoring? What if every professional could have a private tutor that understands their industry,

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55:37

#330 Harnessing AI to Help Humanity with Professor...

DataFramed ·

2025/11/10

Data storytelling isn't just about presenting numbers—it's about creating shared wisdom that drives better decision-making. In our increasingly polarized world, we often miss that most people actually have reasonable views hidden behind the loudest voices. But how can technology help us cut through the noise and build genuine understanding? What if AI could help us share stories across different communities and contexts, making our collective knowledge more accessible? From reducing unnecessary

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49:06

#329 Building Trust in AI Agents with Shane Murray,...

DataFramed ·

2025/11/03

Data quality and AI reliability are two sides of the same coin in today's technology landscape. Organizations rushing to implement AI solutions often discover that their underlying data infrastructure isn't prepared for these new demands. But what specific data quality controls are needed to support successful AI implementations? How do you monitor unstructured data that feeds into your AI systems? When hallucinations occur, is it really the model at fault, or is your data the true culprit

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42:37

#328 The Challenges of Enterprise Agentic AI with...

DataFramed ·

2025/10/27

The promise of AI in enterprise settings is enormous, but so are the privacy and security challenges. How do you harness AI's capabilities while keeping sensitive data protected within your organization's boundaries? Private AI—using your own models, data, and infrastructure—offers a solution, but implementation isn't straightforward. What governance frameworks need to be in place? How do you evaluate non-deterministic AI systems? When should you build in-house versus leveraging cloud services? As

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55:21

#327 Building a Sales and Marketing Capability for...

DataFramed ·

2025/10/20

The journey from startup to billion-dollar enterprise requires more than just a great product—it demands strategic alignment between sales and marketing. How do you identify your ideal customer profile when you're just starting out? What data signals help you find the twins of your successful early adopters? With AI now automating everything from competitive analysis to content creation, the traditional boundaries between departments are blurring. But what personality traits should you look for when

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56:52

#326 Is the Data Analyst Role Dying Out? with Mo...

DataFramed ·

2025/10/13

The role of data analysts is evolving, not disappearing. With generative AI transforming the industry, many wonder if their analytical skills will soon become obsolete. But how is the relationship between human expertise and AI tools really changing? While AI excels at coding, debugging, and automating repetitive tasks, it struggles with understanding complex business problems and domain-specific challenges. What skills should today's data professionals focus on to remain relevant? How can you

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43:13

#325 Using Data to Master the Cycles of Leadership...

DataFramed ·

2025/10/06

Leadership in data-driven organizations requires a delicate balance of technical expertise and human understanding. As businesses navigate unprecedented uncertainty in global markets, geopolitics, and technological change, the role of data as a source of truth becomes increasingly vital. But how do you create a culture where data informs decisions at every level? What separates leaders who merely collect data from those who leverage it to drive bold, transformative action? For data professionals

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58:36

#324 Using Behavioral Science to Hack Your Customers...

DataFramed ·

2025/09/29

Behavioral science is revolutionizing how businesses connect with customers and influence decisions. By understanding the psychological principles that drive human behavior, companies can create more effective marketing strategies and product experiences. But how can you apply these insights in your data-driven work? What simple changes could dramatically improve how your audience responds to your messaging? The difference between abstract and concrete language can quadruple memorability, and timing

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48:03

#323 The Evolution of Data Literacy & AI Literacy...

DataFramed ·

2025/09/25

Data literacy and AI literacy are becoming essential skills in today's digital landscape. As organizations collect more data and deploy AI solutions, the ability to understand, interpret, and make decisions with these tools is increasingly valuable. But how do we develop these skills effectively across an organization? What does successful implementation of data and AI literacy programs look like in practice? The journey to becoming data literate doesn't require becoming a data scientist—it's about

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167 results

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