Data: Heaven or Hell? (Adastra Podcast)

90: “The Best Airlines Will Use AI to Build Trust, Not Just Revenue,” Says Shingai George, Aviation Expert

Shingai George, Aviation Consultant specializing in data analytics, AI, and sustainability, shares how modern data platforms, AI-driven decision-making, and shared data ecosystems are helping the aviation industry adapt

89: „Bez AI nepůjde změny ve školách škálovat“, říká Tomáš Kaplan z NF Eduzměna

Jak se měří dopad systémové změny ve vzdělávání? Proč je těžší pracovat s kvalitativními rozhovory než s tabulkou počtů škol a učitelů? A jak může AI pomoci školám doporučovat vhodné formy podpory podle jejich konkrétníc

88: "Context is King," Says Chris Peart, Snowflake

Chris Peart, Sales Leader at Snowflake Canada, shares how unified data, governed context, and agentic AI are reshaping how enterprises turn information into action. He explains why "context is king" as frontier models be

87: "Where Not to Use AI Matters More Than Where to Use It,” Says Brad Freels, Microsoft

Brad Freels, Azure Data and AI Specialist at Microsoft, shares how meeting customers where they are, building AI Centers of Excellence, and diving in without waiting for "perfect data" are reshaping how enterprises unloc

81: “The technology is good enough. The real hurdle now is people, fear, and change management,” says Shannon Bell, CIO, OpenText

Shannon Bell, EVP, Chief Digital Officer and Chief Information Officer at OpenText, shares how “information first” thinking, simplicity, and agentic AI are reshaping how large enterprises work. She explains why most ente

84: "Start with Business Challenges, Not Solutions," Says Justin Rister, Microsoft

Justin Rister, Senior Cloud and AI Specialist at Microsoft, explains why leaders should start with business pain points, not technology. He shares how Fabric unifies the analytics stack for teams of all skillsets, why Da

86: "31,000 customers have adopted Fabric in the last two and a half years," says Tamer Farag, Microsoft

Tamer Farag, Global Fabric Partner Lead at Microsoft, shares how the fastest-growing analytics platform in the world is helping 31,000 customers unify fragmented data estates and unlock AI value. He highlights why you do

82: Risk in AI-Developed Cancer Drugs with Jon Steffey, Tolmar

83: AI není zkratka k lepšímu reportingu. Je to spíš test připravenosti vašich dat, říká Kristýna Merňáková (Adastra)

Jak připravit data, tak aby AI skutečně pomáhala a neškodila? Jak funguje „chat with your data“ v praxi? A proč bez kontextu AI odpovídá špatně, i když má správná data? Zjistěte více o řešení Power BI .

80: "Helpful, not creepy: personalization that earns trust," says Kevin McCurdy, Global CPG Partner Lead, AWS

Kevin McCurdy, Global Partner Lead, Consumer Goods, AWS, shows how Gen AI, trusted data, and risk-based guardrails turn experiments into repeatable CPG value. He highlights AWS and partner capabilities (Amazon Bedrock, S

79: “Good enough to start, governed enough to scale," says Rehan Shah, AWS

Rehan Shah, General Manager and Head of Channel and Partner Sales for US Greenfield at AWS, explains how the right mix of AI tools, trustworthy data, and strong controls turns early AI trials into real business results.

78: "The car is becoming a smartphone on wheels, an extension of your living room," says Chris-Markus Kratz, AWS Global Director of Automotive and Manufacturing

Chris‑Markus “CMK” Kratz, AWS Global Director of Automotive and Manufacturing, explains how outcome‑first, customer‑obsessed transformation and ecosystem partnerships are reshaping the industry. He details the shift to s

77: “Think of it as a three-layer cake: platform, data, AI,” says Glenn Remoreras, CIO, Breakthru Beverage Group

Glenn Remoreras, EVP, Chief Information Officer at Breakthru Beverage Group, shares how a cloud-first “platform, data, AI” architecture and executive-led AI readiness turn market pressures into value. He highlights migra

76: Data pomáhají lidem z dluhů. Digitalizace mění práci dluhových poraden (David Borges, Člověk v tísni)

Jak dlouho trval vývoj a rollout řešení? Proč byl pilot klíčový pro přijetí mezi poradci? A jaké další procesy chtějí v Člověku v tísni digitalizovat dál – od komunikace s finančním arbitrem až po soudy? Více o řešeních

82: AI makes no sense without customer impact. Implementing it just for the sake of technology is a dead end (Jan Vacek, DHL)

How do you set up an AI strategy in a large organization? Why is security more important than speed? And how do you prevent AI from turning into an uncontrolled “agent zoo”?

75: "It’s not about replacing people—it’s about empowering people," says Kevin Harmer, Chief Cloud Officer at Adastra

Learn more about: Adastra AI

74: Don’t wait for perfect data—start, then improve (Sam Wong, Mark Anthony Group)

What does it take to build an incubator that learns fast and delivers real value? When is “good enough” data enough—and how can AI expose and improve the gaps? Which operating model and governance practices drive adoptio

73: Gorillas with Digital Wallets: How AI Helps Understand the Needs of Other Species (Jonathan Ledgard, Tehanu)

How can artificial intelligence help protect biodiversity? Will we ever objectively understand what is in the “interest” of other species? And what happens when the interests of different species collide?

71: The Future of Data Platforms? SaaS and AI, says Adam Wojtkowski from Snowflake

How does Snowflake work with AI models to keep data in a secure environment Why is going back to on-prem solutions no longer an option? And why does Wojtkowski believe SaaS and AI will dominate the future of data platfor

72: Fabric unifies data work: one version for reporting, SQL, and AI (Lars Andersen, Microsoft)

What use cases are companies solving with Fabric most often? How can organizations start with smaller projects and scale them to an enterprise level? And why does Andersen believe it’s always worth building new solutions