Data: Poklad, nebo peklo

By AdastraBusiness Technology Management

Data: Poklad, nebo peklo episodes

April 09 82: "31,000 customers have adopted Fabric in the last two and a half years," says Tamer Farag, Global Fabric Partner Lead, Microsoft
19 min
March 1080: "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, SageMaker, secure integrations) with real wins such as demand forecasting, planogram automation, and Adastra’s Mark Anthony Group solution that scales assortment optimization and auto-generates seller scripts, plus quick-win assistants, cost controls, and an enterprise AI program with clear budgets, ownership, and accountability across product, employee, and customer use cases.
What does it take to move from quick wins with Amazon Q to custom, domain-aware agents on Bedrock that scale across the enterprise?
When is “good enough” data enough to start, and how can AI assistants surface gaps while improving data quality over time?
Which operating model and risk-based guardrails help leaders control cost and compliance while accelerating adoption?
25 min
February 2679: “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. He shows how AWS provides access to top models, better value, responsible AI practices, and secure ways to connect your systems. Examples include instant insights from manufacturing data and Breakthru Beverage moving hundreds of servers, plus quick AI helpers like a Sales Coach and a Legal Assistant. He also shares how to keep costs in check and set up a company-wide AI program with clear budgets and accountability.
What does it take to move from quick wins with Amazon Q to custom agents on Bedrock that scale across the enterprise?
When is “good enough” data enough to start, and how can AI assistants surface gaps while improving data quality over time?
Which operating model and risk-based guardrails help leaders control cost and compliance while accelerating adoption?
17 min
February 0577: “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 migrating 300+ services to AWS, why the data layer is the most critical, risk-based guardrails, and quick-win pilots like Legal GPT and an AI Sales Coach.
What does it take to build a foundation that learns fast and scales AI beyond hype?
When is “good enough” data enough, and how can AI expose and fix the gaps?
Which operating model and governance enable adoption without slowing delivery?
48 min
February 0578: "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 software‑defined vehicles and the car as a proactive companion, how GenAI is collapsing mainframe refactoring from years to months, and what it takes to move beyond pilots to production. Kratz shares lessons from Amazon’s own “shop floor” in its fulfillment centers, why the cloud is ready for OT, and why critical thinking and change management matter as much as technology. He also covers autonomy at scale, the equalizing effect of AI for SMBs and OEMs alike, and the “better together” role of SIs like Adastra.
How do OEMs and suppliers work backwards from outcomes to deploy GenAI in real production?
What makes the factory floor ready for cloud and AI, and how do you ensure resilience?
How does mainframe modernization unlock microservices and accelerate transformation?
Which ecosystem partnerships and governance practices deliver value without slowing execution?
Is AI the great equalizer across company sizes, and how should leaders manage the cultural shift?
32 min
January 2676: 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 Power Platform a kvalitě dat.
33 min
January 1382: 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”?
34 min
January 12 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
31 min
January 0774: 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 adoption without slowing execution?
Learn more about: GenAI, Adastra AI
29 min
October 14, 202573: 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?
28 min