The enterprise data infrastructure benchmark report 2026
A global benchmark of enterprise data integration spend and its impact on AI readiness and ROI.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
The Value of Low-Code Development
The benefits of low-code development are well-documented: lower IT costs and greater business agility, being among them. Yet despite all the good press, many organizations are wondering if low-code development is worth all the hype. There's also pushback from data engineers and developers who believe that low-code software will take their places within organizations- which isn't the case. Underneath all the opinions, what does low-code development really bring to your business?
Salesforce as a Single Source of Truth
One of the biggest challenges that organizations face is making sure that all stakeholders and decision makers are operating with the same information. Units operating from different sets of facts end up making bad decisions for the enterprise as a whole.
Healthcare Data Analytics: Turning Clinical Data Into Better Patient Outcomes
Healthcare isn’t just about medicine anymore; it’s about data. Every test result, clinical note, scan, survey, wearable readout, and insurance claim adds to a growing pool of clinical data. But raw data doesn’t improve outcomes on its own. It has to be interpreted, connected, and acted on.
Stefano Puntoni on the Missing Piece in AI Strategy: Humans | The Data Chief
95% of AI projects fail. Is your "tech-first" mindset to blame? @wharton’s Stefano Puntoni breaks down the Human-AI gap with podcast host Cindi Howson on.
Stop AI Hallucinations at the Source | Simba Intelligence
AI isn't failing because the models are weak. It's failing because the data beneath them is broken. 88% of AI pilots never make it to production. 74% of companies haven't seen value from AI. The uncomfortable truth? These failures aren't about intelligence—they're about access, governance, and context.
A Wharton AI Research Leader's Formula for Responsible AI
Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact.
From Fear to Adoption: Stefano Puntoni on Fixing AI in the Workplace | The Data Chief
Is AI a tool or a threat? Wharton Professor Stefano Puntoni explains why "self-preservation mode" is killing AI adoption in the workplace. Puntoni joins Cindi Howson (The Data Chief host) & breaks down why AI isn't a strategy—it's a tool that requires a "meet in the middle" approach. To succeed, leaders must provide the vision and resources, while empowering workers to co-create the roadmap.
Ep 66 | Women Leaders in Technology: AI Agents Are Your New Team- Now What?
From econometrics to anthropology to leading roles at Salesforce, AWS, and Nextdoor, Tatyana shares how her background shaped a fundamentally different approach to leadership. Drawing on her unconventional journey, she explains why agentic AI is forcing leaders to rethink how they manage technology, shifting from systems to a focus on teams, culture, and governance. Together, Tatyana and Paul share their perspectives on.
Data Silos Could Be Your Biggest Cloud Liability
In an always-on industrial economy, fragmented data is a liability. Your analytics reports may look flawless, but if they’re built on data silos scattered across edge, core, and cloud, they’re built on a fault line. Data silos drive-up costs, distort the critical decisions meant to drive competition, and prevent organizations from reaching a state of data singularity — where data becomes unified, portable, and continuously usable for AI.