Software Efficiency Gives Infrastructure Teams Another Lever Beyond Adding Capacity
Janne Kalliola, Founder of Coonti, argues that software waste compounds across the technology stack and becomes more costly as AI scales.
Future of Data Management
The future of data management—lakehouse, data fabric, governance, real-time pipelines, and unstructured data at AI scale.
As AI Uncouples Data From Applications, Storage Becomes The Foundation For Sovereign AI
Prakash Darji, GM of Digital Experience at Everpure, on why data primacy and corporate sovereignty are the new foundations of enterprise architecture.
Small Modular Reactors Turn Data Center Operators Into Owners Of Their Own Generation
Husam Mohammed, MEP Design Director at Jacobs, on why the campuses being designed now are expected to produce their own power, water, and cooling on site.
Tokenized Finance Turns Data Quality Into A Real-Time Systemic Risk Control
Grace Wu, former Head of Product and Account Data Asset at HSBC, explains why stablecoins and tokenized assets are forcing financial institutions to redesign enterprise data architecture around real-time trust, governance, and accountability.
Restore Testing Gives Database Teams Proof Their Recovery Plan Works
Mariyan Clement, Database Architect at IBM, explains why monitoring a backup job proves nothing about recovery, and why he destroyed his own database to find out what a restore really involves.
Why Capital Markets Firms Are Rethinking Data Infrastructure for Production AI
Everpure's Mike Russo and Richard Galvez on the orchestration, governance, and resilience gaps that separate AI experimentation from production in capital markets.
Kubernetes Becomes The Enterprise Standard As Storage Catches Up To AI Demand
Greg Muscarella, GM of Portworx at Everpure, explains why storage, not compute or networking, is the constraint holding enterprises back as Kubernetes absorbs virtualized, containerized, and AI workloads onto a single platform.
As The AI Model Becomes A Commodity, Enterprise Data Becomes The Moat
Jayashankar Attupurathu, Technology Strategy Advisor to Boards and CXOs, on why the golden source, the pipeline, and sovereignty rules decide what a model can do.
Data Intelligence Becomes The Dividing Line For Enterprise AI Maturity, Says One Of Cisco's Field CTOs
Bogdan Muraru, a Field CTO working with UK enterprises, argues that AI maturity now shows up in six-month business cases, sovereign data fabrics, and the unsolved problem of agent identity rather than in pilot counts.
Energy Companies Once Competed on Assets and Now Compete on Data Quality
Arnab Ray, a Product Owner at Shell working in energy trading data, traces how two decades of market crises turned regulatory reporting into the data foundation that algorithmic trading and AI now run on.
Digital Twin Pilots Fail When Organizations Rush Past the Data Foundation
Abdourahmane Tahir, Head of Digital Services at Applus, explains why operational digital twins depend on rebuilding fragmented asset information into a governed, connected data layer before anything else.
Government Missions Require Mission-Ready Data
Katherine Hennessey, Head of U.S. Government Strategy at Everpure, explains why federal AI adoption depends less on model selection and more on modernizing the aging data infrastructure, storage architecture, and interoperability frameworks.
Data Architecture Takes Center Stage As Enterprises Build For Production-Ready AI
At Accelerate 2026, a Bloomberg Businessweek Radio broadcast surfaced a consistent diagnosis from CTOs, product leaders, a CFO, and a pharmaceutical platform engineer: the data layer is what separates AI experiments from AI that works.
The Federal Government's AI Problem Is Really A 50-Year-Old Data Architecture Problem
For decades the public sector has called data its most strategic asset, even as the systems treat data as an afterthought. AI is changing that, and in government what's at stake is public trust.
Industrial AI Readiness Starts at the Sensor and Most Organizations Are Not There Yet
Oliver Inseal, Divisional NPD Engineering Manager at Parker Hannifin, explains why industrial AI is only as trustworthy as the physical sensor producing the data underneath it.
How Certified Data Is Eliminating Duplicate Pipelines Across Enterprises
Gangadhar Thumu, Lead Data Engineer at AT&T, breaks down why the hidden cost of data platform modernization is the duplicate work happening across business units that lack shared visibility.
The Paradox Of Simplicity: Maintaining A Data Platform Is Harder Than Building It
Manoj Kumar Anugu, Senior Data Platform Engineer at COUNTRY Financial, explains how steady discipline keeps a data platform from sliding into a costly mess as it scales.
Production AI Demands Statefulness That Might Require a Whole New Approach to the Inference Layer
An Intel AI engineer and the CEO of a YC-backed inference startup are converging on the same conclusion: inference is becoming a state management problem, and the engineering required to solve it has been around for decades.
Industrial Leaders Turn Unified Data Pipelines Into A Scalable AI Advantage Across Plants
Jan Hoscan, VP and Head of Industrial at Everpure, argues that industrial AI succeeds or fails on whether companies can turn fragmented IT and OT data estates into unified, governed, AI-ready infrastructure.
How AI Can Turn Data Pipelines Into Supply Chain Attack Surfaces
Mohamed Azard Rilvan, Cybersecurity Consultant at Verizon Enterprise Solutions, explains why ETL is now a runtime environment, why inherited risk from third-party code will not go away, and why internal documentation matters more than any new tool.
Enterprises Trade Big Data Cleanups For AI That Resolves Debt Incrementally
Kjersten Moody, CEO for North America at Elai, explains why accumulated data debt is the primary bottleneck for enterprise AI and why agentic approaches are replacing the brute-force fixes that came before.
Why Media Companies That Collect Data Without Feedback Architecture Are Just Building Graveyards
Hemant Soni, Digital Product Delivery Leader at Capgemini, explains why the organizations pulling ahead in media and telecom are not the ones with the most data, but the ones that close the loop on signals fastest.
Why Financial Services Data Engineers Choose Orchestration Over Model Power
Ajinkya Chatufale, Lead Data Engineer at Barclays, on why enterprise AI reaches production only when teams orchestrate use cases, models, agents, protocols, and human review as one system.
Building Meaningful Datasets for AI Is a Change in Culture, Not Technology
CTO and Chief AI Officer Sean G Miller discusses how AI leaders are building meaningful data sets with historical context, and how this task is best understood as bringing technology back into an organization's business culture.
The Paradox of `Unforgiving Agents`: How One Databricks Tech Lead Raises the AI Trust Floor With Embedded Governance
Sandipan Bhaumik, Data and AI Technical Lead at Databricks, explains why AI agents that consume bad data without question are forcing governance into the architecture itself.
Iceland's Geothermal Grid Gives Financial Firms a Renewable Path to Sovereign AI Infrastructure
Ryan Ballantine, Director of Product Management at Options Technology, explains why Iceland's geothermal energy, transatlantic positioning, and geopolitical stability make it an optimal location for sovereign AI infrastructure in financial services.
Are Most Data Governance Problems Just Systems and Delivery Problems In Disguise?
Rajesh Ramaswami, Independent Advisor and former technology leader at Microsoft and Accenture, explains why most data governance problems originate in system design and delivery, and why engineering discipline is the only fix that holds.
Unpredictable Cloud Costs and Physical Resiliency Failures Are Driving Enterprises Back to Hybrid Infrastructure
Debjani Roy, a former Senior Director of Data and AI at BT, explains how unbudgeted price hikes, runaway egress fees, and catastrophic infrastructure failures are pushing large enterprises toward private sovereign clouds built on open-source foundations.
Everpure VP Champions AI-Aware Platforms as Monolithic Software Models Fade
The era of rigid, costly enterprise software is ending. Kaycee Lai, VP of AI & Analytics at Everpure explains how AI is driving a new model where value lies in the data platform, not the app, and why enterprise-grade standards for AI are now essential.
Shared Data Ownership Turns Governance from an IT Afterthought Into an AI Prerequisite
José Siles, Data Engineer at Nestlé, explains why data governance keeps failing and why the fix has nothing to do with the tools organizations already have.
AI Leaders Prioritize Traceable Data As Models Move Into Production Systems
Sue Eze, an independent data governance consultant, explains why production-ready data is defined by traceability and accountability, not model performance, and why the gap between the two only surfaces when decisions need to be justified.
AI Governance Matures as Enterprises Build Guardrails, 'Commit Gates,' and Embedded Controls
Ema Gutierrez, VP of AI Governance at Kira Tech AI, emphasizes embedding guardrails and commit gates directly into AI system design.
When Enterprise AI Fails, It's Often Not the Model, but a Mess of Data Lurking Beneath
Ravish Kumar of BCS Technology International makes the case that data discipline, not model quality, determines AI success.
How Data Reduction Software Shields Cloud Budgets from Hardware Price Volatility as AI Surges
As AI demand causes cloud costs to spiral, Dan Kogan, VP of Cloud + New Products at Everpure, explains how data reduction software cuts bills and unlocks funds for innovation.
As AI Reshapes Legacy Stacks, Unified Data Becomes the Key to Combatting Complexity Sprawl
Nirav Sheth, VP of Worldwide Pre- and Post-Sales Engineering at Everpure, explains how integrated security and operational simplicity are shaping the next generation of enterprise data management.
How Managing Datasets Instead of Storage is Becoming the Deciding Factor for AI Success
Chadd Kenney, VP of Product Management at Everpure, lays out why AI only works at scale when enterprises move beyond storage and manage datasets with context, policy, and control.
Enterprise-Ready, Not Just AI-Ready is the New Mandate for Success
Kaycee Lai, VP of Enterprise AI and Analytics at Everpure, discusses how collapsing manual data workflows is essential for real-time, AI-driven decision-making.
‘Simplicity Is What Lets You Be Brave’: Options Technology VP Says Streamlined Stacks are the New Competitive Edge
As enterprises race to scale AI, Options Technology VP Andrea Moccia explains why simplicity, not complexity, is becoming the decisive factor in turning infrastructure investment into real business outcomes.
Protecting Digital Infrastructure In An Era of Platform Concentration
Suresh Sankaran Srinivasan of Axiata explores how to build resilient systems, navigate digital risk, and stay ahead of crises that bridge the physical and digital worlds.
When Reactive Patchwork Fails To Fix Flawed Architecture, Structural Data Weakness Must Be Met Head-On
Vijay Kumar, Data Architect at Bizmetric, explains that most enterprise data failures stem from weak architecture that blocks reliable insight and long-term AI value.
Making the Case for Data Spaces to Solve AI's Context Challenges in Isolated Systems
Jayadev Vasantham, CTO of IndustryApps, shows how data spaces offer a workable path beyond centralized models that leave AI blind to meaning and context.
Enterprise AI Requires Unified Data Architecture Across Edge and Cloud, Says Everpure VP
Nirav Sheth, a VP at Everpure, explains why AI and rising costs are forcing a shift to unified, cloud-smart hybrid architectures.
HSBC Head of Product Data Reimagines the 'Single Source of Truth' as a Federated Ecosystem
Grace Wu, Head of Product Data at HSBC, explains why the traditional single source of truth must evolve into a federated ecosystem to scale enterprise AI.
Exploring Multidimensional Data Structures To Improve Pattern Detection: With IBM Sr. Data & AI Architect
Saeed Kasmani, a Senior Data & AI Architect at IBM, explains how MIT’s latent-perception research reveals AI’s architectural security gaps.
How One Public Sector AI Advisor Approaches Sovereignty To Turn Foreign Tech Into Domestic Value
Maria Luciana Axente, CEO at Responsible Intelligence, explains why sovereign AI means creating domestic value from foreign technology to improve an entire nation.
Major Cloud Outages Push Enterprises Toward Hybrid Resilience
Oluwaseun Odeyemi, a Data Architect at the UK Health Security Agency, explains how to build a hybrid model for future resilience against major cloud outages.
Inside the Hidden Labor Cost of Custom Cloud Security Architectures
Philip Asiala, a Senior Principal Enterprise Architect at SAIC, explains how company culture dictates cloud security architecture and its costs more often than technology.
In the Autonomous AI Era, Zero Trust is Becoming an Architectural Mandate
Kishore Vutukuri, an Enterprise Architect at EY, explains why Zero Trust is a mandatory architecture for securing enterprises in the age of AI.
OpenAI Inks $38 Billion AWS Deal in Pivot from Microsoft
OpenAI signs a $38 billion, seven-year deal with Amazon Web Services for AI model training, marking a strategic pivot from its exclusive reliance on Microsoft.
A New, Intuitive Blueprint for Financial Data Architecture Prioritizes Business Outcomes Over Scale
Subhash Kommuru, VP of Enterprise Architecture at Wells Fargo, explains how a new blueprint for data architecture can help leaders avoid repeating costly mistakes with AI.
A Northern Trust Senior VP Defines the New Framework for AI Governance and Trust
Armel Roméo Kouassi, a SVP at Northern Trust, explains why the rise of AI in global finance is creating new risks and how a new approach to governance can help.
At Advertising Week 2025, Top Analytics Leaders Champion Sustainable Data Quality Over AI Hype
Aarushi Khera, a Manager of Advanced Analytics at Walmart Connect, explains why Advertising Week 2025 highlighted a complex reality for the industry around data quality and governance.
Tech Leaders Overhaul Data Governance to Unleash AI and Outpace Rivals
Dr. Ganesh Selvaraj, a consultant in Data, AI, and Decision Intelligence, explains how a new wave of leaders is redefining governance as a strategic accelerator for enterprise AI innovation.
University of New Haven’s Innovation VP Has a Plan to Overhaul the Academia-Industry Partnership for the AI Era
Paul S. Lavoie, the University of New Haven's VP of Innovation, explains why a broken partnership between industry and academia creates a knowledge gap that slows AI adoption in manufacturing.
Inside the Māori-Led Movement Redefining Data Sovereignty for New Zealand
Dr. Karaitiana Taiuru, a Māori Data Sovereignty and AI Ethics expert, explains how Indigenous-led data governance frameworks can help manage the risks of data globalization.
Banks Say 'Explainable Velocity' Backed by Real-Time Data is Key to Balancing Speed and Trust in the Age of AI
Rohit Kela, Industry Consulting Manager at NTT DATA, explains why financial firms chasing processing speed risk deploying AI systems that are fast but not trustworthy.
The Next Phase of Financial Innovation Starts with Smarter, Data-Literate Regulation
Gary Palmer, CEO of Payall Payment Systems, explains why regulators often struggle to regulate the financial industry and how the challenge introduces new risks.
A Seamless Experience Erodes Trust in Finance, but 'Responsible Friction' Builds It Back
Olivia Hyde, co-founder of Prompts to Profit, explains how an obsession with finding AI use cases can create inefficiencies for financial institutions that deploy enterprise AI.
At Law Firms, AI Success is Defined Through Security, Governance, and Irreplaceable Human Oversight
Scott Cohen, EVP at Lineal, explains why law firms should focus on change management and human workflows for successful enterprise AI.
How Data Intelligence Can Help Stop the Chase for Shiny Objects in AI
Gary Nakanelua, Managing Director of Product & Innovation at Blueprint Technologies, on the biggest threats to AI adoption.
How Developers In The C-Suite Are Fixing Healthcare's Foundational AI Flaws
Eric Snyder tech leader at the University of Rochester's Wilmot Cancer Institute, on healthcare's AI ambitions, "Innovation Theater", and cultural paralysis.
Solving the Hyperscaler Heat Crisis: Inside One Company's ‘Picks & Shovels’ Play for the AI Boom
Ian Parker of facilities-level cooling company Healixa on energy-efficient cooling solutions for hyperscaler data centers.
Why a First-Party Data Strategy Matters More than the 'Best Model' for Enterprise AI
Vinay Mummigatti, the EVP at Skan and former Chief Automation Officer at LexisNexis, on why a first-party data strategy beats having the latest models.
Data Cleaning ‘Janitorial Work’ is Key to Unlocking Life Sciences Breakthroughs
Ming "Tommy" Tang, Director of Bioinformatics at AstraZeneca, discusses data quality challenges in bioinformatics and how they stall scientific discovery.
Why Enterprise AI Strategies are Collapsing After 'Decades of Data Hoarding'
Kolby Beck, Senior Solution Architect at Kimball Equipment Company, on why the rush to adopt AI often exposes significant structural issues for enterprises.
How Sovereign Infrastructure Could be Europe's Answer to US Tech Dominance
Gilles Closset, Global AI Ecosystem Leader at OVHcloud, discusses sovereign AI and the France Travail partnership.
Walled Gardens in a Borderless World: How Geopolitics are Undermining Open Source
Mitch Ashley, VP and Practice Lead at The Futurum Group, discusses conflicts in sovereign software practices and open source development