Discover how AI supercharges the best low-code use cases in Pharma, CPG and Finance to take the next steps in enterprise digital transformation.
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Discover how AIoT creates a real-time nervous system: edge AI, digital twins, and predictive analytics for manufacturing, energy, and smart cities. Enable intelligent operations today!
The next wave of enterprise transformation is intelligent, not just digital. With low-code and AI, organizations now build and evolve applications up to ten times faster, while embedding intelligence…
Many of us believed digital transformation was so advanced that soon there’d be nothing left to digitize. Then reality set in. Core processes remained tied to slow, complex systems, innovation…
Article
AI-Assisted Software Development Process: Insights From an International Survey on AI Readiness & Adoption
The rapid advancements and adoption of GenAI is reshaping how software is being created. From code completion and documentation generation, to supporting decision making, such as exploring…
When I talk to clients, almost everyone tells me the same thing: “We already have a data platform, we are data driven.” On paper, that is usually true. In reality, it is more complicated.
Most supply chain control towers today focus on visibility and alerts. They collect signals and show what is happening, but they leave people to investigate root causes, assess business impact, and…
Ensuring AI requires integrating risk management, ethics, and accountability into organizational governance. Frameworks like ISO/IEC 42001 and emerging regulations such as the EU AI Act and NIST AI…
Before dashboards, before automated insights, before anyone called it “BI,” there was a baker. Every morning, they decided how much bread to bake. Not based on reports—but on experience and…
Before dashboards, before automated insights, before anyone called it “BI,” there was a baker. Every morning, they decided how much bread to bake. Not based on reports—but on experience and…
Choosing the right AI model is critical for success. Learn about key risks: unverified models, bias, API vulnerabilities, and version drift. Avoid common mistakes in your AI initiatives.
Article
How to Ensure AI Data Security in Enterprise Implementations: Data Risks and Mitigation Strategies
Discover critical data risks before deploying AI systems: data leakage, poisoning attacks, and quality issues. Learn how to mitigate these threats and deploy AI safely.
While bringing immense potential, AI solutions can also introduce hidden vulnerabilities. Learn about the most important ones and ways to deal with them.
Discover how advanced pricing in pharma leverages data, AI, and analytics to balance value, access, and commercial performance.
For years, Snowflake was seen primarily as a modern data warehouse: scalable, cloud-native, and designed to unify data silos. But over the past two years, a deeper shift has unfolded. One that…
Is your organization truly ready for AI, or just caught up in the hype? In this article, we outline five essential questions every business should ask before committing to AI adoption. From setting…
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