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Garbage In, Garbage Amplified: The AI Feedback Loop Most Companies Miss
Most teams are using AI to summarize and connect internal data. Fewer realize they may be creating a feedback loop in the process. When AI-generated content gets stored alongside source material, it can quietly shift what is treated as truth. This blog article breaks down how it happens, why it matters, and one simple structural change that can prevent it.
Closing The Execution Gap For Store Modernization
Retail modernization often fails due to execution gaps, not strategy flaws. Overcoming technology debt, execution variability and AI expectations requires a holistic approach. By focusing on end-to-end lifecycle management, retailers can transform technology investments into growth drivers, ensuring seamless operations and enhanced customer experiences. Start small, assess and evolve strategically.
The AI Scaling Paradox: It's Not The Tech. It's The Operating Model.
AI's transformative potential in retail is hindered by outdated IT strategies and organizational resistance. While AI demands adaptive governance and cultural change, many initiatives stall due to fragmented data, leadership misalignment and unclear ROI. Success requires strategic coordination, robust infrastructure and a shift from pilot projects to core business integration.
Healthcare Technology Insights for 2025
The unprecedented speed at which regulatory and political changes are announced by our new federal administration is requiring healthcare executives to find balance between strengthening their core business and catching up with the AI train that has taken most industries by storm. The endless opportunities made possible by AI for reinventing healthcare are offset by the risks associated with increasing cyber threats and workforce challenges. Collectively, this promises to make 2025 a year like no other.
Security vs. Privacy, the Difference is Epic
Cyber teams need to understand the difference between security and privacy and apply them to every system in production.
Cisco's Intent to Acquire Splunk and the Evolution of Data-Driven Security
Cisco has revealed its potentially largest acquisition to date with the strategic intent to reshape the security information and event management (SIEM) sector by acquiring Splunk in an all-cash transaction valued at $28 billion.
Unleash Real-Time Agentic AI with Streaming Agents on Confluent Cloud with WWT
Confluent's Streaming Agents revolutionize AI workflows by unifying data processing with agentic AI on a single platform. Leveraging real-time context, they enhance decision-making and automation, ideal for dynamic enterprise applications. Discover how these agents transform data into actionable insights, driving innovation and efficiency in real-time fraud prevention, customer support and supply chain optimization.
Key Takeaways from DISTRIBUTECH 2025
The flagship transmission and distribution event provided insight into how electric utilities can stay ahead of growing energy complexities.
Successful AI and Automation Strategies for Life Sciences Organizations
Life sciences companies are leveraging automation and AI solutions to contend with a myriad of industry drivers that are reshaping the landscape.
AI to Cyber... Fuel to Fire
Artificial intelligence is fueling a rapidly escalating cyber storm, with malicious actors leveraging the technology to launch more advanced and destructive cyberattacks. But AI also empowers more robust cyber defenses if applied ethically. This post explores both sides of the AI arms race in cybersecurity.
Data as a Service for Utility Grid Modernization with the Advent of AMI 2.0
AMI 2.0 is modernizing the utility grid with real-time data and edge analytics, enabling utilities to reduce outages, optimize operations and improve customer experience through governed data-as-a-service architectures.
Is the Data Warehouse Dead?
The traditional enterprise data warehouse is evolving rather than becoming obsolete, adapting its role alongside advancements in AI technologies such as large language models (LLMs) and retrieval-augmented generation (RAG). These AI capabilities enable direct analytical operations on diverse data types, challenging the need for all data to be centralized and conformed in a warehouse.