Recently, I was confronted with a novel situation regarding a conscientious objector to AI. While working to formulate goals for our AI strategic initiatives, a teammate informed me they would refuse to use it as part of their role. Digital transformation is difficult to achieve on its own, let alone when members of your own…
DetailsThe market for enterprise resource planning (ERP) systems is entering what some industry experts are calling an upgrade “supercycle,” fueled by a convergence of key factors. Grandview Research predicts global ERP software sales will grow 9.5% annually from 2026 to 2033. Fortune Business Insights puts the growth rate from 2026 to 2034 at 13%. And…
DetailsTaylor Paletta was glancing at two versions of the same customer-service interaction on her monitor. As director of support and digital success at the enterprise software company, Ninety, she could read the support chat in one window while watching the customer’s product session in another. The customer had already spent several minutes trying to solve…
DetailsIn cybersecurity, engineering velocity has become a competitive advantage. Threats and vulnerabilities evolve quickly, customer security needs keep changing and organizations that respond faster are more likely to stay ahead. Across the engineering organizations I have led in cybersecurity, SaaS, mobility and insurance, I have seen how lengthy development cycles and unnecessary waiting make it…
DetailsMicrosoft believes the era of enterprise agentic transformation is here, underscored by a slew of Microsoft Fabric announcements at the European Microsoft Fabric + SQL Community Conference in Barcelona today. “We’re going to talk a lot about the notion of how you prepare your data estate to really provide the context for AI agents to…
DetailsThe gap between simply running AI models and running them profitably is widening fast. Early production architectures can buckle under the relentless demands of multi-agent autonomous workloads and real-time fine-tuning. Moving forward requires a fundamental shift toward a unified AI factory infrastructure engineered to optimize token-per-watt efficiency. As organizations scale up multi-turn agentic workflows and…
DetailsCIOs across industries face a common bottleneck: data pipelines and compute architectures designed for traditional analytics cannot scale to handle large-scale artificial intelligence. As organizations accelerate their deployment of large-scale models across core corporate divisions, many data centers are straining under massive power requirements and complex multi-node orchestration. To overcome these constraints, leaders can look at the…
DetailsThe scaling of artificial intelligence has forced IT leaders to re-evaluate infrastructure. While public clouds offer rapid deployment for general applications, they introduce steep trade-offs for highly regulated, data-intensive workloads. Issues like high latency, unpredictable operational costs, and diminished data control complicate the development of proprietary intellectual property. To bypass these limitations, leading institutions are…
DetailsFor enterprise Chief Information Officers, the honeymoon phase of artificial intelligence is over. As organizations move past baseline experimentation and begin anchoring generative AI and agentic workflows into core operational stacks, we are hitting a collective wall. That wall isn’t defined by a lack of use cases or algorithmic capability; it is defined by the…
DetailsThe move from proof of concept or prototype to production is a common stumbling block for AI projects, and one that database services provider pgEdge is keen to help enterprises overcome. AI applications often start with developers reaching for Postgres because it gives them a database that can handle an application’s operational data while supporting…
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