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Rackspace Technology at ViVE 2026
2026-02-06 19:19:08| The Webmail Blog
Rackspace Technology at ViVE 2026 jord4473 Fri, 02/06/2026 - 12:19 Cloud Insights Rackspace Technology at ViVE 2026 February 17, 2026 by Rich Fletcher, Global Healthcare Marketing Director, Rackspace Technology Link Copied! Recent Posts Rackspace Technology at ViVE 2026 February 17th, 2026 Rethinking Security in the Face of the Skills Gap February 16th, 2026 Community Impact 2025: A Global Year of Giving Back February 13th, 2026 Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 Related Posts Cloud Insights Rackspace Technology at ViVE 2026 February 17th, 2026 Cloud Insights Rethinking Security in the Face of the Skills Gap February 16th, 2026 Culture & Talent Community Impact 2025: A Global Year of Giving Back February 13th, 2026 AI Insights Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 Cloud Insights How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 At ViVE 2026, Rackspace Technology explores cyber resilience in healthcare and how minimum viable hospital strategies help organizations sustain care during disruption. Moving beyond cybersecurity to enable the minimum viable hospital Healthcare leaders know cybersecurity is no longer just an IT concern. When systems go down, care delivery is at risk. That reality is driving a broader shift from traditional prevention-only security models toward cyber resilience. At ViVE 2026, Rackspace Technology will be on site to engage with healthcare executives and IT leaders navigating this shift. Our team will join industry peers to explore how resilient cloud foundations help organizations protect patient trust, meet regulatory demands and keep clinical operations running when it matters most. Cyber resilience as a healthcare imperative Hospitals are complex digital ecosystems. Clinical systems are only one part of the picture. Core operations such as facilities, staffing, supply chains and administrative services are just as essential to patient outcomes. As cyber threats increase, resilience becomes the true indicator of readiness. Cyber resilience is about maintaining a minimum viable hospital. By connecting security, cloud architecture and operations, healthcare organizations can sustain essential care and hospital-wide operations during disruption. This reduces impact to patients, protects operational continuity and reputation and ultimately helps prevent loss of life, transforming cybersecurity from a reactive function into an operational imperative. ViVE 2026 speaking session Melissa Pettigrew, Product Director, Healthcare, Rackspace Technology, will take the ViVE stage to explore this topic alongside Rubrik, sharing practical insights on how healthcare organizations can operationalize resilience without slowing innovation. Session details Title: Beyond Cybersecurity: Enabling the Minimum Viable Hospital Through Cyber Resilience Event: ViVE 2026 Location: Live from the CHiME Theater, Los Angeles Convention Center Date & time: Tuesday, February 24, 2026 | 12:50 PM1:20 PM Speakers Melissa Pettigrew, Product Director, Healthcare, Rackspace Technology Nathan Bahls, Sales Engineering Manager, Rubrik Calli Dretke, EVP, Chief Digital and Marketing Officer, CHIME The session will examine how cyber resilience strategies support continuity of care, align security with operations and help healthcare leaders rethink preparedness through the lens of patient impact. Meet the Rackspace team at ViVE Rackspace Technology will be sending a team of healthcare sales and product leaders to ViVE 2026. We will be hosting onsite meetings throughout the event in Meeting Room MC-655, located in the Meeting Cube Complex on the show floor. If you are attending ViVE and want to discuss cyber resilience, cloud modernization or healthcare-specific security challenges, we would welcome the conversation. Attend the session Tags: Private Cloud Cloud Insights Healthcare
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Getting Started With AI: A Practical Path Forward
2026-02-04 21:44:25| The Webmail Blog
Getting Started With AI: A Practical Path Forward jord4473 Wed, 02/04/2026 - 14:44 AI Insights Getting Started With AI: A Practical Path Forward February 5, 2026 By Madhavi Rajan, Head of Product Strategy, Research and Operations, Rackspace Technology Link Copied! Recent Posts Getting Started With AI: A Practical Path Forward February 5th, 2026 Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 How to Keep Azure Cloud Costs Under Control with Continuous Optimization January 26th, 2026 Using Agentic AI to Modernize VMware Environments on AWS January 22nd, 2026 Related Posts AI Insights Getting Started With AI: A Practical Path Forward February 5th, 2026 Cloud Insights Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 AI Insights Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 Cloud Insights How to Keep Azure Cloud Costs Under Control with Continuous Optimization January 26th, 2026 AI Insights Using Agentic AI to Modernize VMware Environments on AWS January 22nd, 2026 AI success starts with focus, not hype. This article outlines a phased approach to AI adoption, from improving operations to enhancing customer experiences and unlocking new revenue. Starting with AI can feel overwhelming. Headlines often focus on massive investments by global enterprises building or consuming frontier models at scale. For most organizations, however, that level of GPU-heavy infrastructure is neither required nor practical. If youre not running large-scale production models, the broader AI ecosystem doesnt need to dictate where you begin. Across the cloud landscape, organizations are at very different stages of AI adoption. While Fortune 100 companies invest billions in in-house development, many organizations in the Russell 2000 and beyond are focused on building practical capabilities that help them stay competitive. The question most leaders ask is straightforward: Where do I begin my AI journey? A useful way to answer that question is to think in phases. Most organizations move through three broad stages of AI adoption: operational efficiency, customer-facing experiences and new revenue streams. The level of investment required depends on several factors. These include compute, network and storage needs, the type of models in use, workload volume, organizational readiness and the phase of adoption. Understanding these variables early helps teams focus on use cases that deliver value without unnecessary complexity. Phase 1: Operational efficiency Organizations of all sizes struggle with inefficiencies caused by fragmented data and disconnected systems. These silos slow decision-making and can create costly errors. In some cases, businesses continue paying vendors months after a contract has ended simply because systems do not talk to each other. Using AI to improve operational efficiency across functions such as IT, finance, HR, supply chain, procurement and sales is often the lowest-risk, highest-impact starting point. These use cases are internal, measurable and closely tied to day-to-day productivity. The challenge is not a lack of data, but where that data lives. Critical information is often trapped in separate systems and supported by institutional knowledge that does not scale. When introducing AI, you need to be clear about intent. The goal is not to replace roles, but to remove friction so people can focus on higher-value work. Many established enterprises carry years of technical debt across product, operations, customer success and go-to-market systems. Simply buying an AI copilot rarely solves that problem. Off-the-shelf tools alone cannot bridge disconnected data or deliver meaningful ROI. Real value comes from applying AI on top of an organizations own data and processes. Consider a typical services business. Supply chain data lives in one system, customer records in a CRM and contracts in a homegrown application. The result is a collection of dashboards that offer limited insight into utilization, customer health or revenue trends. AI can act as an intelligence layer across these systems. It can surface which customers are growing, highlight utilization patterns and support scenario modeling. ROI becomes tangible through faster insights, fewer spreadsheets and better decisions. Speed to value also matters. How quickly do teams see results once a model is deployed? In one finance organization, analysts reduced time spent wrangling spreadsheets by roughly 40% with the help of an AI assistant. That time shifted to scenario modeling and analysis, where human judgment delivers the most value. Completing this phase gives organizations a clearer view of what their AI workloads require and how those capabilities can eventually extend to customer-facing value. Phase 2: Customer-facing experiences As AI matures, personalization becomes a key driver of customer retention. Buying AI tools does not equal adoption. AI must deliver specific business outcomes to matter. While automation can support customization, true personalization requires context, judgment and empathy. This applies across both B2C and B2B environments. In financial services, for example, some organizations use AI to assemble client intelligence that includes recent activity, potential opportunities and emerging risks. That insight allows teams to personalize interactions, anticipate needs and identify growth opportunities earlier. Continuous monitoring of customer consumption patterns helps organizations anticipate change. When paired with alerting and recommendations, customer-facing teams can deliver more relevant outreach, predict demand shifts and align offerings more closely to customer goals. This is especially valuable in subscription and recurring revenue models. With the right foundation, teams can enter every customer interaction better informed and more precise. Data, process insight and market context come together, enabling employees to move beyond routine tasks and focus on deeper, strategic engagement. Phase 3: Embedding AI into what you sell The first two phases help organizations improve how they operate and serve customers. The third phase is where AI becomes transformational, embedded into what you sell and directly driving new revenue. Success at this stage looks different by industry. In financial services, AI may streamline onboarding or fraud response while improving the customer experience. In other sectors, AI may become a differentiated product or service in its own right. This shift often requires new business models. Many AI-native companies tie pricing to outcomes rather than consumption alone. In these cases, AI is not just an internal capability, but a core part of the value proposition. Sustaining that value depends on culture and decision-making. AI influences the full lifecycle, from product development to billing and supply chain operations. Real impact only emerges when teams align across functions. While AI excitement dominated recent conversations, the next phase will be defined by how effectively you translate AI into practical execution and measurable outcomes. How Rackspace Technology can help Turning AI ambition into results requires the right foundation, governance and operational support. Rackspace Technology helps organizations design, deploy and manage AI solutions that align to real business goals, whether the focus is efficiency, customer experience or new growth opportunities. With deep expertise across hybrid cloud, data platforms and AI operations, Rackspace provides a structured path from experimentation to production. Learn more about how Rackspace supports AI initiatives here. Tags: AI Insights
Category: Telecommunications