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$NOW CEO Bill McDermott says AI can identify problems but it cannot fix them. ServiceNow sits on 80B enterprise workflows across legacy systems and acts as the “last-mile” execution layer.

Shay Boloor

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137,777 views • 3 months ago •via X (Twitter)

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$NOW CEO Bill McDermott says the market is pricing in fear that LLMs could replace large parts of enterprise software. But in an AI economy where companies need to operationalize agentic AI safely, ServiceNow looks more like the control layer for governance, context, routing and oversight. The market is still struggling to separate software that gets disrupted by AI from software that becomes more valuable because AI needs exactly that control layer. I think ServiceNow sits much closer to the second bucket.

$NOW CEO Bill McDermott says the market is pricing in fear that LLMs could replace large parts of enterprise software. But in an AI economy where companies need to operationalize agentic AI safely, ServiceNow looks more like the control layer for governance, context, routing and oversight. The market is still struggling to separate software that gets disrupted by AI from software that becomes more valuable because AI needs exactly that control layer. I think ServiceNow sits much closer to the second bucket.

Shay Boloor

264,328 views • 2 months ago

At #Knowledge26, our CEO Jensen Huang and ServiceNow Chairman and CEO Bill McDermott unveiled the next chapter of enterprise AI. Through Project Arc and Vibe Coding, we are integrating the NVIDIA AI Factory into the ServiceNow platform to turn complex intent into seamless action.

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"We are a growth company," ServiceNow Chair and CEO Bill McDermott says while discussing the company's first-quarter earnings on "Bloomberg Open Interest"

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“‘The World Works with ServiceNow’ “It isn’t a tag line - it’s a HARD line.” Listen as $NOW CEO Bill McDermott tries to rally the troops.

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🚨 ServiceNow CEO Bill McDermott just dropped this on the AI hype: “Most businesses don’t want to build workflow software for everything internally. They want one responsible AI Control Tower.” ServiceNow is becoming the fabric connecting every hyperscaler, every LLM, systems of record and now full security (cybercrime = $1 Trillion/month problem). True agentic enterprise is here: MoveWorks, VZA identity, Armis OT/security. Integrated major moves in just 20 days. Jensen Huang ( $NVDA CEO) approves, they’re teaming up on the agentic future. 2030 Price Target: $1,200 – $2,000+ per share as they hit $30B+ revenue and own the enterprise AI operating system. While others talk apocalypse, ServiceNow is building it. $NOW to the moon. Who’s loading up?

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Sequoia partner Grady Buchanan says systems of record SAAS like Workday, Salesforce, and ServiceNow are safer from AI. The risk sits with workflow apps in the middle, as AI agents become the new layer that does the work on top of core data.

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$NOW CEO Bill McDermott says ServiceNow can become a $1T company by 2030. He bought $3M worth of shares at $107. $NVDA CEO Jensen Huang says it could 100x. President Trump bought $5M. Anthropic says it’s essential infrastructure. OpenAI is integrating deeply with it. $AMZN, $MSFT & $GOOGL are all expanding partnerships. And vibecoding an alternative would probably cost 10x more than just using ServiceNow. Is ServiceNow the easiest buy in the market?

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1,595,683 views • 1 month ago

Current AI cannot solve difficult, real-world problems. The path to AGI is a focus on improving reasoning systems, multi agent workflows, and coordination.

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What happens when AI finds vulnerabilities faster than teams can fix them? Nikesh Arora breaks down how AI could surface long-hidden weaknesses across enterprise systems faster than they can be remediated.

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$PLTR CEO Alex Karp argued that AI alone is not enough. The real value comes from combining models with domain expertise, workflows, and operational execution. His view is that enterprise AI is ultimately about solving business problems, not maximizing token usage. As models become commoditized, the winners may be the companies that combine taste, data, and execution rather than compute alone.

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$SPCX spending $60B on Cursor validates the idea that real AI value accrues to the application layer that owns the workflow, proprietary data loop and enterprise distribution. $NOW is building exactly that as the orchestration layer for enterprise AI agents across business workflows. The Cursor deal is a reminder that the market will pay massive premiums for software that owns where work actually happens.

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Watch our Founder and CEO Jensen Huang and ServiceNow President and COO CJ Desai talk about the recent partnership, the future of #AI as an industry, and how #generativeAI models will transform enterprise #IT operations. Watch the entire video:

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WHERE THE ENTERPRISE AI STACK IS BEING BUILT 1. $PLTR building the orchestration layer of the AI economy through the control systems enterprises need before models can take real-world actions backed by a Rule of 40 score of 127 2. $CRWD, $PANW, $ZS & $RBRK building the security layer of the AI economy across endpoint, identity, Zero Trust & cyber recovery as every new agent, machine identity & AI-generated workflow expands the attack surface 3. $NET building the connectivity layer of the AI economy through the internet control plane that agents, APIs & inference traffic must move across in real time, with Cloudflare sitting behind over 20% of the web 4. $SNOW & $MDB building the data layer of the AI economy through the clean, structured, production-grade enterprise data systems that make AI usable inside real applications and workflows

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397,599 views • 2 months ago

General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.

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AI agents need a completely different execution surface than humans do humans can wait between clicks. agents can't with PAYMENT INTENTS, agenta can make multiple queries across multiple workflows, across multiple apps, and execute them instantly & atomically only possible on Sui

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$NVDA CEO Jensen Huang says “software companies aren’t dead” because AI agents still need an application layer to process, orchestrate and turn tokens into real workflows He also highlighted $PLTR, $CRWD and $NOW as partners helping bring agents into production.

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237,313 views • 1 month ago

Introducing Zams: The UI layer for enterprise AI agents. As AI agents get smarter, the real skill isn’t doing the work—it’s knowing how to orchestrate them. We built Zams to solve 3 problems holding AI agents back.

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40,302 views • 1 year ago

Ali Ghodsi, the cofounder and CEO of Databricks, says Zoom has a massive chance to build an AI-first product, that could seriously disrupt the traditional enterprise SAAS. Because it sits on the largest datasets of meeting videos and transcripts. The big pain in enterprise software is data entry and coordination. Zoom already sits on the raw input: every customer call and internal meeting, plus the video, audio, and transcript. If Zoom can reliably pull out decisions, context, and action items, then write them back into the right system of record automatically, as an AI-first workflow layer, it becomes the front door for work. That would replace lots of separate SAAS tools that exist mainly to collect notes and updates. --- Video from 'Bg2 Pod' YT channel (link in comment)

Ali Ghodsi, the cofounder and CEO of Databricks, says Zoom has a massive chance to build an AI-first product, that could seriously disrupt the traditional enterprise SAAS. Because it sits on the largest datasets of meeting videos and transcripts. The big pain in enterprise software is data entry and coordination. Zoom already sits on the raw input: every customer call and internal meeting, plus the video, audio, and transcript. If Zoom can reliably pull out decisions, context, and action items, then write them back into the right system of record automatically, as an AI-first workflow layer, it becomes the front door for work. That would replace lots of separate SAAS tools that exist mainly to collect notes and updates. --- Video from 'Bg2 Pod' YT channel (link in comment)

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Trustless systems need trustless intelligence. Verifiable AI aligns AI execution with the guarantees blockchains already provide. Mentor Session #4 features Advait from OpenGradient (∇, ∇) on building verifiable AI systems. App layer FTW.

Trustless systems need trustless intelligence. Verifiable AI aligns AI execution with the guarantees blockchains already provide. Mentor Session #4 features Advait from OpenGradient (∇, ∇) on building verifiable AI systems. App layer FTW.

Capx AI

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HERE’S TODAY’S FOX BUSINESS SEGMENT • The “SaaSpocalypse” 2026: legacy SaaS gets repriced as the plumbing layer in an agentic AI stack • Where value is migrating in the Agentic AI Stack: orchestration, security, connectivity, and data • Cyber picks for the agentic era: $CRWD as the interaction layer for agents, $RBRK as the “undo button” for agents & $ZS as the control plane for agent traffic • Why AI systems can’t function without clean, well-organized data: $SNOW, $MDB • The enterprise AI bottleneck: nobody is better positioned than $PLTR sitting between cheap, powerful models & messy, valuable enterprise data • Picks-and-shovels winner in agentic AI: $NET

HERE’S TODAY’S FOX BUSINESS SEGMENT • The “SaaSpocalypse” 2026: legacy SaaS gets repriced as the plumbing layer in an agentic AI stack • Where value is migrating in the Agentic AI Stack: orchestration, security, connectivity, and data • Cyber picks for the agentic era: $CRWD as the interaction layer for agents, $RBRK as the “undo button” for agents & $ZS as the control plane for agent traffic • Why AI systems can’t function without clean, well-organized data: $SNOW, $MDB • The enterprise AI bottleneck: nobody is better positioned than $PLTR sitting between cheap, powerful models & messy, valuable enterprise data • Picks-and-shovels winner in agentic AI: $NET

Shay Boloor

191,754 views • 4 months ago