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Yellow.ai Pitches Nexus EDGE to Automate Employee IT, HR Support

Share with your CIO Yellow.ai is betting that the next frontier in enterprise AI isn't customer service but the internal help desk, and its Nexus EDGE desktop agent is the…

HR & Talent

AI, security and technology sovereignty reshape enterprise priorities across the UAE

Share with your CISO Dell Technologies' Modern Enterprise Readiness Study 2026 puts hard numbers on what UAE security leaders already sense: 68% of organizations say security and compliance concerns have…

Security & Governance

AI Adoption vs AI Transformation: What Actually Changes Inside an Enterprise? | nasscom

The Adoption Trap: Why Most Enterprise AI Investments Are Just Expensive Productivity Theater There is a pattern playing out inside enterprises right now that should concern every C-suite executive who…

Strategy & Leadership
News of the Week
AI shopping could develop around open marketplaces, retailer-controlled platforms, a dominant super app or renewed trust in human creators. Each would change how brands get discovered and how customers decide what to buy. David Bratslavsky walks through the four scenarios and the preparation they share: product information that AI tools can read and a clear reason for people to choose the brand. The report features BCG's scenario framework and OpenAI's shopping demonstrations. Companies featured: @TheBostonConsultingGroup @OpenAI WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:02 Four AI futures marketers should prepare for

Four AI futures marketers should prepare for

September 24th

A company that helps build an AI startup may want to own the technology that gives it an advantage. Vantora's sovereign AI model gives enterprise partners an equity stake from the start and a path to bring the business in-house once it proves its value. Using J.B. Hunt as the example, David Bratslavsky explains how private data, an embedded engineering team and an initial customer relationship fit together. The aim is to give the partner more control over AI built around its own operations. Company featured: @jbhunttransport Vantora: https://www.vantora.us WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 0:59 Sovereign AI and the captive startup model

Sovereign AI and the captive startup model

September 24th

Vantora starts with an expensive problem inside a large company, then builds an AI business to solve it. After raising more than $100 million, the company is expanding an approach that puts builders alongside enterprise teams and their operating data. David Bratslavsky looks at the model through the example of Alaska Airlines, how Vantora uses its COSMOS technology and the financial opportunities it says it targets. Vantora reports that it has launched 17 ventures. Company featured: @AlaskaAirlines Vantora: https://www.vantora.us WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:00 How Vantora builds AI ventures

How Vantora builds AI ventures

September 24th

Independent safety testers are working inside AI labs while models are still being developed. Accenture and Anthropic are building a team of embedded evaluators to test how models respond to deceptive or harmful requests. David Bratslavsky explains how red teaming works, how testers report failures to engineers and why testing continues after a fix. Passing an individual test does not establish that a model is safe; the work aims to uncover problems before release. Companies featured: @Accenture @anthropic-ai WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:06 How embedded evaluators test AI

How embedded evaluators test AI

September 24th

Supplier records and payment histories can help a business forecast risk, but preparing spreadsheet data for AI often takes substantial work. TabPFN 3.5 is designed to make predictions from rows and columns without a new round of model training for every task. David Bratslavsky looks at SAP's approach to missing entries and mixed formats, plus how businesses can access the Plus version through SAP AI Core. The report covers potential uses including supplier assessments and late-payment forecasts. Company featured: @SAP WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 0:53 TabPFN 3.5 turns business data into predictions

TabPFN 3.5 turns business data into predictions

September 24th

Legal teams are using AI to work through research, contracts and the documents behind corporate deals. This report looks at OpenAI's Astra for Law and how firms can build tools around their own negotiating guidelines and past agreements. David Bratslavsky explains three practical uses: finding relevant cases, identifying risks across contract clauses and reviewing large collections of deal documents. Lawyers still need to trace findings to the source and check the evidence before acting on them. Company featured: @OpenAI WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:17 How law firms are using OpenAI

How law firms are using OpenAI

September 24th

One overnight document review can cost a software provider more than a customer's entire monthly subscription. AI agents can read files, write summaries and check their work through hundreds of billable steps, even when the customer makes only one request. David Bratslavsky explains the pressure this puts on flat subscription pricing and why a provider might switch models to keep costs under control. For buyers, that can mean the same product is doing the work with a different model. WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:02 Why AI agents challenge software pricing

Why AI agents challenge software pricing

September 24th

A lower price per token does not always mean a lower bill. David Bratslavsky examines Grok 4.7's pricing and its developer's comparisons with GPT-5.6 Sol, including tests involving engineering and legal work. For companies running AI at scale, the useful comparison is the cost of a completed task at the quality the business needs. This WorkAI.tv report explains why token consumption and answer quality belong in the same purchasing decision. Companies featured: @Grok @OpenAI WorkAI.tv | News of the Week | September 22, 2026 https://workai.tv #EnterpriseAI 1:08 Grok 4.7 and the price of AI performance

Grok 4.7 and the price of AI performance

September 24th

Companies spend billions on powerful model but still struggle to make them useful. Why a new model fails on decades-old company systems, and how forward-deployed engineers working inside your business close the gap. #enterpriseai 1:07 Are Forward Deployed Engineers the Key to Enterprise AI?

Are Forward Deployed Engineers the Key to Enterprise AI?

September 11th

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How HR Teams Use AI Agents in 2026: 5 Enterprise Deployments for Employee Support, Onboarding and Cost Savings
HR & Talent

How HR Teams Use AI Agents in 2026: 5 Enterprise Deployments for Employee Support, Onboarding and Cost Savings

Share with your CHRO Five enterprises have moved HR AI agents past pilot into production at meaningful scale, and the numbers are specific enough to anchor a business case. LTM (formerly LTIMindtree) has…

A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops
Industry News

A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops

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Parallel Loop Raises $6.6 Million Seed Led By 3one4 Capital To Scale Enterprise AI Transformation
Strategy & Leadership

Parallel Loop Raises $6.6 Million Seed Led By 3one4 Capital To Scale Enterprise AI Transformation

Share with your CIO Parallel Loop is betting that enterprise AI adoption stalls not on model quality but on integration depth, and it's raised $6.6 million in seed funding led by 3one4 Capital…

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We are dedicated to bringing you practical advice on how to best use AI in your enterprise from executives and experts who are making it work at their companies.
Shyam Bhojwani, CIO & CISO at Nextdoor, joins David Bratslavsky of WorkAI.tv for a practical conversation about building enterprise AI that can operate securely and deliver measurable value. They discuss the data foundation, governance, clear ownership for AI agents, enterprise search as context, production testing, routing models by task impact, measuring outcomes, and how security leaders can help teams move safely into production. Chapters 0:00 Introduction 0:33 Aligning technology and security 1:02 Nextdoor's approach to AI 1:34 Where an AI journey should begin 2:05 What follows the data layer 3:02 Who owns each AI agent? 3:36 Controlling agent sprawl 4:36 Why enterprise search matters 5:47 Start with the user problem 6:10 How to run a production proof 7:04 Moving from context to production 7:28 What agents are doing now 8:10 Lessons from implementation 8:44 Where enterprise AI is overhyped 9:19 Routing AI tasks by impact 9:54 Measuring CIO impact 10:58 How CISOs should lead in AI Learn more: Nextdoor: https://nextdoor.com/ WorkAI.tv: https://workai.tv/ #EnterpriseAI Safe Harbor Statement This video contains forward-looking statements regarding Nextdoor's future business expectations. These forward-looking statements are only predictions and may differ materially from actual results due to a variety of factors, as more fully detailed under the caption 'Risk Factors' in our Quarterly Report on Form 10-Q for the quarter ended June 30, 2026, filed with the Securities and Exchange Commission ('SEC') on August 4, 2026, and our other SEC filings, which are available on the Investor Relations page of our website at http://investors.nextdoor.com and on the SEC's website at www.sec.gov. All forward-looking statements are based on information available as of the date of this video and should not be relied upon as predictions of future events. Nextdoor undertakes no obligation to update these forward-looking statements for any reason or to conform them to actual results or revised expectations, except as required by law. Enterprise Search Unlocks AI | Shyam Bhojwani, Nextdoor CIO & CISO
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