Check Out The Insights Shared In The Article "Smart Cybersecurity Spending – How CISOs Can Invest Where It Matters Most" => ds3-bandwidth.com/2025/10/26… @ScottBVS @ChuckDBrooks @Corix_JC @mclynd @BillMew @cybersecboardrm @Shirastweet @YuHelenYu @robmay70 @mirko_ross @AccidentalCISO

Don't miss my latest #livestream at 12 noon today - "AI Agents: Can We Really Trust Them To Run Our Businesses?" 📅 Date: Today, 22nd October 2026 🕒 Time: 12:00 GMT, 07:00 EST, 04:00 PST, 17:30 IST LinkedIn > lnkd.in/gsq28F2 Twitter > lnkd.in/ehrXiUW Facebook > lnkd.in/e_9hcfph YouTube > lnkd.in/dMhGX2q 🤖 What happens when AI agents start making thousands of decisions faster than humans can oversee them, and how can businesses stay in control? I'm joined by Stijn Christiaens, Co-founder and Chief Data Citizen at Collibra, to explore why businesses struggle to scale AI agents, the hidden costs of AI hallucinations, the importance of trustworthy data, context and control, and why unlocking the real potential of autonomous AI requires us to fundamentally rethink how businesses operate. 🚀

Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security link.amazon/B0eXunR6c by @ChuckDBrooks

AI Workplace Policies That Could Help Prevent A Crisis For Companies forbes.com/sites/edwardsegal… #artificialintelligence #digitaltransformation

A new framework teaches #AI models to audit and repair each other’s reasoning, improving accuracy buff.ly/KlQKrZh #tech #digital #innovation #disruption #leadership #business #management #governance #AgenticAI #genAI #LLM #data #CEO #CIO #CTO #CDO #AIStrategy #digitalstrategy #digitaltransformation @VentureBeat @BenDee983 @jblefevre60 @pierrepinna @kalydeoo @Ym78200 @CurieuxExplorer @mvollmer1 @JoannMoretti @anand_narang @EvanKirstel @SpirosMargaris @ipfconline1 @Jeffkagan @AndresVilarino @efipm @FMFrancoise @MHcommunicate @JeromeMONANGE @mary_gambara @drsharwood @smoothsale @debashis_dutta @devbhatt72 @MarshaCollier @PamMktgNut @arlenenewbigg @JagersbergKnut @TysonLester @GlenGilmore @pchamard @baski_LA @AnthonyRochand @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @c4trends @amalmerzouk @ralf_ladner @netzpalaver @nafisalam @cto_software @Oschonschek @Matt_Rosenquist @Shirastweet @Kevin_Jackson @JimMarous @chidambara09

AI Agents: Can We Really Trust Them To Run Our Businesses? nitter.siddz.com/i/broadcasts/1OGwbnrea…

Cloud providers aren't just building custom chips to save you money; they're doing it to make leaving their platform virtually impossible. This 'chip lock-in' is moving beyond APIs and contracts, directly impacting your workloads. #CloudComputing #TechLockIn #AIChips

The Hidden Costs Of AI Data Centers, And Who Really Pays #AI #datacenters are powering the #artificialintelligence boom, but their rapid expansion is raising concerns about electricity #prices, water consumption, public health, tax breaks and pressure on local #infrastructure. As #communities and #governments respond, the hidden costs of AI #infrastructure are becoming a growing challenge for #BigTech. linkedin.com/pulse/hidden-co…

Connectivity is easy to overlook until it fails. On Built for Trust, @NickLippis and zLinq's Tatiana Finkelsteyn explore the hidden risks of ISP management, network resilience, and the path toward automation. 🎧 Tune in here: hubs.li/Q04BNC5M0

#Quantum Debt Is Growing—And Most Companies Are Not Prepared "The biggest #business risk around quantum computing might very well be that companies wait until it arrives before preparing for it" buff.ly/0yAbSm2 #tech #cybersecurity #data #datasecurity #encryption #cryptography #PQC #QDay #CIO #CTO #CDO #CISO #CEO #leadership #management #governance #quantumcomputing #HNDL #cyberthreats #technicaldebt @Forbes @David_Anri @BetaMoroney @ChuckDBrooks @MikeFlache @Khulood_Almani @IngridVasiliu @Fabriziobustama @Timothy_Hughes @NafisAlam @YuHelenYu @RLDI_Lamy @MCLynd @OlKonol_oa @RigneySec @BenRothke @HWillert @AndrewinContact @TerenceLeungSF @Shi4Tech @enilev @Nicochan33 @SabineVdL @bimedotcom @IanLJones98 @FrRonconii @RiccardoBua @Eli_Krumova @NYIke @HaroldSinnott @SallyEaves @GlobalIQX @AntGrasso @AkwyZ @DinisGuarda @PVynckier @YvesMulkers @HaleChris @BillMew @RobMay70 @NigelTozer @m49D4ch3lly @Ronald_vanLoon @jeancayeux @NevilleGaunt @asokan_telecom @cybersecboardrm @RVP @QuePasaChico

🧠 Is AI making us more productive… but less skilled? Artificial intelligence can now write, analyse, research, solve problems and complete tasks that previously required years of experience. 🤖 But there's a growing concern we need to take seriously: AI deskilling. If we constantly rely on AI to do the thinking, make decisions and complete challenging tasks for us, could we gradually lose the very skills that make us valuable? The answer isn't to stop using AI. It's to use it differently. Instead of simply accepting AI-generated answers, we should challenge them, understand the reasoning, practise our own skills and use AI as a tool for learning rather than a replacement for effort. The goal shouldn't be to let AI do everything we can do. It should be to use AI to become better at what we do. 🚀 Watch the video and tell me: Do you think AI is making people smarter or more dependent on technology? 👇 #AI #ArtificialIntelligence #AIDeskilling #FutureOfWork #FutureSkills #CriticalThinking #GenerativeAI #AIProductivity #HumanSkills #AITips #WorkplaceAI #FutureOfAI

The AI Confusion Problem: Fear-Spreading Voices Are Drowning Out Real Value — and Real Risks We have an AI confusion problem, and it's getting worse by the day. The gap between what AI can actually do — impressive, productivity-driving, straight-up beneficial — and the noise surrounding what it might do is wider than it's ever been. I recently joined John Rush on his radio show, Rush To Reason, to talk about exactly this. My central point: strong voices, including Bill Gates, are out there spreading fear, uncertainty, and doubt — warnings of killer robots and mass doom. But the real dangers we need to deal with are much more specific: flawed reasoning models, hallucinations, bad data, and poor implementation. None of these require a sci-fi apocalypse to cause real damage. The result of all this hype? Everyone is confused about AI's purpose, fixated on the dramatic instead of the practical, and overlooking the very real productivity gains sitting right in front of them. Honestly, taken at its essence, it's kind of funny. Get clear-eyed about AI. Separate the real risks from the mythology, and start capturing the benefits. Listen to my conversation with John here: rushtoreason.castos.com/epis…

Want to hide yourself and become anonymous while hacking? -----> Use Proxy Chaining #EthicalHacking

Enterprise AI Doesn’t Fail in the Demo. It Fails in the Mess. The easiest AI system to build is the one that works when everything is clean: the data is available, the prompt is clear, the workflow is simple, and the model has exactly the context it needs. That is not enterprise reality. Enterprise AI has to operate inside fragmented systems, conflicting records, stale policy documents, unavailable APIs, informal approval paths, regional compliance rules, and exceptions that never appear in the boardroom demo. This article makes an important point: the problem is not always the model. The problem is often the architecture around the model. A polished AI answer based on partial, outdated, or contradictory context can be more dangerous than no answer at all. It creates confidence without operational truth. The real work is not just prompt engineering. It is governance, observability, access control, source traceability, escalation design, auditability, fallback procedures, and clearly defined human ownership. AI does not eliminate enterprise complexity. It exposes it. The organizations that succeed with AI will not be the ones that only optimize for the happy path. They will be the ones that design for the disputed claim, the missing field, the conflicting customer record, the unavailable system, and the policy exception. Start with the mess. Build the controls. Then scale the automation. Article: techtarget.com/it-strategy/n…

Everyone wants to scale AI agents. But how many businesses really know what their agents are doing? 🤖 This was one of the biggest questions coming up at World Summit AI in Amsterdam. I caught up with Bianca Vloon, Regional VP of Sales, Northern Europe at @Collibra, to discuss what she's hearing from business and technology leaders. And something interesting is happening. A year ago, the conversations were largely about understanding what AI could do. Today, companies are much more focused on deploying AI into production, scaling it successfully and making sure they can actually trust it. As Bianca explained, two things are becoming increasingly important: 🔹 Context: AI agents need the right business knowledge, trustworthy data, policies and processes to make good decisions. 🔹 Control: Organizations need visibility into what their AI agents are doing, what information they can access and which actions they're allowed to take. And there's another important consideration: cost. Businesses need to balance speed, trust and governance while ensuring their AI investments deliver real value. I think this reflects a significant shift in the AI conversation. We're moving from experimenting with what the technology can do to figuring out how to make it work reliably across entire organizations. This is where Collibra is doing some really interesting work to close the context and control gap that enterprises struggle with. Their AI Command Center provides a centralized view of every agent, model and use case, governed with continuous trust signals, automated traceability and proactive risk prevention. A must for deploying AI at scale. collibra.com/products/ai-com… #Sponsored #AgenticAI #AIAgents #ArtificialIntelligence #AIGovernance #Collibra

Shaping global #governance of #AI agents buff.ly/CS29iAW #tech #AgenticAI #digital #innovation #disruption #leadership #business #management #compliance #GRC #CIO #CTO #CDO #CEO #AIStrategy #digitalstrategy #digitaltransformation @BrookingsInst @jblefevre60 @pierrepinna @kalydeoo @Ym78200 @CurieuxExplorer @mvollmer1 @JoannMoretti @anand_narang @EvanKirstel @SpirosMargaris @ipfconline1 @Jeffkagan @AndresVilarino @efipm @FMFrancoise @MHcommunicate @JeromeMONANGE @mary_gambara @drsharwood @smoothsale @debashis_dutta @devbhatt72 @MarshaCollier @PamMktgNut @arlenenewbigg @JagersbergKnut @TysonLester @GlenGilmore @pchamard @baski_LA @AnthonyRochand @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @c4trends @amalmerzouk @ralf_ladner @netzpalaver @nafisalam @cto_software @Oschonschek @Matt_Rosenquist @Shirastweet @Kevin_Jackson @JimMarous @chidambara09

Hackers are using AI to find bugs and write exploits faster than you can patch them. My friends at @wiz_io made a free playbook for keeping up. Grab it here ntck.co/WizAIPlaybook #ad

How much authority are you ready to hand to an AI agent? I explored this with Sriram Iyer, SVP & GM of AI Strategy and Products at @OneTrust, in our latest CXO Spice conversation. As agents move from recommending decisions to taking action, leaders need a clearer answer than “we have a policy.” What does that mean for governance, accountability and the decision to scale? Watch our full conversation: piped.video/l_5cw2AuKb8 #AIGovernance #OneTrust #TrustWeek #CXOSpice #OneTrustPartner

87% of developers are getting faster with AI. Only 28% say they're experiencing less friction in their work. Something isn't adding up. #Sponsored Those are two of the striking findings from @Atlassian's new State of Developer Experience 2026 report. And the research reveals some other fascinating insights into the gap between AI's promises and what businesses are actually achieving. Consider these findings: 65% of developers spend time correcting AI-generated work that missed the original intent. 49% spend at least four hours a week managing AI tools and reviewing code. 60% say AI usage is treated as a signal of productivity. That last statistic particularly caught my attention. Are we creating a culture where being seen to use AI matters more than the value it actually delivers? I've been arguing for some time that the biggest benefits of AI will come from fundamentally rethinking how organizations operate. Giving employees increasingly powerful AI tools while leaving outdated processes, fragmented systems and unnecessary bureaucracy untouched will only get us so far. And here's another telling finding: Only 17% of developers say their organization has a clear AI strategy across the software development lifecycle. Yet developers in organizations with a clear strategy are nearly twice as likely to report less friction. For me, this is where the real opportunity lies. We need to move beyond using AI for individual tasks and start rethinking entire workflows, connecting information across systems and enabling people to work more effectively. In software development, that means adopting a more AI-native approach across the entire development lifecycle. And I believe the same principle applies to virtually every business function. Ultimately, the goal should be better business outcomes, not simply more AI-generated code, more AI tools or more AI activity. I'd love to hear your thoughts. Is AI genuinely making your organization more productive, or are we simply getting faster at generating work that someone else needs to check? Explore the full findings in Atlassian's State of Developer Experience 2026 report: fandf.co/4yXaSTw Paid partnership with Atlassian.

Ever wondered where the Internet actually lives? The Dallas Infomart and Equinix DA11! 🌐 ——-> I got access inside this massive data center to see how they cool millions of server, an entire room packed wall-to-wall with high-powered GPUs. Watch the full video to discover everything I learned there! 👇 piped.video/v477fvbj3rk?si=2OKx…