Linthicum Research

• Founded and lead Linthicum Research, specializing in custom research for major analyst organizations and media groups.  
• Developed and executed courses, webinars, and articles, enhancing knowledge sharing in AI and cloud computing.  
• Designed and implemented optimized cloud and GenAI architectures, driving efficiency and innovation across projects.

Founder/Lead Researcher

LinkedIn

Over 70 on-line video courses on the important topics within the cloud computing space.   This includes architecture, migration, and DevOps, as well as the basics such as core concepts, storage, and networking.

Author

YouTube

• Spearheaded the production and deployment of the "Cloud Computing Insider" YouTube channel and podcast, focusing on enterprise cloud computing and AI.  
• Collaborated to create engaging content that educates and informs industry professionals.  
• Analyzed audience feedback to refine content strategy, resulting in a 30% increase in viewer engagement over six months.

Creator-Cloud Computing Insider Channel/Podcast

Pearson

Author of over a 17 books on Enterprise Computing topics.

InfoWorld

Cloud computing blogger for InfoWorld, providing news and commentary within the cloud computing space.   The InfoWorld cloud computing blog is frequently the most read blog in the cloud computing space.

Blogger

Louisiana State University

Creating course content, as well as providing remote instruction.   Courses include cloud computing, DevOps, and cloud computing architecture.

Adjunct Instructor

Deloitte Consulting

Focused on cloud technology strategy and architecture practice. Wearing many hats including thought leadership, demand creation, public outreach, service offering innovation, and project leadership.   Created several inovative programs including Cloud Complexity Management, and Responsive Data Architecture.   Oversaw several larger cloud computing deals, as well as delivery on those deals.

Chief Cloud Strategy Officer (Retired)

GigaOm

Provide analysis of key cloud computing technology and trends, including creation of blogs, major reports, news updates, and advisory. Speaks at most GigaOM conferences, including Structure Data and Structure. Curator, Analyst, and contributor for GigaOM Pro.

Technology Futurist

Cloud Technology Partners, a Hewlett Packard Enterprise company

SVP at Cloud Technology Partners providing core leadership in support of client engagements including cloud strategy, architecture, and implementation.   Member of the executive team, providing strategic guidance for the company.  Additionally, providing key thought leadership activities including keynote presentations at most major cloud computing conferences, commentary to the press including "Forbes" and "Business Week," Webinars, and publication of over 200 blogs and articles.

SVP [Exit]

Blue Mountain Labs

CTO and Founder of the Blue Mountain Labs focusing on emerging technology spaces including cloud computing, and the use of this technology within enterprises and government agencies.   Started Blue Mountain Labs with the vision that emerging technology has value when proper planning and strategy creation occurs, and has provided guidance for dozens of Global 2000 enterprises around the ability to leverage cloud computing and SOA for business value.

Founder and CTO (Former CEO)  [Exit]

Internationally Known AI and Cloud Computing Thought Leader and Influencer, Enterprise Technology Innovator, Educator, 5x Best Selling Author, Speaker, YouTube/Podcast Personality, Over the Hill Mountain Biker.

*** Please follow me, don’t request a connection, I ran out of allowed connections years ago. ***

David Linthicum is a globally recognized thought leader, innovator, and influencer in artificial intelligence (AI), cloud computing, and cybersecurity. Until early 2024, he served as the Managing Director and Chief Cloud Strategy Officer at Deloitte Consulting LLP, where he brought over 30 years of extensive experience in enterprise technology, championing innovative AI-driven solutions that enabled corporations and start-ups to disrupt their markets and enhance operational efficiency.

David's extensive expertise in AI is well-regarded, with key contributions to developing advanced AI strategies and architectures for global clients across various industries. During his tenure at Deloitte, he spearheaded the integration of AI technologies into cloud infrastructures, creating intelligent systems that drive business transformation and competitive advantage. His thought leadership in the AI domain has been featured extensively in prominent publications and platforms.

David frequently appears on most lists of top cloud computing and AI thought leaders and influencers. He has authored over 17 best-selling books, thousands of articles, and over 70 courses on LinkedIn Learning, many of which focus on the practical applications and strategic benefits of AI in business. His influence extends to mentoring the next generation of technology professionals through various AI talent development programs.

Currently, David continues to provide key thought leadership, architecture, and technology leadership, serving Global 2000 companies, new innovative companies, and government agencies. He provides essential guidance for navigating the emerging world of enterprise technologies. David Linthicum remains a pivotal figure in advancing AI and cloud computing technologies, making him a frequent keynote speaker, podcast contributor, and media commentator on AI, digital transformation, cloud architecture, and security topics.

Agentic AI Hype: Things Are Getting Silly Fast

Every morning I log onto LinkedIn and see another chorus of voices yelling about their “agentic AI” credentials. This week, McKinsey & Company  claims to be running 12,000 AI agents across their client base. Twelve. Thousand. Let that number rattle around in your head for a bit.

Anyone with hands-on experience deploying actual enterprise agents—that reason, plan, act, and adapt—knows that even getting one into production is tough. Deploying a dozen? Impressive. Scaling to thousands? Comedic, unless your definition of “agent” is so watered down it means “any script with a prompt.” Are we really counting every tweak—“Summarize meeting,” “Summarize meeting but with extra vibes”—as a separate agent now?

None of this is ringing true, and I suspect many folks quietly know it. The market’s going berserk with everyone selling, buying, and boasting about agentic architectures, when in reality, traditional AI would do just fine—and often better. Instead, we’re rebuilding systems with agents on top of agents, driving up complexity and cost for little tangible benefit. It’s the emperor’s new AI wardrobe.

Let’s get real: Not every business problem needs a fleet of agents. In fact, the more agentic the sales pitch, the less substance I’m finding underneath. We’re rapidly approaching a reality check, and when it hits, a lot of consulting firms will be left looking pretty foolish. Sometimes the best solution is the simple one—do what works, not what’s trendy.

Reality has a habit of snapping back hard. It’s time we built for reality’s terms, not for LinkedIn’s theater.

#AI #AgenticAI #Consulting #EnterpriseAI #TechRealityCheck

David Linthicum

Why This Plaque Sums Up Everything Wrong with Enterprise AI Deployment

Saw this image floating around—McKinsey & Company  being honored for their consumption of AI resources. Yes, a plaque, not for driving innovation or building value with AI, but for using up more “AI capacity” than almost anyone else. You honestly can’t make this stuff up.

The fact that this is celebrated highlights a critical problem in how many big consulting firms (and their clients) are approaching AI today. Success is being measured by the sheer volume of AI resources consumed, not by the outcomes or real value delivered. If we believe spending more on AI compute is the goal, we haven’t grasped what makes this technology transformative in the first place.

Enterprise leaders are tying their AI “success” to eye-popping spend and scale, when what we should truly be celebrating is pragmatic, incremental, and useful applications of AI—deployments of generative AI and other advanced technologies that actually drive meaningful business outcomes over time. That’s where the real, lasting wins will come from.

Right now, it’s an open secret: 95% of enterprise AI projects are failing to deliver meaningful results. Teams are routinely over-engineering, over-spending, and picking the wrong problems to solve. Too often, the effort is wasted, and the technology remains deeply under-optimized.

If the measure of success continues to be plaques like this—awarding those who use the most, not those who achieve the most—then enterprises and their partners risk missing the real opportunity with AI altogether. Some will even face serious trouble down the road.

Let’s stop rewarding consumption for its own sake and start demanding actual, measurable value from our AI investments. The future belongs to those who understand why and how to use AI effectively—not just those who can rack up the biggest bill.

#AI #EnterpriseAI #DigitalTransformation #ValueCreation #BusinessStrategy #Consulting #AIwaste

Amazon’s AI Excuse: Why We’re Not Buying It

As someone who has closely followed tech industry trends for years, I can’t say I’m surprised by the recent news of Amazon’s corporate restructuring and layoffs. I called this well before these events unfolded, and I strongly doubt artificial intelligence has anything meaningful to do with the drastic job cuts being announced.

Let’s get real: the post-pandemic adjustments, overhiring, and mounting pressure from shareholders to bolster profitability are likely the key drivers here—not some sudden revolutionary gains from AI automation. Yet, Amazon seems intent on spinning this as an inevitable byproduct of their "AI-fueled efficiencies."

Amazon needs to be more honest with the public, employees, and investors. We see right through this narrative. Layoffs on this scale—especially targeting HR and operations—are almost always about cutting costs, consolidating management after overexpansion, and responding to Wall Street scrutiny. The AI explanation feels, at best, opportunistic. At worst, it’s a distraction.

Let's not forget: over the past two years, many tech giants, including Amazon, have wielded AI as a buzzword to mask some hard truths. Sure, AI has the potential to streamline certain processes, but to suggest it’s the primary force driving tens of thousands of layoffs? Few within this industry are buying it.

Transparency matters. Companies like Amazon owe their stakeholders—both employees and investors—a straightforward explanation of what’s really happening. Anything less undermines trust, and in the long term, that erosion of trust is far more costly than any short-term efficiencies gained from cutting jobs.

If this truly is about overhiring or other operational challenges, let’s just call it what it is. Hiding behind AI as a smokescreen does a disservice not only to the workforce but also to the credibility of the industry as a whole.

What are your thoughts? Do you believe AI is at the core of these changes—or is it just a convenient story? Let’s discuss. #TechTrends #Amazon #AI #JobCuts #Transparency 


 https://lnkd.in/eTquBieF

Closing in on 190,000 followers: ￼Grateful for This Tech Community

I’m excited (and honestly a bit amazed) to share that my network here on LinkedIn is about to surpass 190,000 followers. Sure, there are plenty of people in this space with even larger audiences, but for someone focused on a highly specific, niche area of enterprise technology, this milestone feels remarkable.

I’m truly grateful for the trust you’ve all shown—following, connecting, and engaging with my posts about the smart and correct use of enterprise technology. Your support lets me know that these topics matter and that a community of professionals seeking practical, real-world tech advice can thrive.

Thank you for allowing me to be a small part of your professional journey. I will continue doing my best to provide actionable content, fresh insights, and honest advice for as long as I can.

Here’s to reaching new milestones and shaping the future of enterprise tech together!

— Dave Linthicum

Making AI work for businesses (not the other way around) | CEO @ Particula Tech

$47K a month.

That's what a healthcare company was paying AWS to run their diagnostics AI.

Last week, we moved it off the cloud entirely. Back to their own servers. The thing everyone says you should never do anymore.

They'd been running patient diagnostics for 18 months. Analyzing scans, flagging abnormalities, routing to specialists. Critical stuff that couldn't go down.

But here's what changed. They hit scale. Processing 200K scans a month now. At that volume, cloud costs weren't just expensive - they were exponential.

We did the math. $6M over three years on cloud versus $340K for their own hardware. Same performance. Better latency, actually. (Patients in the same city as the servers.)

And here's the part nobody mentions. Local models mean patient data never leaves their building. No uploads. No API calls sending scans to some data center. No wondering which jurisdiction your data is sitting in.

Their compliance team was relieved. HIPAA audits got simpler. Security team stopped worrying about third-party breaches.

Not saying cloud is wrong. For most companies starting out, it's perfect. You need flexibility. You're testing. You don't know your usage patterns yet.

But once you hit predictable, high-volume workloads with sensitive data? The math flips. And the risk drops.

Nobody talks about this because "cloud-first" became gospel. And for early stage? It is. But at scale, sometimes the old way makes sense again.

Worth running your own numbers before renewing that next contract.

Today, on Veterans Day, I want to honor the memory of my father, Maj Ronald G. Linthicum, US Army. My dad served our country with incredible dedication for over 25 years, including two tours in Vietnam—where he was wounded in combat during his second deployment.

He was more than an outstanding officer and an inspiring warrior; he was, above all, an extraordinary father and devoted husband. His legacy is built not just on his military achievements and courage under fire, but on the strength of his character, his unwavering sense of duty, and the boundless love and support he gave our family.

Though he’s been gone for some time now, there isn’t a day that goes by that we don’t miss him deeply. His lessons and his love continue to shape who I am and guide me in everything I do.

On this Veterans Day, I remember you with pride and gratitude, Dad. Thank you for your service, your sacrifice, and—for me—the gift of being your son. 

#VeteransDay #Family #Honor #Gratitude

I’ve been reflecting the same opinion for a long time, and I’m the guy who has the most watched agentic AI course on the Internet.   This architecture pattern has some merit, but in very narrow, use cases, it’s definitely not going to solve all the problems as being promoted to solving right now. My larger concern is that people are going to figure that out, and the tech industry are gonna look like dummies.

“AI agents are not amazing - they’re slop”

This week, Andrej Karpathy (yes, OpenAI co-founder and former Tesla AI lead) called most so-called “agentic AI's” slop.

Not “rough”
Not “early”
Slop.

Meanwhile Sam Altman says these agents will “join the workforce” in 2025.

That’s a twelve-month gap between marketing and reality - and a decade gap, according to Karpathy, between capability and competence.

So… who’s right?

Altman’s timeline reflects ambition.
Karpathy’s critique reflects engineering reality.
Most “AI agents” today are fragile prompt chains wrapped in slick UX - a mechanical turk pretending to be autonomous intelligence.

They hallucinate. They get stuck in loops. They depend on human babysitting.
And yet, they’re being sold as the new industrial revolution.

We’ve seen this before.
 - ERP systems that promised “one version of the truth”
 - CRM platforms that promised “a single view of the customer”
 - AI agents now promise “self-running enterprises”

Each wave follows the same arc:
[1] Hype (investors drool)
[2] Chaos (users struggle)
[3] Integration (consultants profit)
[4] Utility (value quietly emerges)

Karpathy’s real message isn’t cynicism - it’s discipline.
He’s saying: stop pretending the scaffolding is the building.

We’re still in the “autocomplete era” - augmenting humans, not replacing them.
Autonomy requires reasoning, context, and self-correction - things even frontier models don’t do well without guardrails, memory, or feedback loops.
Until then, calling them “agents” is like calling an Excel macro a “junior analyst”.

Karpathy’s realism is a much-needed corrective.
AI doesn’t need more prophecy; it needs more honesty.

True intelligence isn’t automation. It’s adaptation.
And right now, AI is still learning to walk without tripping over its own prompts.

Excited to Connect at AWS re:Invent 2025—Let’s Make It Count!

I'm thrilled to announce that I’ll be at AWS re:Invent this year in just a few weeks! It’s always an incredible opportunity to connect with some of the brightest minds in cloud and technology.

Interested in meeting up? I only have a handful of meeting slots available, but I’d love to hear from you! Send me a message here on LinkedIn—let me know why you’d like to meet, and what you think would make the conversation interesting for both of us.

Please don’t be offended if I’m not able to meet everyone; slots really are limited. Looking forward to some great discussions and new connections. See you in Vegas!

Dave

#AWSreInvent #CloudComputing #Networking #LasVegas #TechEvents #AWS #Innovation #LetsConnect

Yesterday’s AWS Outage: Hard-Learned Lessons and the Question of Recourse

Yesterday’s AWS outage dealt a significant blow across the digital landscape. Consider the numbers:

$72 million per hour — Estimated direct losses for Amazon during the downtime
~9 hours — Duration of the outage
500 million to
500 million to 650 million — Potential total direct loss for Amazon
Over $1 billion USD — Possible combined losses for all impacted businesses

Major organizations—ranging from McDonald’s and Office 365 to Apple Music, Snap, Lyft, Roblox, and a wide range of banks and retailers—felt the ripple effects. Lost productivity, lost revenue, and shaken customer trust are only the beginning.

Given the massive scale of the financial and operational impact, what recourse do these businesses really have? Is meaningful compensation on the table, or is this another warning sign to diversify, invest in disaster recovery and high-availability strategies, and avoid single-vendor dependencies?

I’m eager to hear from fellow leaders and technologists: How are you responding to events like this, and do you see recourse as a realistic expectation in agreements with cloud providers?

#cloudcomputing #awsoutage #cloudstrategy #riskmanagement

What an incredible day out on the gravel bike in Loudoun County VA! The weather was perfect—one of those days that reminds you just how good it feels to be out there, soaking up the scenery and fresh air.

Of course, gravel biking in my 60s comes with its own special highlights:

-My GPS might just be my most enthusiastic riding partner, constantly “recalculating” after every detour I can’t resist.
-I like to think the local wildlife are my biggest fans, especially when they witness those less-than-graceful moments on loose gravel.
-And let’s be honest: the true reward is justifying that second pastry after the ride—all in the name of proper recovery!

Sometimes you just need a great ride to recharge before diving back into work, videos, and new projects. Here’s to many more days like this!

The Amazon Web Services (AWS) We Once Knew Is Gone—And I Called It

Over the past year, I raised concerns that the AWS of a decade ago—fearless, innovative, always at the edge—was fading into memory. I spoke out about how today’s AWS seems more focused on profit margins and market share than real innovation. No shortage of folks were happy to tell me I was “off base,” “negative,” or “missing the big picture”—and I took plenty of criticism for saying what needed to be said.

Now we see it confirmed: AWS is issuing strategic announcements light on vision, heavy on PR, while their true competitors are actually building. The energy that built AWS—one of relentless customer-centric invention—seems replaced with the drive to simply defend the numbers, maintain profiles, and ride the inertia. It’s disappointing … but not surprising, at least to me.

To all who dismissed my concerns—I’d appreciate an apology, but let’s be real, I won’t hold my breath. Maybe now we can have an honest conversation about what comes next, and what real leadership should look like in enterprise cloud and AI.

Let's pay more attention to my predictions, okay?   You should be seeing a clear pattern.  

#AWS #CloudComputing #AI #Innovation #Leadership #EnterpriseIT #TechTrends #TruthToPower

Technology, Policy, and Strategy | Middle East & Africa Policy and Business Development

As talk of an #AI #bubble grows louder, few are looking at the financial plumbing driving it. Beneath the hype, two circular systems are forming, each powering, and inflating, the other.

In one loop, OpenAI–NVIDIA–Oracle:
#Nvidia invests in OpenAI ➡️ #OpenAI rents compute from Oracle ➡️ #Oracle buys Nvidia’s chips ➡️ Nvidia records record-breaking sales.

In the rival loop, Anthropic–Google:
#Google invests in Anthropic ➡️ #Anthropic trains on Google’s TPUs and Cloud ➡️ Google records record-breaking sales.

Each side’s acceleration pushes the other to spend more. Two circular economies, two narratives of dominance, and one increasingly inflated AI market.

Broke My Own Record: A Wild Day Talking to Reporters About the AWS Outage

Yesterday was one for the books—I broke my personal record for the number of reporters I communicated with in a single day, all thanks to the AWS outage. Not much else to say except that it shows just how big of an impact a major cloud provider going down can have across the tech ecosystem and the media landscape. Here’s hoping for quieter days ahead—though I’m not holding my breath.

#AWSOutage #CloudComputing #Media #TechNews #BreakingRecords #AWS #CloudNews

The High Cost of Building on Vibes: Why “Vibe Coding is Stupid” (Even With AI)

You’ve seen the meme—“Vibe Coding is Stupid.” But behind the laughs, there’s a painful reality. I’ve watched top-notch teams torch huge budgets chasing the next big thing, letting AI fill in the blanks while they code off the cuff. Instead of strategy and standards, they lean on “feeling it out.” The result? Bloated, unmanageable systems and expensive rewrites that kill momentum.

AI is powerful, but if you’re just going with the flow, you’re not innovating—you’re setting up for a collapse. Cutting documentation and skipping structure doesn’t make you agile; it makes you the next case study in what NOT to do.
I just dropped an article about how vibe coding wrecked a well-funded startup, and why getting serious about standards is the only way to win long-term. If you want to stop burning money and actually build sustainable systems, do yourself a favor and read this piece.

Because “move fast and break things” only works if you know how to fix them. If you’re tired of shortcuts that lead to dead ends, check out the story.

#VibeCodingIsStupid #Cloud #AI #SoftwareEngineering #TechDebt #Innovation #DevFail

Are Tech-to-Tech AI Deals Just a Legalized Ponzi Scheme?

Let’s call it what it is: The current wave of AI “innovation” seems less about delivering real value and more about inflating the valuations of technology companies through an endless loop of tech-to-tech transactions. Billions are changing hands between cloud providers, AI startups, and software vendors, but where is the real-world impact? These deals make big headlines, but on closer inspection, what we see is value cycling within an enclosed ecosystem—money and market cap simply chasing each other in circles. This is beginning to look and feel like a legalized Ponzi scheme, where perception trumps reality and insiders cash in long before tangible results reach the broader economy.

The real test for AI isn’t tech companies selling infrastructure or AI capabilities to one another. It’s whether traditional enterprises—the Global 2000 companies—can actually harness this technology to transform operations and drive measurable outcomes. But most of these companies remain in the early, experimental phases (if they’ve started at all), even as the hype machine for AI runs at full blast. Meanwhile, tech giants are getting richer and more powerful just by selling to each other, not by solving problems for the real world.

I’ve said it before, and I stand by it: The current model isn’t sustainable, and the market will correct. If we keep recycling valuation in closed loops—without delivering on the true promise of AI for healthcare, manufacturing, retail, logistics, and every other core industry—we’re simply inflating a bubble that will pop. This system is propped up by optimism and self-induced hype, not real innovation or customer value.

So let’s have an honest conversation: Are we building the future, or are we just inflating numbers and moving money around in plain sight? Is today’s AI frenzy any better than the Ponzi schemes of the past, just done with fancier tech and bigger checks? How do we pivot this industry toward genuine, real-world value before the bubble bursts—again? I want to hear your perspective.

#LegalizedPonziScheme #TechBubble #AIBubble #ArtificialIntelligence #EnterpriseAI #BusinessValue #DigitalTransformation #Innovation #CloudComputing

Why Are the Big Consulting Firms Silent on the AWS Outage?

It's striking how little we've heard from the major consulting firms regarding the recent AWS outage. With so many enterprises entrusting their transformation journeys to these advisors, their silence raises questions: Are they avoiding tough conversations about cloud risk? Is it easier to tout cloud success stories than to address operational vulnerabilities?

As leaders in tech, we should demand open, honest dialogue around resiliency, multi-cloud strategies, and risk management—especially when major outages occur. Thought leadership means tackling the hard topics, not just the headline wins.

#CloudComputing #AWS #Consulting #CloudResilience #CloudStrategy #ITLeadership #Outage #EnterpriseIT #TechTrends #RiskManagement

Private cloud is now a strategic priority.

Public cloud services have long been perceived as the primary choice for hosting cloud workloads, as highlighted in VMware’s Private Cloud Outlook 2025 report. However, the data gathered from participants in the study suggests a contrasting reality. Their comprehensive research uncovers that a significant 69% of enterprises are actively migrating workloads back from public cloud environments. This trend is primarily driven by heightened concerns over security vulnerabilities and the unpredictability of associated costs.

Enterprises are increasingly cautious about the potential risks of data breaches and unauthorized access that can occur in public cloud settings. These security apprehensions are prompting businesses to reassess their cloud strategies and explore alternative options. Additionally, the fluctuating nature of public cloud expenses, which can vary based on data usage and other factors, is causing enterprises to reevaluate the economic viability of such solutions.

To delve deeper into these issues, we invite you to join our live event tomorrow featuring me. I will lead an insightful discussion on the often-overlooked expenses of hybrid cloud models and provide guidance on strategic planning for 2026. This event promises to equip you with the knowledge needed to recalibrate your organization's cloud strategy, ensuring it is robust and cost-effective in the face of evolving technological landscapes.

https://lnkd.in/e9Y9KZVT

Resilio Adam Kranitz
-------------------------

AWS is down, AWS is down!    Everybody run in circles with your hair on fire. I’ll tell you when to stop.   😊


Amazon cloud computing outage disrupts Snapchat, Ring and many other online services https://lnkd.in/e7W-rDjx

Why the EU’s Cloud Moves Signal a Global Cloud Evolution

We're watching a pivotal conversation unfold in the European Union right now—one that is already shaking up how enterprises think about their cloud strategies worldwide. For years, the major US-based public cloud hyperscalers—AWS, Azure, and Google Cloud—have dominated the market, driving innovation but also concentrating workloads and, frankly, risk.

But the EU is taking a second look. In the wake of high-profile outages and mounting costs, policymakers and enterprises are openly questioning the wisdom of relying so heavily on a handful of hyperscalers based outside their borders. We’re now seeing a push toward distributing workloads to a wider array of providers: sovereign clouds, colocation partners, regional managed service providers, and other non-US cloud entities.

Why does this matter beyond Europe? Because these decisions set precedents that the rest of the world is sure to study carefully. If the EU successfully reduces its dependency on US hyperscalers, I believe other regions—facing similar concerns over data sovereignty, resiliency, and cost—will follow suit in the next 2–3 years. Many enterprises may not talk about it publicly, but I’m convinced that the “great cloud reevaluation” is quietly underway across the globe.

Does this mean the major hyperscalers will lose significant revenue? Honestly, I doubt it. The exponential growth of AI and generative AI workloads will more than fill any gaps left by traditional enterprise migrations. But what we will see—and should encourage—is a safer, more resilient, and more distributed cloud landscape. Our critical workloads and data sets belong across a diverse mix of platforms: on-premises, across multiple clouds, and yes, with trusted regional partners.

I’ll be following this story closely. I recommend you do too. The next phase of cloud is about optionality, resilience, and smart risk management—and the EU’s decisions are a key signpost for what comes next.

#cloud #multicloud #digitaltransformation #cloudstrategy #EU #cloudcomputing #datasecurity

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