AI megaprojects, outages, and breaches defined 2025. Here’s what they mean for how you work in 2026—and how to build smarter, more resilient workflows with AI.
Most teams discovered the same thing in 2025: your work is only as strong as the infrastructure underneath it. AI got faster, data centers turned into their own cities, and a couple of bad days at Cloudflare quietly cost the world millions of hours of productivity.
This matters because AI, technology, work, and productivity are now the same conversation. If you rely on SaaS tools, cloud platforms, or AI assistants to get things done (which is almost everyone), the stories that shaped 2025 aren’t just “tech news” — they’re a preview of how your next year of work will feel.
In this post, I’ll break down the biggest tech moves of 2025 and translate them into something practical: what they mean for how you work, how reliable your tools really are, and what you should do now to work smarter, not harder, in 2026.
1. AI Is Rewriting the Power Grid (And Your Infrastructure Strategy)
The key trend behind the wildest headlines of 2025 is simple: AI is hungry, and power is the new bottleneck. Google’s space-powered data centers, OpenAI’s Stargate in Texas, and Kevin O’Leary’s off-grid Wonder Valley project are all chasing the same thing — compute at insane scale.
From solar in space to gas in Texas
Three projects summed up the new era of AI infrastructure:
- Google Project Suncatcher – Satellites running AI workloads in orbit, fed by continuous solar power. The idea: use space as a solar-powered compute layer rather than fighting over land, cooling, and local grids.
- OpenAI + Oracle + SoftBank’s Stargate (Texas) – A $500B AI data center network, starting with a 900-acre site loaded with around 50,000 Nvidia Blackwell chips and powered by a 1.2-gigawatt natural gas plant.
- Wonder Valley AI (Alberta) – Kevin O’Leary’s 7.5-gigawatt off-grid complex running on stranded natural gas, designed to both run AI and feed energy back to local communities.
Different locations. Different politics. Same story: whoever can feed AI with the most reliable power and compute wins the next decade.
Why this matters for your day-to-day work
You don’t need your own data center to care about this. What you do need to understand is how it affects your tools and productivity:
- AI capacity won’t be the limiting factor for most teams. The big players are investing trillions in infrastructure. That means more powerful AI models, more features, and more availability over the next few years.
- Latency and reliability will become a competitive edge. If your workflow depends on AI (think code generation, content production, analytics), tools that sit closest to serious infrastructure will feel meaningfully faster and more responsive.
- Cost structures will change. As energy and compute dominate costs, vendors will get aggressive about usage-based pricing. Free tiers will shrink, and “unlimited” will quietly disappear.
What to do now:
- Audit which work in your org truly benefits from AI (idea generation, summarization, coding, research) and route those into AI-first workflows.
- Prefer tools that clearly explain their infrastructure story (regions, redundancy, SLAs) rather than just promising “AI features.”
- Start tracking AI usage like any other cost center instead of letting it become an invisible expense.
2. When One Company Blinks, Your Entire Workflow Stalls
The Cloudflare outages in November and December 2025 were the bluntest reminder of the year: centralization is convenient until it isn’t. One provider handling close to a fifth of global web traffic had back-to-back issues, and suddenly Spotify, LinkedIn, Canva, and countless other services just… stopped.
For knowledge workers, that translated to:
- Missed client calls due to broken conferencing links
- Design teams frozen because their online tools were unreachable
- Marketers, recruiters, and sales reps unable to reach key platforms
One vendor glitch; entire workdays derailed.
AI as a resilience layer, not just an assistant
Most people talk about AI as a “productivity boost.” I think that’s the second most interesting use. The bigger play is this:
AI can help you design workflows that survive outages, failures, and weird edge cases.
Concrete ways to use AI to harden your operations:
- Redundancy planning: Ask an AI system to map your critical workflows (sales pipeline, content production, support, finance) and explicitly identify single points of failure. Then have it propose backup tools or offline flows.
- Dynamic routing: For technical teams, AI-assisted infrastructure config can help design multi-CDN, multi-region, or failover strategies that aren’t a nightmare to maintain.
- Runbooks and playbooks: Use AI to write, refine, and simulate incident response playbooks — including what non-technical teams should do when major tools go offline.
A simple checklist for “Cloudflare-proof” productivity
For non-engineering teams, here’s a straightforward baseline:
- Have at least one offline-friendly tool per core activity.
- Writing: local docs or markdown editors.
- Presentations: desktop slide tools.
- Task management: exportable spreadsheets or simple project boards.
- Keep backups of critical assets locally. Key decks, contracts, RFP templates, pitch assets — don’t rely solely on a single SaaS provider.
- Document “outage mode” rules. For example: if CRM is down, where do reps log deals? If your design system is offline, what do teams use as a fallback?
AI doesn’t remove risk. But used well, it shrinks the blast radius of the next Cloudflare-style incident.
3. Security Took Center Stage: Credentials Are the New Toxic Waste
2025 also had a theme that should make every leader slightly uncomfortable: your logins are probably already out there.
Two major incidents stood out:
- A 47GB exposed database with 184 million credentials from accounts tied to Microsoft, Google, Apple, Facebook, and PayPal.
- A 3.5TB dataset with 183 million accounts and over 16 million Gmail addresses, many of which hadn’t appeared in public breach lists before.
Both were fueled by infostealer malware, quietly grabbing passwords and tokens from infected devices. Even worse, many of these credentials hadn’t yet been “burned” — they were fresh fuel for phishing and credential-stuffing attacks.
The real shift: from perimeter security to identity chaos
The old mental model was: “Don’t get hacked.” The new reality is harsher:
Assume your credentials are compromised. Design your work and systems around that assumption.
Where AI and smarter technology can actually help:
- Password and access hygiene: Modern password managers and security tools use AI to flag weak, reused, or suspicious credentials and suggest safer policies.
- Anomaly detection: AI-driven security tools can spot odd login patterns — unusual locations, times, or devices — much faster than traditional rule-based systems.
- Phishing resistance training: AI can generate realistic phishing simulations for your team and then analyze where people struggled, so you can train more effectively.
Practical moves for 2026
If you run a team, I’d treat these as non-negotiable:
- Enforce multi-factor authentication for any account that touches money, customer data, or internal IP.
- Use a centralized, enterprise-grade password manager; ban password sharing in chat or documents.
- Run quarterly security “fire drills”: use AI to design scenario-based tabletop exercises (e.g., “A key exec’s email is compromised; what happens next?”).
If AI is powering more of your work, you can’t afford for your identity layer to be the weakest link.
4. Devices and Satellites: The New Frontline of Work
While billion-dollar AI cities stole headlines, a quieter shift happened in your pocket and in orbit.
iPhone 17 Pro: Your workstation, not just your phone
Apple’s iPhone 17 Pro line leaned all the way into professional workflows:
- Vapor-chamber cooling for sustained heavy workloads (think long 4K shoots, mobile editing, or on-device AI tasks)
- Lidar scanning and enhanced depth mapping for creators, AR, and 3D workflows
- Up to 2 TB of storage, USB 3 speeds, and full ProRes RAW capture
For creators, consultants, and field workers, this isn’t a gadget upgrade — it’s a genuine shift toward phone-as-primary workstation. You can:
- Shoot, edit, and ship pro-grade content without a laptop
- Capture detailed spatial data for design, construction, or product demos
- Run heavier on-device AI tasks with fewer thermal issues
Pair that with cloud-based AI tooling, and suddenly your “mobile workflow” isn’t a compromise — it’s your main stack.
Apple vs. Starlink: Why space matters to your calendar
Another 2025 story that sounds distant but isn’t: Apple’s Globalstar partnership clashing with Elon Musk’s Starlink over satellite spectrum and direct-to-device services. That fight isn’t about prestige; it’s about who controls connectivity in the places where fiber and 5G aren’t an option.
If you:
- Work remotely in rural areas
- Travel frequently
- Rely on always-on access for sales, support, or operations
…then satellite connectivity battles directly affect whether your “work from anywhere” promise actually holds up.
As satellite-to-phone services mature, you’ll see:
- Fewer “dead days” due to connectivity
- More realistic options for globally distributed teams
- New failure modes — because now your uptime depends on space infrastructure and spectrum policy, not just cables in the ground
Again, the practical rule: diversify. Have at least two viable connectivity methods if your work is mission-critical.
5. AI, Geopolitics, and the New Risk Profile for Knowledge Work
One of the most under-discussed stories of 2025 was OpenAI uncovering China-linked operations using ChatGPT and Meta’s Llama models for surveillance and propaganda.
These campaigns produced Spanish-language disinformation and code for tracking protests in Western countries. That’s not some abstract policy debate — it’s a signal of how AI is now embedded in geopolitics, information warfare, and social movements.
What this means for your team
Three direct implications for anyone working with AI and information:
- Information integrity is now a core productivity challenge. If your research, marketing, or strategy work relies on online data, you’ll increasingly encounter AI-generated noise, propaganda, and subtle manipulation.
- Your AI stack is part of your threat surface. How you configure, log, and govern access to AI tools matters, especially if your organization handles sensitive information.
- Media literacy becomes a work skill, not just a civic one. Teams need training to question sources, recognize synthetic content, and triangulate claims.
AI can help fight this, too:
- Use AI to cross-check claims across multiple sources.
- Run content through detectors that highlight likely synthetic or manipulated media.
- Build internal knowledge bases so your team doesn’t repeatedly rely on the open web for the same critical facts.
Teams that treat “truth filtering” as a core part of their workflows will simply make better decisions than those who don’t.
6. How to Work Smarter in 2026: A Practical Playbook
If 2025 showed anything, it’s that scale cuts both ways: bigger data centers, bigger outages, bigger leaks, bigger ambitions. The smart move for 2026 is not to chase every trend, but to re-architect how you work around three principles:
-
AI as a co-worker, not a toy
- Assign AI clear roles in your workflows: drafting, summarizing, coding, QA, analysis.
- Standardize prompts and templates so results are consistent and sharable across the team.
- Track the hours saved the same way you’d track automation or process improvements.
-
Resilience by design
- Map every critical process and identify single points of failure in tools, access, and people.
- Use AI to propose backup processes, alternative tools, and offline modes.
- Run periodic “chaos drills”: simulate outages or account lockouts and see how long work can continue.
-
Security as a work habit, not an IT project
- Normalize password managers, MFA, and least-privilege access.
- Use AI to generate and refine training scenarios that feel real to your teams.
- Treat compromised credentials as expected and design your processes accordingly.
The reality? It’s simpler than it looks. The organizations that will win in this new AI and technology landscape aren’t the ones with the flashiest tools. They’re the ones who quietly build reliable, boring, robust systems around those tools — systems that keep work moving whether a satellite, a CDN, or a password fails.
As AI becomes the backbone of daily work and productivity, the question to ask yourself is straightforward:
Are you building a workflow that assumes everything will work, or one that stays productive even when it doesn’t?
The choices you make in 2026 will answer that for you.