The Stock That Keeps AI From Tripping Over Its Own Data

Author

Noah Zelvis
January 13, 2026

AI is heavier software. More events, more users, more bots, more alerts, more security noise, and way more systems talking at once.

The winners are not always the flashy apps. Sometimes it is the boring layer that keeps everything in sync, in real time, without blowing up.

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Cloud Computing

Google Quietly Becomes The Brain Behind Apple’s AI Push

Google (NASDAQ: GOOGL) has secured one of the most strategically important AI wins in consumer tech by powering Apple’s next generation of AI features.

Gemini models and Google’s cloud stack will now sit underneath Apple’s foundation models, including future upgrades to Siri.

This move shifts Google from being a visible AI competitor to an invisible backbone.

Instead of fighting for user attention, Google supplies intelligence at scale inside hundreds of millions of Apple devices.

Apple Gets Capability, Google Gets Reach

Apple has struggled to push Siri beyond incremental improvements, even as rivals sprinted ahead with conversational and agentic AI.

Plugging into Gemini gives Apple immediate access to advanced reasoning, language understanding, and cloud scale without abandoning its privacy-first architecture.

For Google, the upside is distribution. Gemini expands far beyond Google-owned surfaces and becomes embedded in one of the largest hardware ecosystems on the planet.

Antitrust Pressure Meets AI Reality

The partnership lands while Google remains under intense regulatory scrutiny, especially around its historical role as Apple’s default search provider.

Unlike search placement deals, this AI collaboration is non-exclusive and structured around capability rather than defaults.

That distinction matters. AI is becoming core infrastructure, not a feature layer.

With Gemini now powering Apple intelligence quietly in the background, Google reinforces its position as a foundational AI supplier even as the competitive landscape reshapes itself.

Infrastructure

IBM Pushes AI To The Edge As Enterprises Ditch The Cloud Middleman

IBM (NYSE: IBM) is expanding its edge AI footprint by deepening its partnership with Datavault AI, bringing ultra-low-latency, secure AI processing closer to where data is created.

The deployment targets enterprise workloads that demand real-time intelligence without relying heavily on centralized public clouds.

Watsonx is IBM’s enterprise AI platform for building, deploying, and governing AI models across cloud, on-premises, and edge environments.

By combining WatsonX with zero-trust micro data centers, IBM positions edge computing as a serious alternative to cloud-first architectures.

The strategy reflects a shift toward faster decision-making, tighter security, and reduced exposure to external infrastructure risks.

Watsonx Evolves Beyond The Cloud

The Watsonx platform continues to expand as a hybrid AI system capable of running across cloud, on-premises, and edge environments.

Its strength lies in combining foundation models, real-time analytics, built-in governance, and enterprise-grade security into a single stack.

This evolution allows enterprises to process and tokenize data instantly at the edge, turning raw information into monetizable digital assets.

IBM is effectively turning AI into an operational layer, not just an analytics tool.

Profits Follow Infrastructure Control

Edge AI opens doors to regulated industries that demand sovereignty, security, and low latency, including government, finance, and critical infrastructure.

IBM’s approach targets long-cycle enterprise contracts rather than consumer experimentation.

As enterprises rethink cloud dependency, IBM’s edge-first AI strategy strengthens its role as a foundational technology provider.

The move positions IBM to capture value where data is created, secured, and acted on in real time.

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Utilities

Microsoft Is Teaching Its Data Centers Some Basic Manners

Microsoft (NASDAQ: MSFT) is rolling out a new community-focused push to make sure its U.S. data centers do not quietly wreck local power systems.

The company says it will pay full utility rates that actually reflect the real cost of electricity, instead of leaning on public infrastructure to absorb the hit.

On top of that, Microsoft plans to work directly with utilities to expand grid capacity when needed, adding new power supply and infrastructure so data center growth does not translate into higher electricity bills for everyone else.

AI Is Thirsty, Microsoft Says It Will Refill the Glass

Data centers consume massive amounts of water for cooling, and Microsoft is now committing to replenish more water than it uses.

This includes regional water restoration projects tied directly to where its data centers operate.

To keep itself honest, Microsoft will begin publishing water usage data for each U.S. data center region, alongside progress updates showing how much water it is putting back into local systems.

The Real Message Behind the Pledge

This move signals a shift in how Big Tech responds to public backlash around AI infrastructure.

Data centers are no longer invisible warehouses of compute; they are local utilities in everything but name.

Microsoft is positioning itself as a responsible grid citizen, trying to scale AI without triggering political, environmental, or consumer blowback as demand keeps rising.

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Recent Tech Movers

CrowdStrike (NASDAQ: CRWD)

Security Autopilot, Still in Demand
CrowdStrike keeps showing up in the same place on every CIO checklist: stop breaches, shrink response time, and do it without doubling headcount.

That is why the story tends to hold up even when software budgets get picky. The AI angle here is practical, not hypey, because security teams are drowning in alerts.

The more automation that actually works, the more valuable the platform becomes.

My take: If the market mood improves, cyber leaders usually catch a bid early.

If the market mood worsens, they often get defended because no one wants to be the company that cut security and paid for it later.

monday.com (NASDAQ: MNDY)

Less Meetings, More Done
This one is the friendly face of productivity software. It wins when teams want a system that helps them run projects without feeling like a spreadsheet punishment.

The AI tailwind is simple: automate the repetitive parts, summarize the noise, and keep everyone aligned without ten status calls.

If businesses keep trying to do more with the same headcount, tools that reduce friction tend to stick.

My take: This is a vibes stock in the best way. When execution looks clean, the multiple can expand fast. When growth investors get nervous, it can deflate just as fast.

Size it like a growth name, not like a bond.

Elastic (NYSE: ESTC)

Search and Observability, With a Real AI Use Case
Elastic is the pick-and-shovels layer for companies that need to search across messy data and monitor systems at scale.

That matters more as AI pushes data into weirder formats and workflows. If your app is slow or broken, you need to find the issue quickly.

If your enterprise is sitting on a mountain of documents and logs, you need search that does not feel like 2009.

My take: This is one of those stocks that can look quiet, right up until the market remembers how many businesses run on search, logs, and monitoring.

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The Long Game In AI

Confluent (NASDAQ: CFLT)

The Real-Time Data Stock That Makes AI Feel Instant
Confluent is not the app your friend brags about. It is the pipe. It moves data between systems in real time, so the business can react in real time.

That sounds boring until you realize AI features are basically hungry little engines that want fresh data, constantly. If data is stale, the output is stale.

If the pipeline is laggy, the user experience is laggy. And if your systems cannot talk cleanly, your AI rollout turns into a slow-motion spreadsheet tragedy.

The reason Confluent works as a longer idea is that it sits under multiple themes at once: streaming data, cloud modernization, and AI workloads that need fast, reliable event flow.

In plain English, it helps companies get the right information to the right place at the right time, without duct tape.

Scorecard You Can Use

  • AI needs motion, not storage: Models and agents love fresh events. Streaming becomes the difference between instant and irrelevant.

  • The plumbing toll booth: If more systems connect, more data flows through. Usage-driven stories can scale nicely when adoption sticks.

  • Enterprise stickiness: Once a company builds around a data backbone, ripping it out is painful. That is good for retention.

Why the Market Cares

  • Real-time is the new normal: Consumers expect instant everything, and businesses want instant insight. Streaming is the backbone.

  • AI agents create more events: More automated actions mean more messages flying around your stack. Somebody has to route them.

  • Cleaner data stories rerate: Markets reward infrastructure that becomes a default layer, even if it is not flashy.

What Could Spook It

  • Sales cycles can get picky: If budgets tighten, big platform decisions can drag out.

  • Competition is real: Cloud giants and open-source alternatives will always try to win wallet share.

  • Execution matters: This stock needs steady proof that customers expand usage, not just sign and stall.

What to Watch Next

  • Net retention and expansion: Are customers turning it into a bigger piece of the stack?

  • Cloud partnerships: Any sign of deeper integrations can help distribution.

  • AI messaging with receipts: New features are nice. Clear customer wins are better.

Actionable Take

  • Builders: Treat it like infrastructure with a runway. Start small, add on pullbacks, and give it time to compound if execution stays clean.

  • Traders: Respect volatility. Use levels and risk controls because this one can swing hard on sentiment.

  • Bottom line: If you believe software keeps getting more real-time and more AI-driven, the companies that move data fast tend to stay busy. Confluent is a clean way to bet on that without picking the winning chatbot.

Everything Else

  • 📱 Apple is once again on top of the global smartphone market, holding a clean 20% share and proving that even in a “mature” market, a shiny logo still beats specs on a slide.

  • 💼 London’s finance world is scrambling for AI tech experts as vacancies jump 12%, turning compliance jobs into something that suddenly needs a Python certification.

  • 🔐 Israeli cybersecurity startup Torq just raised $140 million at a $1.2 billion valuation, proving that even when valuations cool, defending networks still pays like offense.

  • 🛒 Walmart teamed up with Google’s Gemini to power a new AI shopping tool, because who needs a cart when you can just tell the algorithm what’s missing in your fridge?

  • ⚡ Analysts are warning that AI data-center power plays like Bloom Energy might be running too hot, as investors pile into the “AI power grid” trade like it’s the next semiconductor boom.

That's our coverage for today; thanks for reading! Reply to this email with feedback or any tech stocks you want me to check out.

Best Regards,
—Noah Zelvis
Tech Stock Insider