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During the past few weeks it has been impossible to dodge ‘expert’ media commentary about an impending AI bubble that is about to burst. Thanks to stellar Q2 earnings from NVIDIA those doubts seem to have been put to rest.

AI demand is climbing. The proof is visible across earnings reports, international trust polls and not surprisingly, even global trade deals. This fortnight revealed where the real momentum is, and where significant risk still lurks. If you lead strategy or operations these are your leverage points.

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1. NVIDIA’s Q2 Blowout: The AI Boom Is Real

NVIDIA just posted record-breaking earnings in Q2, signaling that demand for AI chips remains exceptionally strong.

What this means for you:

• Capital is still flowing into compute-heavy AI; not just experiments, but serious deployments.
  
• If you’re building or training AI models, securing compute or partnerships with chip providers is still mission-critical.

Action Tip: Review your compute roadmap and check partnerships. Check if you can lock in capacity or negotiate favorable access now before costs spike again.

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2. East vs. West: Trust in AI Is Higher in China

According to a new poll, public trust in AI in China is significantly higher than in Western nations.

What this means for you:

• Adoption risk in China is different; consumer-facing AI products may scale faster there.
  
• In Western markets, user trust must be earned more deliberately.

Action Tip: If you’re entering or scaling in China, you will need to prioritize consumer AI use-cases. If you’re focused on Western markets, you will need to build trust via transparency and explainability early.

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3. US-Saudi AI Chip Deal: Strategic Supply Chain Opening

The U.S. has approved a major deal to supply AI chips to Saudi Arabia.

What this means for you:

• The geopolitics of AI hardware is shifting. Saudi Arabia could become both a customer and a partner for compute infrastructure.
  
• There may be lower-cost, high-capacity compute alternatives through MENA-based data centers or partners.

Action Tip: Explore partnerships in the Middle East, whether through data center collaboration, compute-sharing or co-development of AI infrastructure.

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4. Research Risk: AI Use Undermining Integrity

A global survey has found widespread use of generative AI in research offices, raising fresh questions over integrity and plagiarism and consequently credibility.

What this means for you:

• AI can accelerate research, but it can also distort outcomes and reduce trust in your data-driven decisions.
  
• For businesses relying on internal R&D, ensuring the ethical use of AI matters as much as innovation.

Action Tip: Define safeguards for AI use in your research workflows. Review data provenance, require human review and create policies for acceptable use of generative models.

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5. India’s AI Adoption Gap: Warning Sign for Innovators

Nearly 45% of Indian companies are still in the very early stages of adopting AI, according to a recent report.

What this means for you:

• There’s a large pool of Indian firms that may soon accelerate. Those that move first could dominate local and regional AI markets.
  
• For global businesses, this is a signal to invest in India now, either via partnerships or localized AI products.

Action Tip: Assess your India strategy, whether it is through investing or collaborating to help shape the market as it matures.

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That’s All for This Fortnight

The AI landscape remains dynamic. Compute demand is surging. Trust is uneven. Research practices are being challenged. But for business leaders who read between the headlines, these developments offer significant opportunity.

Until next time,

The AI-First Mindset Team

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About Us

At AI-First Mindset we work with leaders and teams to bridge the gap between knowing AI and using it. This includes easy orientations through hands-on workshops, AI integration bootcamps and finally business-process automation.To explore how we can help, contact us at aifirstmindset.ai.