AI is no longer a side experiment or innovation lab project. In 2025, it crossed the line into enterprise infrastructure. Companies that fail to rewire their operating models now risk losing the entire next decade.

1. Generative AI Spending Has Exploded

• $37B spent on GenAI in 2025, up from $11.5B in 2024 — a 3.2x YoY jump

• GenAI now represents 6% of the global SaaS market

• AI spend is no longer discretionary—it’s becoming a default line item

What changed:
Enterprises stopped asking “Should we try AI?” and started asking “Where does AI deliver immediate productivity?”

2. Buy > Build Is the New Enterprise Default

• 76% of AI use cases are purchased, not built in-house

• Enterprises want speed, reliability, and measurable ROI

• Internal model-building is increasingly limited to hyperscalers and top-tier tech firms

Implication:
The AI advantage now comes from integration and workflow redesign, not custom model development.

3. Coding Is the Killer AI Use Case

• Coding tools are the fastest-growing AI category

• $4B spent on AI coding tools alone in 2025

• AI-assisted development is becoming a baseline expectation, not a differentiator

Signal:
AI is already reshaping how software is built—quietly, deeply, and permanently.

4. Power Is Shifting in the LLM Market

• Anthropic leads enterprise LLM spend with 40% market share

• OpenAI drops to 27%

• Enterprises are prioritizing reliability, safety, and governance, not hype

Takeaway:
Model choice is becoming a risk-management decision, not a brand preference.

5. Infrastructure Is Where the Money Is Going

• $18B went into the AI infrastructure layer in 2025

• Compute, orchestration, data pipelines, and security are now strategic assets

• AI infrastructure is being treated like cloud was a decade ago

Bottom line:
AI’s real winners will be infrastructure builders, not feature-level tools.

6. SaaS Is Being Rewritten by GenAI

• AI SaaS market projected to hit $101.7B

• GenAI features now appear across ~200 software categories

• 56% of SaaS companies already launched or tested AI features

• Another 25% have AI on their product roadmap

Top product use cases:

• Content generation

• Personalization

• Design and workflow automation

7. Monetization Models Are Changing

• Shift toward usage-based pricing

• AI features increasingly gated behind premium tiers

• Revenue is tied directly to value delivered, not licenses sold

Result:
AI is reshaping not just products—but business models.

8. Humans + AI: The Final Constraint

Harvard research reinforces a critical truth:

• AI value depends on how people actually use it

• Productivity gains come from workflow redesign, not tool access

• Organizations that don’t retrain and restructure will underperform—regardless of spend

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