News Analysis
The Gist
- AI innovation costs drop dramatically. DeepSeek R1 slashes AI model costs to 3-5% of previous levels, reshaping the economics of AI development.
- Shifting focus to application. Lower costs move the spotlight from infrastructure spending to what can actually be built with AI.
- Optimism meets uncertainty. Cheaper AI could spark breakthroughs, but questions remain about its potential impact and true value.
Building with AI might cost 5% of what it did a week ago. What gets built has never been more important.
I want to try to cut through some of the noise that’s circulating on the rise of DeepSeek R1, the new open source AI model from China. We’re going to see so much writing about the model, its origins and its creators’ intent over the next few days. But no detail will be more meaningful than how cheap DeepSeek makes running AI models.
Infrastructure spending, until this point, has buoyed the entire AI industry. Tech companies spent billions of dollars on data centers and compute, and promised hundreds of billions more, grounding Wall Street’s expectations of the technology’s potential.
OpenAI raised $6.6 billion last year, much of it to be spent on training, giving investors a sense of what it expected in return, and hence what they might expect on the dollars they put in.
Related Article: DeepSeek Shakes Up AI Game: $1 Trillion at Stake
Table of Contents
A Shift in AI Economics
But DeepSeek’s emergence changes the equation. The company not only learned how to build a leading AI model with far less up front investment, its architecture made cutting edge AI available at a fraction of the cost. DeepSeek today runs at 3-5% of the price of OpenAI’s comparable o1 models. And so developers can now build AI applications at a much lower cost than before.
The focus will therefore soon turn to what you can build with AI vs. how much compute you can assemble to build it. That’s scaring everyone, both because massive infrastructure spending is no longer the benchmark, and because what developers have built with generative AI so far has been slightly underwhelming.
Yes, enterprises have used GenAI for real optimizations, and Salesforce has agents now. But take away the billions spent on infrastructure, and just show the AI products themselves, and the multi-trillion dollar hype hardly feels justified.
Opportunities and Uncertainties With DeepSeek
The good news is that building with cheaper AI will likely lead to new AI products that previously wouldn’t have existed. It will likely turn expensive enterprise proof of concepts into actual products. And it may give new hope to some working on the wasteland of consumer AI (Apple, of course, was up 3.5% yesterday).
The bad news is we still don’t fully know what to do with generative AI. And so the promise that more efficiency will lead to greater usage isn’t a sure thing. We’re also not sure whether the DeepSeek breakthrough will lead to even greater advances in AI technology, or whether it will immediately commoditize the state of the art, creating less incentive to build it. Or perhaps something in the middle.
Even if there’s a lot to be optimistic about today, you can see why people are a bit jittery. Things are about to get real.
Core Questions Around DeepSeek
Editor's note: These questions explore the implications of DeepSeek R1 for AI innovation and industry dynamics.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
Oct
15
Agentic AI Playbook Real-World Customer Service Use Cases You Can Deploy Now
Boost self-service by 30% and slash call volume by 63% with agentic AI.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
How will DeepSeek R1 impact AI development and infrastructure spending?
DeepSeek R1’s cost efficiencies could redefine priorities in AI, moving focus from heavy infrastructure investments to more accessible applications and innovation.
What are the biggest opportunities and risks of the AI cost paradigm?
Lower costs democratize access to AI technology, enabling smaller companies and independent developers to create applications that were previously out of reach due to high infrastructure and computational expenses. This could lead to a surge in innovation, turning proof-of-concept projects into viable products and expanding the AI ecosystem beyond enterprise-level solutions.
