- The Loop
- Posts
- 🔆 The AI Cost Iceberg: Total Cost of Ownership (part 1 of 2)
🔆 The AI Cost Iceberg: Total Cost of Ownership (part 1 of 2)
Programmable biology, IP-friendly AI for creators, and a more complete picture of what it costs to implement AI successfully.
Allegra Guinan & Emma G Moller
February 20, 2025
Was this email forwarded to you? Sign up here
🗞️ Issue 58 // ⏱️ Read Time: 8 min
Hello 👋
When people talk about the cost of AI, there's often a focus on the headline-grabbing training costs of large models like Deepseek-R1 and GPT-4. However, the true cost of AI adoption is far more nuanced and complex. This week, we're breaking down the real numbers behind AI development, training, and implementation to help decision-makers better understand the financial impact of AI.
In this week's newsletter
What we’re talking about: A more comprehensive and realistic assessment of the total cost of ownership (TCO) of organizations who wish to build and deploy AI systems.
How it’s relevant: Most companies are not building foundational models, they’re integrating 3rd party AI tools into their products and services. With most discussions around AI costs focusing on initial training and inference, organizations are left with a skewed understanding of how much to budget for their AI transformation.
Why it matters: Miscalculating or overlooking the TCO of AI implementation can severely disrupt an organization's strategic initiatives including forced compromises, delayed innovation, or strained resources across departments.
Big tech news of the week…
🎨 Adobe has launched its Firefly Video Model in public beta. Firefly is only trained on content that Adobe has permission to use, which includes licensed content from Adobe Stock and public domain content, making it the only generative AI video model that is IP (Intellectual Property)-friendly and commercially safe.
⚖️ The first U.S. ruling on fair use in AI-related copyright litigation has been made. A federal judge in Delaware has ruled that Thomson Reuters' competitor, Ross Intelligence, violated copyright law by using Thomson Reuters' content to build a competing AI-based legal platform. The ruling is seen as a significant victory for content owners in their ongoing legal battles against AI companies, potentially setting a precedent for future cases involving AI and copyright infringement
🧬 Latent Labs, a new startup founded by a former Google DeepMind scientist, launches with $50M in funding to make biology programmable. They aim to enable researchers to “computationally create” new therapeutic molecules from scratch, upending the current drug-discovery process.
🇬🇧The UK’s AI Safety Institute becomes AI Security Institute to “reflect its focus on serious AI risks with security implications, such as how the technology can be used to develop chemical and biological weapons, how it can be used to carry out cyber-attacks, and enable crimes such as fraud and child sexual abuse.”
AI Total Cost of Ownership
For most organizations, the cost of AI systems doesn't end when a foundational model is released into general availability; that's where it begins. Total cost of ownership (TCO) in the AI context goes beyond the traditional definition of purchase and deployment costs. It encompasses the entire journey of AI adoption: from initial acquisition and customization, through ongoing operations and maintenance, to the eventual evolution or retirement of the system.
Unlike traditional IT systems, AI TCO is characterized by unique challenges:
the need for advanced hardware infrastructure
specialized expertise
continuous model updates
data quality management, and
cultural transformation.
As organizations rush to adopt AI, understanding these comprehensive costs becomes crucial for sustainable implementation and long-term success.
Today, we’ll discuss the cost considerations of build vs. buy, pay-as-you-go, and customization. Other key components like Design Thinking and Cost of Culture will be covered in next week’s newsletter, making this newsletter Part 1 out of 2. Let’s get into it!