deepseek's r1 is an impressive model, particularly around what they're able to deliver for the price.
we will obviously deliver much better models and also it's legit invigorating to have a new competitor! we will pull up some releases.
— Sam Altman (@sama) January 28, 2025
The introduction of a new AI model that operates at less than a tenth of current industry costs is a game-changer. It opens the way for a new generation of affordable AI solutions that will transform how organizations approach artificial intelligence. For the marketing industry, this cost revolution promises to reshape everything from customer engagement to campaign optimization.
When running advanced AI systems costs thousands of pounds per month, organizations must carefully ration their use. But what happens when that cost drops by 90%? AI transforms from a carefully rationed resource to a ubiquitous utility.
People don’t talk enough about a giant DeepSeek achievement over most US models – it actually has a reasonable name.
— Ethan Mollick (@emollick) January 30, 2025
Another odd aspect of the sudden attention to DeepSeek is a lot of people assuming it is the first open weights* models. One of the biggest companies in the US has spent billions making open models & intends to keep doing so.
*not open source, there is no access to training data
— Ethan Mollick (@emollick) January 29, 2025
Marketing teams could deploy AI across every customer touchpoint, analyze every campaign in real-time, and personalize every interaction without watching the meter tick. This cost reduction reshapes the competitive landscape in several ways. It democratizes access to sophisticated marketing tools, allowing smaller businesses to access capabilities previously reserved for enterprises.
It encourages experimentation when every AI interaction costs pennies instead of pounds.
Reshaping AI in marketing
It enables continuous operation rather than campaign-based deployment.
However, challenges remain. The rush to adopt cheaper AI solutions must be balanced against reliability requirements. A marketing automation system that fails during a major campaign can cost far more than the savings from a cheaper AI model.
Geographic considerations and data sovereignty also require careful attention. Looking ahead, the marketing industry will likely split into two camps: those who see cheaper AI as a way to do the same things for less money and those who recognize it as an opportunity to reimagine their entire approach to customer engagement. The most successful organizations will be those using the cost reduction to deploy AI in ways previously considered impractical.
As AI becomes a commodity rather than a luxury, the competitive advantage will shift from access to implementation. Success will depend not on having the technology – which will be widely available – but on developing innovative ways to apply it. For the marketing and advertising industry, this cost reduction marks the beginning of a new era.
The question isn’t whether organizations will adopt cheaper AI solutions but how quickly they’ll recognize and adapt to the new possibilities they enable.
