Even as the Chinese LLM sensation DeepSeek’s R1 kicks off a debate on whether India should tap into this cheaper version, research firm Gartner Inc., has asked organisations to be cautious about key challenges such as Shadow AI, potential biases and legal implications, which can cause severe harm if proper guardrails are not put in place.
The hype surrounding DeepSeek could lead to unmanaged adoption of DeepSeek applications (mobile and chat) by employees as they simplify the development of such apps. This creates risks on inputs (example: data leakage) and outputs (example: inaccuracies).
“Leaders should assess its implications, including enhanced AI scaling, security risks, and strategic opportunities. The model reduces inference costs while maintaining competitive performance, pushing AI commoditisation forward,” the research firm said.
While DeepSeek R1 fosters AI accessibility, companies should critically evaluate its adoption, potential biases, and legal implications. The launch signals a shift toward efficiency-driven AI innovation rather than sheer computational scaling.
Implications
“The implications of R1’s launch are profound. It underscores the inefficiencies in current leading vendor pricing models, which often result in a negative return on investment (RoI) for high-value use cases when deployed at scale,” it pointed out.
“These models can stifle innovation in GenAI applications, even when vendors subsidise pricing to capture early market share. R1’s cost-effectiveness and accessibility — being free for developers to download and integrate—demonstrate that substantial performance can be achieved without exorbitant investments,” it observed.
Key challenges
The appeal of a high-performing and low-cost model will be strong for developers and product leaders who can easily use DeepSeek’s APIs and model marketplaces or download DeepSeek models to conduct experiments.
“This could lead to a variety of risks depending on the model deployment (local or remote), and consequences on data storage, logging, and the possibility for the provider to use the data for training,” it pointed out.
Privacy and data security
DeepSeek chat privacy policy indicates that processing and logging occur in China and that the company might use data for training. The same might apply when using DeepSeek through its API.
There has been a downward trend for pricing over the last 6 to 12 months. DeepSeek shook the pricing ground here, but that doesn’t mean that organisations should all of a sudden change course because of this.
“Avoid building private generative AI models unless a compelling business case exists that will significantly transform your business model. Ensure the investment aligns with strategic objectives and offers a substantial competitive advantage,” it suggested.
