In a world dominated by tech giants like OpenAI, Google, and Meta, a new contender has emerged, shaking up the global AI industry—DeepSeek. This Chinese AI company has made waves with its open-source large language models (LLMs), which are designed to compete with some of the most established names in artificial intelligence. 

The company’s meteoric rise has prompted CxOs to rethink their approach to generative AI, particularly when it comes to cost-efficiency, accessibility, and the potential for on-premises AI solutions. To help leaders navigate this rapidly evolving landscape, here are seven key qualities of DeepSeek that every executive should be aware of.

1. Cost-Effective Innovation

One of DeepSeek’s most striking features is its ability to develop high-performing models at a fraction of the cost of its competitors. Unlike the hefty $100 million price tag associated with training models like OpenAI’s GPT-4, DeepSeek has demonstrated that it’s possible to train advanced AI models with much lower investment. Using Nvidia H800 chips, the company has managed to develop competitive models for under $6 million—a feat that has disrupted traditional models of AI development. This cost-saving approach has caught the attention of CxOs, especially as the cost curve for generative AI continues to come down.

For leaders, the message is clear: you don’t need to spend exorbitant amounts on AI infrastructure to stay competitive. With the advent of models like DeepSeek’s, executives are being forced to reconsider their AI budgets and explore more cost-efficient solutions.

2. Open-Source Accessibility

DeepSeek’s commitment to open-source development is another key quality that sets it apart. Constellation Research CEO Ray Wang has highlighted how DeepSeek has “democratized access to AI.” By making its models open-source, the company has lowered the barriers to entry for smaller organizations and developers who may not have the resources to access proprietary models from the likes of OpenAI and Google.

This shift is a game-changer for businesses that want to implement generative AI without incurring the high costs of proprietary solutions. Leaders should take note of the growing trend of open-source AI and consider how this could benefit their own organizations, whether through cost savings or fostering innovation within their teams.

3. Flexibility and Lower Hardware Requirements

Another standout feature of DeepSeek is the model’s ability to operate in private environments without requiring top-of-the-line hardware. Unlike other models that demand the latest and most expensive GPUs, DeepSeek’s model runs efficiently on more affordable infrastructure. This flexibility is a major advantage for businesses that want to experiment with AI in-house but don’t have access to cutting-edge hardware or cloud-based resources.

This development represents an opportunity to experiment with generative AI solutions in a more accessible and cost-effective manner. If your organization is considering adopting AI for internal use, DeepSeek could provide a viable option that doesn’t require heavy investments in hardware or cloud computing.

4. Potential for On-Premises AI

The question of whether AI will remain primarily a cloud-based service or shift towards on-premises solutions is a topic of much debate. While many experts believe that cloud computing will continue to dominate, there is growing interest in on-premises AI, especially in light of DeepSeek’s innovations. Holger Mueller from Constellation Research noted that AI workloads will still primarily reside in the cloud but pointed out that DeepSeek’s model is opening up possibilities for on-premises AI, particularly for organizations that want to maintain tighter control over their data and infrastructure.

CxOs should consider the potential benefits of on-premises AI, particularly when it comes to sensitive use cases where data privacy and security are top priorities. As AI costs continue to decrease, on-premises solutions may become more feasible for companies that wish to have more direct control over their AI deployments.

5. Human Intervention and Creativity

DeepSeek has taken a unique approach to AI model development by incorporating human intervention into its training process. Constellation Research’s Andy Thurai pointed out that the company’s success is due in part to its ability to be creative with limited resources. The lack of access to abundant GPUs in China has pushed DeepSeek’s team to think outside the box, focusing on distillation techniques and other methods that allow them to build competitive models on a budget.

This human-centered approach to AI development is something that business leaders should take note of. It underscores the importance of creativity and innovation in overcoming resource constraints and building effective solutions. For organizations looking to implement AI, this approach serves as a reminder that technical excellence is not the only path to success—human ingenuity can be just as powerful.

6. Security Considerations

With any AI model, especially one that operates in open-source environments, security is a major concern. DeepSeek’s accessibility and flexibility come with inherent risks, including the potential for prompt injection and jailbreaking, as noted by Constellation Research analyst Chirag Mehta. For leaders, this raises important questions about the security of sensitive data and the potential vulnerabilities that may arise from using a model that has not been fully vetted for security risks.

As CxOs explore the potential of DeepSeek’s models, it’s crucial to remain vigilant about security. Mehta advises businesses to carefully consider whether they are comfortable using a model like DeepSeek for high-stakes use cases, particularly those involving sensitive information. While the model offers a high level of accessibility, businesses must balance this with robust security protocols to protect their data and systems.

7. Impact on the Tech Landscape

The rise of DeepSeek has had significant ripple effects throughout the AI and tech sectors, particularly in how Wall Street and other investors view the future of AI hardware. The success of DeepSeek’s low-cost models has led to concerns about the profitability of companies like Nvidia, which traditionally dominates the AI hardware space. The shift towards more affordable, efficient models could challenge Nvidia’s market position and force the company to adapt its strategy.

For leaders in tech, this disruption presents both opportunities and challenges. As AI models become more cost-effective, businesses will have more options for integrating AI into their operations. However, executives must also remain aware of the broader market dynamics and how these changes could affect their relationships with hardware vendors, cloud providers, and other key stakeholders in the AI ecosystem.

What CxOs Need to Do

So, what should CxOs do in response to the rise of DeepSeek? Constellation Research’s Chirag Mehta offers some practical advice: “If you’re a CxO, the best analogy is what open source did to the industry. That’s what this model is now doing to its competitors.” CxOs should keep their options open and stay focused on solving the specific problems they face with generative AI.

At the same time, leaders need to consider the long-term implications of the cost curve for AI. As models like DeepSeek continue to drive down costs, businesses will need to assess whether they want to invest in high-end, proprietary AI platforms or take advantage of more affordable, open-source solutions.