As you know, artificial intelligence is changing our lives, and this forces companies to transform themselves to adapt to this new way of life. The transformation created by Chat GPT and DeepSeek makes it necessary for companies to establish AI infrastructure for themselves. This means that, in today's economic environment, companies will start seeking help from AI to take the right steps to grow.
So, how will they do this? You will need to introduce your business to AI models like Chat GPT, DeepSeek, Google Gemini, and others. Currently, there is fierce competition among AI models, and we hear about their impact in the media, which makes us debate which one to use. Although the competition in AI algorithms will continue, it is clear that, at first, they can all provide similarly complex outputs.
Feature | DeepSeek | ChatGPT | Gemini |
Model Type | Mixture-of-Experts (MoE) | Transformer-based | Transformer-based |
Parameters | 671 billion | 1.8 trillion | 1.6 trillion |
Multimodal Support | Text only | Text and images | Text, images, and voice |
Efficiency | High | Medium | Medium |
Customization | High | Limited | High |
Use Cases | Technical queries, coding, research | Content creation, general conversation, coding | Creative writing, multimodal tasks, data analysis |
Math Performance | 90% accuracy | 83% accuracy | 85% accuracy |
Coding Success | 97% | 89% | 91% |
Reasoning | Logical step-by-step explanations | Multistep reasoning | General reasoning with real-world examples |
Context Window | 128K tokens | 200K tokens | 1M tokens |
Therefore, the key here is to provide the correct data output and utilize AI effectively with the right questions. In other words, the most important factor in AI usage for companies will be sharing the right data in detail to train AI. With this data, AI will better understand your industry and company, and inform you about the right opportunities in your market.
The critical difference in AI’s ability to derive correct results from data lies in how it optimizes its model, the richness of your data, the scope, and how you define your business scenarios.
Specifically:
Learning ApproachThe customized data sets you use when training your AI model will determine the quality of your optimization outputs. If you share the same data pool as your competitor, the way you train your model, the metrics you prioritize, and the value propositions you present to the end-user will make the difference.
Data Quality and DiversityIt’s not about having more data but about having meaningful and clean data. Providing specialized data variables specific to customer behaviors, market conditions, and competitive intelligence will create a more successful AI model.
Real-Time Learning and Feedback MechanismsSystems that can interpret feedback from users and transform it into new data variables, updating their database and model accordingly, will outpace their competitors.
Scalability and Infrastructure: The speed, cost-effectiveness, and ability to scale seamlessly will be important considerations when choosing the infrastructure and tools you will use. Transitioning to scalable data and data enrichment architectures will become crucial for you. Even if your competitor’s AI is excellent, if it's built on a slow or expensive system, it will fall behind in the market.
Internal / External AI: Among these variables, perhaps the most important will be your data diversity. While most companies focus on developing their own CRM data, AI will push you to connect to external data sources at maximum scale. To produce the correct results, your model needs to connect to the outside world, which will require external data sources. You will need to benefit from external data sources like social media, mobility, and others.
The year 2025 will be a year where companies will understand the importance of enriching internal data with external sources, interpreting these data through their own industry and market insights, and developing a custom AI model with the right variables.
A New Era for CEOs in CompaniesAs mentioned in the Harvard Business Review article, a well-trained AI model will become your company’s new CEO.Harvard Business Review - AI can mostly outperform human CEOs
What can AI do?
Real-Time Competitive Analysis – Predict a competitor's strategic moves in advance.
Dynamic Pricing and Promotions – Predict a competitor’s inventory, sales performance, and adjust product/price balance in the market automatically.
Macroeconomic Forecasts – Enable real-time visibility and accurate predictions of economic fluctuations, consumer mobility, and regional trends.
Efficiency and Operational Functions – Identify gaps and errors in operations, determine investment strategies for efficiency.
Customer Communication – Analyze interactions across digital channels, call centers, etc., to manage communication and audience engagement, as well as generate creative visual works.
Budgeting and Investments – Ensure your budget is used efficiently.
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