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Cem Dilmegani

Cem Dilmegani

Principal Analyst
346 Articles
Stay up-to-date on B2B Tech
Cem has been the principal analyst at AIMultiple for almost a decade.

Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, Washington Post, global firms like HPE, NGOs like World Economic Forum and supranational organizations like European Commission. [1], [2], [3], [4], [5]

Professional experience & achievements

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. [6], [7]

Research interests

Cem's work focuses on how enterprise AI and software.

Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and the tech team support Cem in designing, running and evaluating benchmarks.

Education

He graduated as a computer engineer from Bogazici University in 2007. During his engineering degree, he studied machine learning at a time when it was commonly called "data mining" and most neural networks had a few hidden layers.

He holds an MBA degree from Columbia Business School in 2012.

Cem is fluent in English and Turkish. He is at an advanced level in German and beginner level in French.

External publications

Media, conference & other event presentations

Sources

  1. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
  2. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
  3. Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
  4. Science, Research and Innovation Performance of the EU, European Commission.
  5. EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
  6. Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
  7. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

Latest Articles from Cem

AIApr 24

Top Image Recognition Tools Compared in 2026

We evaluated the real-world performance of top cloud image recognition tools for object detection tasks by benchmarking their default API configurations across 5 classes using 100 images. This included contrasting performances, analyzing features, and comparing service offerings in relation to pricing. Benchmark Results Performance overview at IoU=0.

CybersecurityApr 24

AI IPS: 6 Real-life Use Cases & Leading Tools

AI intrusion prevention systems (IPS) use machine learning algorithms and behavioral analytics to detect and prevent several cyber threats. AI can strengthen traditional IPS capabilities by enabling faster, more adaptable, and more cost-effective detection, especially for organizations with limited resources.

DataApr 24

Top +10 Data as a Service Companies

Data fuels generative AI and enterprise innovation. Data as a Service (DaaS) is a cloud computing model that provides data on demand to users, usually on a subscription basis. This streamlines data collection and management.

Enterprise SoftwareApr 24

Compare Top 7 Meter-to-Cash Solutions

Utilities must accurately track energy consumption, generate bills, and collect payments across millions of customers. However, fragmented systems, legacy infrastructure, and complex billing processes can make the meter-to-cash (M2C) cycle inefficient and error-prone.

DataApr 24

AI Data Quality in 2026: Challenges & Best Practices

Poor data quality delays the successful deployment of AI and ML projects. Even the most advanced AI algorithms can yield flawed results if the underlying data is of low quality.

AIApr 24

ChatGPT for Customer Service: Top 10 Use Cases

ChatGPT has moved from novelty to infrastructure in customer service. Companies are using it to cut response times, handle volume their teams can’t absorb, and reduce the cost of routine interactions. But results vary sharply depending on how it’s implemented. OpenAI launched GPT-5.

DataApr 24

Top 7 Online Survey Participant Recruitment Tools

Companies conduct online surveys to understand market trends and their target audience. Survey participant recruitment tools help businesses to find appropriate participants.

DataApr 24

Top 13 Training Data Platforms

Data is an essential part of the quality of machine learning models. Supervised AI/ML models require high-quality data to make accurate predictions. Training data platforms streamline data preparation from collection to annotation, ensuring high-quality inputs for AI systems.

AIApr 24

Top 30+ NLP Use Cases in 2026 with Real-life Examples

The NLP market reached $34.83 billion in 2026, with projections to hit $93.76 billion by 2032. Healthcare is adopting AI at twice the rate of the broader economy, while the voice recognition market has grown to $22.49 billion in 2026, projected to reach $61.71 billion by 2031. We analyzed 250+ deployments across industries.

AIApr 22

Top 125 Generative AI Applications

Based on our analysis of 30+ case studies and 10 benchmarks, where we tested and compared over 40 products, we identified 125 generative AI use cases across the following categories: For other applications of AI for requests where there is a single correct answer (e.g., prediction or classification), check out AI applications.

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