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Cem Dilmegani

Cem Dilmegani

Principal Analyst
687 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 enterprises can leverage new technologies in AI, agentic AI, cybersecurity (including network security, application security) and data including web data.

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

AIJul 16

Top 10 Applications of Deep Learning in Manufacturing ['26]

Deep learning, a subset of artificial intelligence and machine learning, uses predictive analytics to extract insights, improve productivity, reduce defects and maintenance costs, and accounts for approximately 40% of the annual value generated by all analytics approaches.

Enterprise SoftwareJul 14

Top 20 Blockchain in Supply Chain Case Studies in 2026

Blockchain technology is gaining popularity as a solution to long-standing problems in supply chain management. By offering a decentralized and tamper-proof method for recording transactions, blockchain can address issues related to traceability, transparency, and trust among supply chain partners.

AIJul 11

AI in Sales: 25 Use Cases & Real-life Examples in 2026

Artificial intelligence can transform and enhance sales processes from lead generation to sales forecasting, helping businesses overcome low conversion rates and long sales cycles.

AIJul 10

Top 5 Computer Vision Security Applications & Examples

As global crime rates rise, the demand for scalable and efficient security solutions is growing. The market is projected to reach $39 billion by 2029, growing at a CAGR of approximately 10% from 2025 to 2029. Conventional manual surveillance is limited by human capacity; personnel can only monitor footage for short periods with inconsistent accuracy.

AIJul 10

Google's AI Strategy and 11 Key Developments in 2026

Google’s current artificial intelligence strategy emphasizes advanced integration of AI models into enterprise solutions, with significant investments focused on improving functionality, accuracy, and efficiency. Check out 10 recent developments for businesses considering implementing Google’s AI tools and platforms into their workflows. 1. Gemini 2.5: Google’s advanced multimodal AI Google DeepMind launched Gemini 2.

Agentic AIJul 10

AI Agent Performance: Success Rates & ROI in 2026

The AI agent market reached $5.4 billion in 2024 and is projected to grow at 45.8% annually through 2030. Therefore, companies that master AI agent deployment will see significantly greater investment returns.

DataJul 9

Data Federation vs. Data Virtualization in 2026

In this article, we compare data federation and data virtualization. We provide insights when data federation should be chosen over data virtualization and vice versa.

DataJul 9

Top 4 Facial Recognition Data Collection Methods in 2026

Despite the controversies surrounding this technology, the facial recognition systems (FRS) market continues to grow. Facial recognition applications are everywhere, from helping improve mental disorder diagnoses to finding fugitives. Developing and improving these systems requires facial data, which sometimes can be challenging to obtain due to security and privacy-related concerns of people.

DataJul 9

Video Data Collection: Challenges & Best Practices in 2026

Video data is crucial for training computer vision (CV) systems, particularly with the increasing demand for autonomous vehicles and CV-enabled technologies. Here, we explore what video data collection entails, the challenges involved, and best practices to consider.

AIJul 9

Bot As A Service (Baas): Definition & Platforms in 2026

Technology as a service delivers tech benefits to businesses without on-premise tools or long-term investments. BaaS providers let businesses use chatbots or RPA bots on a pay-as-you-go basis, avoiding licensing and extensive training. Bot-as-a-Service (BaaS) has been gaining popularity, and businesses that adapt will have increasing advantages over those that don’t.