Cem Dilmegani
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
- Cem Dilmegani, Post-AI Banking: Millions of jobs at risk as banks automate their core functions. International Banker.
- Cem Dilmegani, Bengi Korkmaz, and Martin Lundqvist (December 1, 2014).Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Media, conference & other event presentations
- Answers to Korea24's questions on job loss due to AI, Korea24
- Real Estate and Technology, presented by Hofstra University’s Wilbur F. Breslin Center for Real Estate Studies and the Frank G. Zarb School of Business in 2023 and 2024.
- Radar AI session (June 22, 2023): "Increasing Data Science Impact with ChatGPT".
- Generative AI Atlanta meetup: Generative AI for Enterprise Technology.
Sources
- Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
- Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
- Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
- Science, Research and Innovation Performance of the EU, European Commission.
- EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
- Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
- We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.
Latest Articles from Cem
Top 5 Google Colab Alternatives in 2026
Google Colaboratory is a popular platform for data scientists and machine learning scientists, but its limitations and pricing may not meet your needs. Several alternatives offer unique features and capabilities that cater to different data science needs and scenarios.
Top 7 Open Source Sentiment Analysis Tools in 2026
Text analytics is estimated to exceed a global market value of US$ 56 billion by 2029. Sentiment analysis has gained worldwide momentum as one of the text analytics applications. Businesses that have not implemented sentiment analysis may feel an urge to find out the best tools and use cases for benefiting from this technology.
8 Ways to Use ChatGPT for Test Automation in 2026
Maintaining high software quality depends heavily on effective test automation, and with AI and natural language processing tools like ChatGPT, automation approaches are rapidly evolving. We explore ChatGPT’s use cases, integration challenges, and potential benefits for test automation.
Top 7 Examples of ChatGPT Sentiment Analysis in 2026
A study estimated that 80% of companies will adapt to solutions that utilize sentiment analysis in 2023. Sentiment analysis is a Natural Language Processing (NLP) method that classifies texts, images, or videos based on the emotional tone as negative, positive, or neutral.
ChatGPT Code Interpreter Plugin: Use Cases & Limitations
Since the release of ChatGPT, programmers and more advanced users of the tool were curious whether OpenAI will allow plugins to the chatbot. OpenAI announced the first plugins in April, followed by many others since then. At the beginning of July 2023, they announced an official ChatGPT plugin, the Code Interpreter. Figure 1.
Top 10 Open Source RBAC Tools in 2026
Based on their categories, features, and market presence I listed the top 10 open source RBAC tools that can help organizations restrict system access by granting grant permissions and privileges to users.
Top 15 DLP Statistics in 2026
Data from network security statistics reveals that the cost of an average data breach in the last year reached a record-breaking $4 million. To safeguard their data, businesses are leveraging solutions such as data loss prevention (DLP) software.
Top 10 Mobile DLP Best Practices & Case Studies in 2026
As remote work and mobile device usage continue to increase, protecting sensitive data on mobile platforms has become a top priority for organizations. Mobile devices often present vulnerabilities for DLP software due to their portability, access to cloud systems, and various apps (Figure 1).
Top 10+ Emotional AI Examples & Use Cases in 2026
The emotion detection and recognition (EDR) market is estimated to reach at ~$50 Bn in 2024, and is expected to reach ~$173 Bn by 2031. Emotion detection and recognition rely on emotion AI to identify, process, and simulate human feelings and emotions.
Top 7 Real-life Network Segmentation Use Cases in 2026
Network security statistics show that the total amount of data breaches has more than doubled in the last three years rising to 1,300+ cases from ~600. Network segmentation tools can help organizations build a finer-grained network to prevent breaches. Here are the top 7 real-life network segmentation use cases and examples: 1.
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