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
The LLM Evaluation Landscape with Frameworks in 2026
Evaluating LLMs requires tools that assess multi-turn reasoning, production performance, and tool usage. We spent 2 days reviewing popular LLM evaluation frameworks that provide structured metrics, logs, and traces to identify how and when a model deviates from expected behavior.
6 Real-life RBAC Examples in 2026
Nearly two-thirds of companies have 1,000 or more high-value files accessible to each employee. Role-based access control (RBAC) systems help organizations: Here are 6 real examples of RBAC implementations their challenges, solutions, and results. Real-life RBAC Examples 1. Dresdner Bank Major European bank with 368 different job functions and 1,300 roles.
8 AI Code Models Benchmarked: LMC-Eval in 2026
More than 37% of tasks performed on AI models are about computer programming and maths.
Top 6 SaaS Backup Solutions in 2026
Many businesses operate under the misconception that their SaaS providers (like Microsoft 365 or Google Workspace) fully protect their data from all threats. While these platforms offer robust infrastructure and some level of data redundancy, they do not protect against accidental deletion, ransomware, or insider threats.
Top 8 PAM Solutions with Free Alternatives in 2026
We spent three days testing and reviewing popular Privileged Access Management (PAM) solutions. We used the free trials and admin consoles of BeyondTrust, Keeper PAM, and ManageEngine PAM360. For solutions that required registration, we relied on official product documentation and user experiences to assess their capabilities.
OCR Benchmark: Text Extraction / Capture Accuracy
OCR accuracy is critical for many document processing tasks, and SOTA multi-modal LLMs are now offering an alternative to OCR.
AI Hallucination: Compare top LLMs like GPT-5.2
AI models can generate answers that seem plausible but are incorrect or misleading, known as AI hallucinations. 77% of businesses concerned about AI hallucinations.
Multimodal Embedding Models: Apple vs Meta vs OpenAI
Multimodal embedding models excel at identifying objects but struggle with relationships. Current models struggle to distinguish “phone on a map” from “map on a phone.” We benchmarked 7 leading models across MS-COCO and Winoground to measure this specific limitation. To ensure a fair comparison, we evaluated every model under identical conditions using NVIDIA A40 hardware and bfloat16 precision.
Compare Remote Control Software: NinjaOne & Acronis
We tested the top 3 remote control software (also known as remote access software) to evaluate the general UI and remote control experience, their remote control quality, protocols, and unique capabilities: Strengths and weaknesses based on our observations An agent needs to be installed for each tool we tested in this benchmark.
Computer Use Agents: Benchmark & Architecture in 2026
Computer-use agents promise to operate real desktops and web apps, but their designs, limits, and trade-offs are often unclear. We examine leading systems by breaking down how they work, how they learn, and how their architectures differ.
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