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
15+ Best Open Source Web Crawlers for LLM & AI
Recent advancements in Generative AI are moving modern crawlers beyond raw HTML. Agentic web crawlers now use natural-language prompts to select links, rather than relying on fixed rules. These tools produce token-efficient markdown, making them essential for high-performance RAG pipelines.
Top 10 Network Monitoring Software
We tested network monitoring tools to find which ones actually deliver on their promises. Here’s what we found after benchmarking performance, ease of setup, and real-world usability. See the top network monitoring tools, assessment of their user experience, and their key features: * Vendors are ordered alphabetically.
Crowdsourced Data Collection: Benefits & Best Practices
Data collection is a crucial stage in developing AI/ML models, as it directly influences their real-world performance. Whether you work with a data collection service or gather data yourself, it’s vital to execute this process correctly. Here, we explore crowdsourcing as an effective data-gathering method, helping businesses select the best approach for their AI/ML projects.
Top 10 Backup Management Software: Key Features & Benefits
With cybercrime costs reaching $10.5 trillion globally in 2025 and the backup software market projected to reach $18.2 billion by 2032 (growing at 8.9% CAGR), choosing the right backup solution can protect you from data loss that could cripple your business operations.
Top 5 Endpoint Management Software with Prices
The most common case of cybercrime is unauthorized access to unmanaged devices. As hybrid work models and bring-your-own-device (BYOD) policies become standard practice, endpoint management software has evolved from a convenience into a necessity.
OpenClaw (Moltbot/Clawdbot) Use Cases and Security 2026
OpenClaw (formerly Moltbot and Clawdbot) is an open-source, self-hosted AI assistant designed to execute local computing tasks and interface with users through standard messaging platforms. Unlike traditional chatbots that function as advisors generating text, OpenClaw operates as an autonomous agent that can execute shell commands, manage files, and automate browser operations on the host machine.
Top 10 Mortgage Chatbots in 2026: Use Cases & Examples
Banks that keep customers happy grow deposits 85% faster than competitors. Loan processing directly affects client satisfaction. . Chatbots can handle mortgage-related tasks around the clock, simulating what mortgage brokers typically do. We examine 10 vendors, their practical applications, and United Wholesale Mortgage’s implementation.
Top Vector Database for RAG: Qdrant vs Weaviate vs Pinecone
Vector databases power the retrieval layer in RAG workflows by storing document and query embeddings as high‑dimensional vectors. They enable fast similarity searches based on vector distances.
Remote Browsers: Web Infra for AI Agents Compared
AI agents rely on remote browsers to automate web tasks without being blocked by anti-scraping measures. The performance of this browser infrastructure is critical to an agent’s success. We benchmarked 8 providers on success rate, speed, and features.
RAG Frameworks: LangChain vs LangGraph vs LlamaIndex
We benchmarked 5 RAG frameworks: LangChain, LangGraph, LlamaIndex, Haystack, and DSPy, by building the same agentic RAG workflow with standardized components: identical models (GPT-4.1-mini), embeddings (BGE-small), retriever (Qdrant), and tools (Tavily web search). This isolates each framework’s true overhead and token efficiency.
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