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
Large Language Model Training in 2026
While using existing LLMs in enterprise workflows is table stakes, leading enterprises are building their custom models. However, building custom models can cost millions and require investing in an internal AI team.
LLM Fine-Tuning Guide for Enterprises in 2026
Follow the links for the specific solutions to your LLM output challenges. If your LLM: The widespread adoption of large language models (LLMs) has improved our ability to process human language. However, their generic training often results in suboptimal performance for specific tasks.
Compare 45+ MLOps Tools in 2026
Machine Learning Operations (MLOps) brings DevOps principles into machine learning to simplify workflows from model development to deployment and maintenance.
Redwood-SAP Partnership: Clean Core Support for SAP Clients
With over 30 years of experience in automation, Redwood has worked alongside SAP to support a wide range of enterprise automation initiatives. This partnership has supported numerous enterprise automation projects. See the services that SAP users can access through Redwood, the history of this partnership, and the dynamics of their collaboration.
Wu Dao 3.0 in 2026: China's Version of GPT-5
When the US cut off China’s access to advanced chips, the Beijing Academy of Artificial Intelligence faced a choice: complain about restrictions or work around them. They picked the second option. Wu Dao 3.0, launched in July 2023, throws out the playbook. No massive trillion-parameter models competing for headlines.
Help Desk Case Studies in 2026
Help desk software tracks customer questions and feedback to improve customer service. Explore the real-life case studies illustrating how help desk software has been beneficial to businesses: Help desk case studies Eurail Eurail is a rail pass provider that allows travelers to use trains across 33 European countries.
Demilitarized Zone (DMZ): Examples & Architecture
A Demilitarized Zone (DMZ) network is a subnetwork containing an organization’s publicly accessible services. It serves as an exposed point to an untrusted network, often the Internet. DMZs are used across various environments, from home routers to enterprise networks, to isolate public-facing services and protect internal systems.
Roadmap to Web Scraping: Benchmark Results from 30M Requests
We crawled more than 30 million web pages using more than 50 products from 6 leading web data infrastructure companies. This massive undertaking enabled us to assess critical performance metrics, including success rates, latency, and stability at scale. Our goal was to determine which solutions truly handle the complexities of enterprise-level scraping.
No-Code AI: Benefits, Industries & Key Differences in 2026
No-code AI tools allow users to build, train, or deploy AI applications without writing code. These platforms typically rely on drag-and-drop interfaces, natural language prompts, guided setup wizards, or visual workflow builders. This approach lowers the barrier to entry and makes AI development accessible to users without a programming background.
10+ Epic LLM/ Conversational AI/ Chatbot Failures
Building chatbots that understand natural language remains difficult. Many fail at basic tasks or produce responses that users mock online. AI keeps advancing, and chatbots might eventually match human conversation skills. Until then, their mistakes offer valuable lessons.
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