Cem Dilmegani
Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, and Washington Post, global firms like Deloitte and 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 enterprise AI and software.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
- Hosted on American Variety Radio, answering Court Lewis' questions on AGI on April 25th, 2026.
- Answered Korea24's questions on job loss due to AI on November 5th, 2025. Recording available on: 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
Compare 10 Python Job Scheduling Methods
Python job scheduling automates tasks at specific intervals to enforce strict execution timelines, catch runtime exceptions, and ensure system state consistency without manual intervention. Here are the various job scheduling methods in Python along with their advantages and disadvantages: Cron is a built-in Unix/Linux scheduler that executes scripts at specific times. It is useful for…
Best 7 AI Test Agents for QA
We evaluated AI testing platforms embedded with AI agents; most were overhyped Selenium/Playwright with marketing. A few were capable of writing/maintaining test cases or visual testing, though even these tools still have notable limitations. From these, we selected 7 platforms and categorized them by their primary focus areas. Our evaluation is based on real-world application…
10+ AI Procurement Use Cases & Case Studies
As the benefits of artificial intelligence (AI) are appreciated by a greater audience, the number of AI use cases in different industries expands daily. AI in the procurement sector is no different. See a comprehensive overview of the AI procurement process, detailing the reasons for its adoption, various use cases, the top 5 AI procurement…
eCommerce Technologies Use Cases & Examples
Increasing competition in the eCommerce sector requires businesses to understand how technology is changing customer expectations. Organizations must remain informed about emerging tools and market developments to respond effectively and sustain service quality. Discover the top 15 eCommerce technologies in personalization and customer engagement, operations and efficiency, and payment systems: Chatbots and intelligent virtual assistants…
Automated Data Collection Tools & Use Cases
Automated data collection uses systems to gather, process, and analyze information efficiently. Since automated data comes from multiple sources in various formats, understanding the different types and their origins is essential to implementing it effectively. Data collection automation uses scripts, bots, APIs, or dedicated platforms to gather, organize, and store data from multiple sources without…
Top 9 Network Traffic Analysis Software
We evaluated 20 network traffic analysis solutions across production environments, testing the performance of NetFlow, sFlow, and IPFIX protocols, as well as real-time monitoring accuracy and threat detection capabilities under enterprise-scale loads. Explore specific vendor comparisons, flow protocol optimization recommendations, and pricing insights based on actual deployment costs. * Vendors are sorted in ascending order…
Top 10 Open Source Web Crawlers for LLM & AI
Recent advances in generative AI have reshaped what developers need from web crawlers. Agentic crawlers now use natural-language prompts to select links rather than fixed rules, and produce token-efficient markdown natively. At the same time, the classic frameworks for large-scale batch crawling remain irreplaceable for enterprise and research use. Language: Python | License: Apache 2.0…
LLM Inference Engines: vLLM vs LMDeploy vs SGLang
We benchmarked 3 leading LLM inference engines on NVIDIA H100: vLLM, LMDeploy, and SGLang. Each engine processed identical workloads: 1,000 ShareGPT prompts using Llama 3.1 8B-Instruct to isolate the true performance impact of their architectural choices and optimization strategies. We measured offline batch throughput across 10,000 total inference operations (1,000 prompts × 10 runs per…
Top 15 Open Source AI Platforms & Libraries
Deploying your own AI model or, in some cases, fine-tuning pre-existing models comes with several challenges: Open-source platforms that offer unified APIs help address these challenges by enabling multi-cloud deployment and optimizing GPU resource management. Below, we list 15 examples of open source platforms/libraries: When choosing these platforms, we focused mainly on how well they…
GPU Software for AI: CUDA vs. ROCm
Raw hardware specifications tell half the story in GPU computing. To measure real-world AI performance, we ran 52 distinct tests comparing AMD’s MI300X with NVIDIA’s H100, H200, and B200 across multi-GPU and high-concurrency scenarios. While AMD’s MI300X boasts 1,307 TFLOPS compared to NVIDIA’s H100/H200 at 990 TFLOPS, a 32% theoretical advantage, real-world performance is a…
AIMultiple Newsletter
1 free email per week with the latest B2B tech news & expert insights to accelerate your enterprise.