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
Analysis of Top 4 Open Source NGFWs Based on Features
Data breaches led to the exposure of 6M records in the first quarter of 2023, according to network security stats. Teams using NGFWs, AI-driven security, and automation are saving ~$2M more than those use the traditional tools.
Best 10+ Commercial & Open Source AI Agents in Sales
AI SDRs support sales teams by automating key parts of the sales outreach process. These agents integrate with CRMs, email tools, and outreach platforms, and improve over time through feedback and performance data for sales operations.
Comparison of Top 5 Free Cloud GPU Services
AI and machine learning advancements have surged demand for GPUs, essential for high-performance computing. Dedicated GPU infrastructure requires high capital, but cloud-based services now offer cost-effective access. Free GPU platforms are increasingly vital for researchers, developers, and budget-conscious organizations.
Top 30+ Agentic AI Companies
Though AI agents are being hyped and some companies rebrand their chatbots as agentic tools, there are still few agents in production. Previously, we benchmarked some of these capable AI agents over several real-world tasks. In this article, we identified key agentic AI companies that live up to the hype.
Top 7 Next-Generation Firewall (NGFW) Features
Traditional firewalls, which perform simple port and protocol inspection, are less capable than next-generation firewalls (NGFWs) in preventing cyber incidents. NGFWs go beyond simple port and protocol inspection by: Learn what is a next-generation firewall (NGFW) and its top 7 features: 1.
Best Open Source RPA Tools
There are already some open-source RPAs, and we are showing the top 6 ones and their source codes. Note that the ecosystem is still relatively immature. However, with the commodification of RPA technology, more vendors are offering similar solutions.
Top 7+ Open Source Firewall Options: Features & Types
Network security statistics reveal that Open source firewalls provide a cost effective solution to network security.
23 Healthcare AI Use Cases with Examples
Healthcare systems are under growing pressure from rising patient data volumes and increasing demand for personalized care. Healthcare AI applications have emerged as a powerful solution to these problems by optimizing processes, enhancing diagnostic accuracy, and improving patient outcomes.
Compare 45+ MLOps Tools
Machine Learning Operations (MLOps) brings DevOps principles into machine learning to simplify workflows from model development to deployment and maintenance.
12+ Data Augmentation Techniques for Data-Efficient ML
Data augmentation techniques generate different versions of a real dataset artificially to increase its size. Computer vision and natural language processing (NLP) models use a data augmentation strategy to handle data scarcity and insufficient data diversity. Data-centric AI/ML development practices, such as data augmentation, can increase the accuracy of machine learning models.
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