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
Top 10+ SIEM Systems & How to Choose the Best Solution
SIEM systems have evolved to become more than log aggregation tools. Some vendors developed unified product suites with UEBA, SOAR, and EDR capabilities, claiming they are “next-gen” SIEMs. Others offer products focused on traditional event and log management.
Top 8 SIEM Use Cases and Real-life Examples
We previously explained open source & commercial SIEM tools, including how to select the best solution.
Top 13 Open Source SIEM Tools
Unlike commercial SIEMs such as ManageEngine Log360, open-source SIEM tools commonly lack core SIEM capabilities, including event correlation, log analytics, alerting, or require combining with other tools. However, several network defensive tools (e.g., intrusion detection and prevention systems and network monitoring tools) can be used as SIEM tools with fine-tuning.
7 Useful AI Transformation Strategies in 2026
AI transformation is the next phase of digital transformation. Businesses are willing to invest in AI technologies to stay ahead of competitors. Digital transformation is a prerequisite for companies to initiate their AI transformation, as digital data is essential for AI training, and digital processes are typically required to deploy AI solutions.
Top 7 Open Source RMM Software: Pros, Cons & Benefits in 2026
IT teams and managed service providers (MSPs) need remote monitoring and management (RMM) tools to maintain infrastructure health, patch endpoints, respond to alerts, and manage devices at scale.
Top 8 Network Observability Tools
Network observability gives organizations visibility into network performance, enabling faster identification and resolution of infrastructure issues. Tools in this category increasingly use AI to automate anomaly detection across traffic and device health. Top 8 network observability tools * Reviews are based on Capterra and G2.
Best AI Code Editor: Cursor vs Windsurf vs Replit
Making an app without coding skills is highly trending right now. But can these tools successfully build and deploy an app? We benchmarked 6 AI code editors across 10 real-world web development challenges. Each task required implementations such as backend, frontend, authentication, state management.
Vision Language Models Compared to Image Recognition
Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).
Top 5 Octoparse Alternatives & Competitors
As a non-technical user, I kick-started AIMultiple’s data collection efforts with Octoparse. However, our requirements expanded over time, and we moved to more scalable services, listed below: Octoparse alternatives pricing comparison Octoparse is a no-code web scraping tool with a visual, point-and-click interface that simplifies the web scraping process.
10 eCommerce Data Collection Best Practices & Examples
As online shopping grows and customer expectations shift, eCommerce businesses face increasing pressure to stay competitive. Real-world data is key to making faster, smarter decisions. Failing to collect and utilize data properly can result in missed sales, inefficient operations, and poor customer retention.
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