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Cem Dilmegani

Cem Dilmegani

Principal Analyst
687 Articles
Stay up-to-date on B2B Tech
Cem has been the principal analyst at AIMultiple for almost a decade.

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

Media, conference & other event presentations

Sources

  1. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
  2. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
  3. Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
  4. Science, Research and Innovation Performance of the EU, European Commission.
  5. EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
  6. Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
  7. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

Latest Articles from Cem

CybersecurityJul 25

Why Cybersecurity in Sports Is More Important Than Ever

At least 70% of sports organizations have experienced cyber incidents or breaches. With cybercriminals targeting: We explore the unique cybersecurity risks facing the sports industry and examine the strategies sports organizations can employ to protect themselves and their stakeholders from cyber threats.

CybersecurityJul 25

Top 14 Intrusion Detection and Prevention Tools in 2026

At its core, intrusion detection and prevention systems (IDPS) monitor networks for threats, alert administrators, and prevent potential attacks. We previously explained real-life use cases of AI IPS solutions.

DataJul 25

Unblocker& Proxy Benchmark: 7 Vendors vs ~5k URLs ['26]

AIMultiple web data collection benchmark analyzes leading web unblocker and proxy service providers including residential proxy networks.

AIJul 25

7 Steps to Obtain Computer Vision Training Data in 2026

Computer vision (CV) technology is advancing rapidly in various industries. As demand for computer vision systems rises, so does the need for well-trained models. These models require large, high-quality, accurately labeled datasets, which can be costly and time-consuming to collect.

DataJul 25

Automated Data Collection Tools & Use Cases in 2026

Automated data collection involves using automated systems to gather, process, and analyze information efficiently. Since automated data is produced from multiple sources and comes in various formats, understanding the different types of data and their origins is crucial for effectively implementing data automation.

DataJul 25

Top 6 Octoparse Alternatives & Competitors in 2026

Octoparse is an easy-to-use platform to get started with web scraping. As a non-technical user, I kick-started AIMultiple’s data collection efforts with Octoparse.

DataJul 25

Scraping Financial Data Without Coding in 2026

While official financial data providers do offer APIs, these are often limited in scope, access, or flexibility especially for real-time or niche data needs. As a result, financial data scraping has become a common approach to collecting such information, typically using technologies like web scrapers, headless browsers, and HTML parsers.

Enterprise SoftwareJul 25

Informatica Scheduling: Features, Limitations & Use Cases

Informatica Scheduling is a workload automation/job scheduling feature within the data management platform Informatica PowerCenter. To help you leverage its capabilities, we explore Informatica Scheduling in detail below, focusing on its key functionalities, comparative advantages, limitations, and practical applications in workload automation.

DataJul 25

Product Market Research: 8 Essential Steps & Real-Life Examples

~90% of companies state that they listen to the voice of their customers while developing new products. One of the efficient ways to hear from customers is to conduct market research. Product market research stands as a beacon, guiding businesses in creating products that resonate with their target customers.

DataJul 25

Top 5 MTurk Survey Participant Recruitment Alternatives

Recruiting participants for consumer or market research can be challenging. Crowdsourcing platforms like Amazon MTurk make it easier to find survey respondents and get quick results. However, potential drawbacks, such as response reliability and data quality, can impact the results.