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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

CybersecurityNov 24

Best 8 CSPM Pricing and Plans in 2026

CSPM pricing isn’t straightforward. What you pay depends on what you’re monitoring, how many people need access, and which features you actually use. The starting price represents monthly payments for annual plans. Data is obtained from vendor websites, AWS Marketplace, and vendr.

CybersecurityNov 24

Top 10 Microsegmentation Tools in 2026

Microsegmentation divides networks into controlled segments, limiting the spread of breaches. When TeamViewer got hacked, its segmented network stopped the attackers from reaching customer systems.Based on the key features and market presence, see the top 10 microsegmentation software solutions: Features All providers offer common features and therefore can support typical microsegmentation use cases.

AINov 24

ChatGPT for Customer Service: Top 10 Use Cases in 2026

ChatGPT has become one of the most talked-about AI tools in business. While it’s primarily known for text generation, companies are finding practical ways to use it in customer service – with varying degrees of success. Here’s what actually works, what doesn’t, and how businesses are implementing ChatGPT to handle customer support.

AINov 24

Large Language Models: Complete Guide in 2026

Large language models are now central to artificial intelligence because they can understand natural language and generate text with high accuracy. They use transformer architecture and deep learning to process large amounts of training data and learn patterns in human language. Their usefulness spans many tasks, from answering questions to analysing documents.

DataNov 24

Remote Browsers: Web Infra for AI Agents Compared ['26]

AI agents rely on remote browsers to automate web tasks without being blocked by anti-scraping measures. The performance of this browser infrastructure is critical to an agent’s success. We benchmarked 8 providers on success rate, speed, and features.

Enterprise SoftwareNov 21

Best 9 Network Monitoring Tools in Windows in 2026

We tested and reviewed several network monitoring tools built for Windows environments to understand how they perform in real-world setups. Our goal was to find solutions that balance reliability, usability, and deep integration with Microsoft systems. We based our evaluation on three primary criteria: * Reviews are based on Capterra and G2.

Agentic AINov 21

Top 9 AI Agents in Accounting in 2026

Tools like Dext, AutoEntry, and Hubdoc have automated data extraction and transaction posting. But these systems are fundamentally still rule-based, often requiring accountants to jump between spreadsheets.

AINov 21

Top AI Note Takers Tested: Motion, Fellow, Otter, and TL;DV

We tested each AI note taker to evaluate their accuracy and features during real world meetings. Follow the links to view our detailed reviews: AI note taker benchmark results Methodology for evaluating AI note taking tools: We tested AI note takers during a strategy session focused on improving sales in the rural market. 1.

Agentic AINov 21

Best 50+ Open Source AI Agents Listed in 2026

Everyone is building AI agents these days. So after hands-on testing with popular AI coding agents, AI agent builders and tools use benchmarks to evaluate their real-world capabilities, we put together a curated list of the best 50+ open source AI agents.

Agentic AINov 21

How ACP Enables Interoperable Agent Communication?

We’re starting to see GenAI move toward standardization, similar to how HTTP transformed the internet in the early 1990s. Just as HTTP enabled the rise of the World Wide Web, new protocols are emerging.