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Cem Dilmegani

Cem Dilmegani

Principal Analyst
706 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, automation, cybersecurity (including network security, application security), data collection including web data collection and process intelligence.

Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and 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

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

Agentic AIAug 30

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.

AIAug 13

Best Design to Code Tools Compared: Detailed Analysis

The design to code landscape has transformed with AI-powered tools promising to bridge the gap between visual design and production-ready code. With 82% of developers now using AI coding assistants daily or weekly, the demand for effective design-to-code solutions has never been higher.

Agentic AIAug 13

10 AI Coding Challenges I Face While Managing AI Agents

From what I have observed, AI agents are particularly helpful during the exploratory phases of work, assisting with implementations or outlining potential approaches.  However, they fall short in contexts that require consistent judgment or strategic reasoning. Below, I outlined the most common AI coding challenges. Click the links to jump to each section: 1.

Agentic AIAug 12

AI Agents vs Agentic AI Systems

Adapted from There’s been a lot of buzz around the terms “AI agents” and “Agentic AI systems” lately. While they’re often used interchangeably, they actually refer to slightly different concepts.

AISep 1

Hybrid RAG: Boosting RAG Accuracy

Dense vector search is excellent at capturing semantic intent, but it often struggles with queries that demand high keyword accuracy. To quantify this gap, we benchmarked a standard dense-only retriever against a hybrid RAG system that incorporates SPLADE sparse vectors.

AIAug 8

AI Application Security: Threats, Vulnerabilities & Real Examples

As 78% of enterprises embed AI into business processes, attackers are targeting models, data, and APIs at unprecedented rates. We explain AI application security and provide real-world examples of threats and vulnerabilities.

Agentic AISep 29

AI Agent Security: 7+ Tools to Reduce Risk

As AI agents gain autonomy, they introduce new risks, ranging from prompt injection to unauthorized access. Security is a critical aspect of AI agents; we cover AI agent security and highlight the tools designed to address it.

AISep 24

AI Web Browsers Benchmark: Complete Selection Guide

We tested 7 AI web browsers, including Perplexity Comet, Arc Max, and Microsoft Edge Copilot, across key performance metrics to determine which solutions deliver practical value for different workflows.

Agentic AIAug 3

Mobile AI Agents: Tools & Use Cases 

At AIMultiple, we focus on developing and assessing Generative AI technologies such as custom GPTs, AI agents, and cloud GPU solutions. Another emerging area of interest is mobile AI agents.  We focus on what modern mobile AI agents are, how they work, and the tools enabling them.

Agentic AIAug 15

Centralizing AI Tool Access with the MCP Gateway

Source: Jahgirdar, Manoj In this article, I’ll walk through the evolution of AI tool integration, explain what the Model Context Protocol (MCP) is, and show why MCP alone isn’t production-ready. Then we’ll explore real-world gateway implementations between AI agents and external tools.

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