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Cem Dilmegani

Cem Dilmegani

Principal Analyst
724 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

AINov 7

Generative AI in Marketing: AdsGency AI, Creatify & Jasper

A survey of 5,000 marketers worldwide revealed that their top priority was “implementing or leveraging AI”, showing a growing recognition of its potential in marketing. In particular, generative AI is becoming a critical component of marketing operations, offering capabilities that support more efficient content production, data-driven decision-making, and enhanced content scalability, personalization, and campaign optimization.

CybersecurityNov 6

Top 8 Network Monitoring Software

We tested network monitoring tools to find which ones actually deliver on their promises. Here’s what we found after benchmarking performance, ease of setup, and real-world usability. See top network monitoring tools, assessment of their user experience, and their key features: * Vendors are ordered alphabetically.

Agentic AINov 6

We Tested Mobile AI Agents Across 65 Real-World Tasks

We spent 3 days benchmarking four mobile AI agents (DroidRun, Mobile-Agent, AutoDroid, and AppAgent) across 65 real-world tasks using an Android emulator with applications such as calendar management, contact creation, photo capture, audio recording, and file operations.

CybersecurityNov 6

Top 10 Application Security Tools: Features & Pricing

Application breaches represent 25% of all security incidents.. Based on our extensive research and technical reviewers’ experience, we selected the top 10 application security tools. Within each vendor’s section, we outlined our rationale for our selection.

AINov 6

IBM reshaping Watson for transforming its AI business

Thomas J. Watson Sr. joins Computing-Tabulating-Recording Company (CTR) in 1914 and over the next two decades transforms it into a growing leader in innovation and technology. He built a worldwide industry; it is called to International Business Machines Corporation (IBM) in 1924.

AINov 5

Chatbot Intent Recognition & 5 Intent Examples

Your chatbot misunderstands half of what customers ask. Not because the technology is bad, but because intent recognition, figuring out what users actually want, is harder than vendors admit. When bots misinterpret intent, customers repeat themselves, abandon purchases, and switch to competitors. Fix intent recognition and you fix your bot’s biggest problem.

AINov 5

Speech-to-Speech Software: Use Cases & Examples

Language barriers often create friction in conversations, slowing down collaboration, travel, and even critical services like healthcare. Speech-to-speech (S2S) technology addresses this problem by converting spoken input into natural-sounding speech in another language or style.

DataNov 2

Top 5 Open Source Database Monitoring Tools

Commercial database monitoring tools often promise polished user interfaces and dedicated enterprise support. Open-source solutions are increasingly chosen for their transparency, cost-effectiveness, community-driven innovation, and flexibility. We’ve analyzed both approaches to understand the current landscape.

AIOct 31

The LLM Evaluation Landscape: 16 Frameworks by Functionality

We spent 2 days reviewing popular LLM evaluation frameworks that provide structured metrics, logs, and traces to identify how and when a model deviates from expected behavior.

Agentic AIOct 31

Compare Best AI Agents in Customer Service

AI agents powered by large language models (LLMs) can respond to customer queries in natural language, interpret context, and generate human-like responses. These agents can process and synthesize large volumes of information from sources such as knowledge bases. We compiled a list of the best use cases for the top 4 customer service AI agents.