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Cem Dilmegani

Cem Dilmegani

Principal Analyst
360 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

Enterprise SoftwareJan 23

Top 10 Open Source Job Schedulers & WLA Tools

Businesses leverage open-source job schedulers and workload automation tools to automate IT tasks without paying licensing costs or getting locked in to a specific vendor.

Enterprise SoftwareJan 23

WLA Migration in 2026: Best Practices & Vendor Approaches

Organizations reconsider replacing their existing workload automation tools, with many actively exploring or transitioning to new solutions. The right workload automation solutions can provide immediate gains in scalability, reliability, and integration capabilities. Explore workload automation (WLA) migration, best practices, what to pay attention to, and the differing approaches from different vendors.

AIJan 23

17 Generative AI Healthcare Use Cases

Healthcare systems are facing increased data volumes, staff shortages, and rising expectations for personalized care. Generative AI is emerging as a key solution by synthesizing unstructured medical data, such as clinical notes, imaging reports, and patient histories, into insights for clinicians and administrators.

AIJan 22

50+ ChatGPT Use Cases with Real Life Examples

ChatGPT hit 900 million weekly active users in early 2026, roughly 10% of the world’s population. OpenAI reached $10 billion in annual recurring revenue by mid-2025. But what are those 900 million people doing with it? OpenAI and Harvard economist David Deming analyzed 1.5 million conversations to find out.

DataJan 22

Best Amazon Mechanical Turk Alternatives

This analysis explores some downsides of using Amazon Mechanical Turk (MTurk), a popular platform for AI data collection and market research. It also compares the top Amazon Mechanical Turk alternatives on the market. Readers interested in MTurk alternatives usually fall under 3 categories; select yours to see relevant alternatives for your business.

AIJan 22

GPU Software for AI: CUDA vs. ROCm in 2026

Raw hardware specifications tell only half the story in GPU computing. To measure real-world AI performance, we ran 52 distinct tests comparing AMD’s MI300X with NVIDIA’s H100, H200, and B200 across multi-GPU and high-concurrency scenarios.

AIJan 22

GPU Marketplace: Shadeform vs Prime Intellect vs Node AI in 2026

Finding available GPU capacity at reasonable prices has become a critical challenge for AI teams. While major cloud providers like AWS and Google Cloud offer GPU instances, they’re often at capacity or expensive. GPU marketplace aggregators have emerged as an alternative, connecting users to dozens of providers through a single interface.

AIJan 22

Invoice OCR Benchmark: Extraction Accuracy of LLMs vs OCRs

Invoice processing is a critical yet labor-intensive business operation that traditionally requires manual data extraction and entry into accounting systems. This manual approach is time-consuming and susceptible to human error.

Agentic AIJan 22

AI Agents: Operator vs Browser Use vs Project Mariner

AI agents are increasingly marketed as end-to-end digital workers, but real-world performance can vary widely depending on the task, tools, and execution environment. To understand what these systems can genuinely deliver today, we conducted hands-on benchmarking across practical business scenarios.

Enterprise SoftwareJan 22

Blockchain Case Studies Across Key Industries

A recent forecast projects the blockchain market will reach 943 billion U.S. dollars by 2032, growing at a CAGR of 56%.While the potential is massive, executives face uncertainty due to the varying maturity of blockchain solutions across industries.