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Cem Dilmegani

Cem Dilmegani

Principal Analyst
573 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

DataOct 31

Top 5+ Geonode Alternatives: Pricing & Features in 2026

Proxy services are essential for companies to use technologies such as web scraping, ad verification, and market research. We reviewed Geonode and its top competitors including Bright Data, Webshare, Oxylabs, Decodo, SOAX, and IPRoyal.

CybersecurityOct 31

Top 20+ Network Security Audit Tools in 2026

Network security audit tools provide real-time insights into a network’s security by scanning tools across the environment and alerting administrators to emerging threats, vulnerabilities, or new patches. Given the broad scope of their functions, these tools vary significantly.

AIOct 28

GPT-5: Best Features, Pricing & Accessibility in 2026

We now have GPT-5, the latest and one of the most advanced language models. GPT-4 vs. GPT-5 The interactive comparison below shows how GPT-5 differs from GPT-4 across architecture, performance, and pricing. Historical Progression Release & Architecture What’s Different in GPT-5 Multiple Models, One System GPT-4 ran every prompt through the same model.

AIOct 28

Custom AI: When to Build Your Own Solutions in 2026

While ready-made AI tools can meet many business needs, they often fall short in areas that require deep data understanding or specialized workflows. Organizations working in complex or niche industries may find that generic systems don’t fully align with their operations or leverage their proprietary data.

AIOct 28

10 Steps to Developing AI Systems

IBM identifies the top AI adoption challenges as concerns over data bias (45%), lack of proprietary data (42%), insufficient generative AI expertise (42%), unclear business value (42%), and data privacy risks (40%).These obstacles can hinder AI implementation, slow innovation, and reduce the return on investment for organizations adopting AI technologies.

DataOct 27

Few-Shot Learning: Methods & Applications

Imagine a healthcare startup building an AI system to detect rare diseases. The challenge? There isn’t enough labeled data to train a traditional machine learning model. That’s where few-shot learning (FSL) comes in. From diagnosing complex medical conditions to enhancing natural language processing, few-shot learning is redefining how AI learns from limited examples.

Enterprise SoftwareOct 27

Control-M for Enterprise Workload Automation

Control-M by BMC Software helps teams coordinate and automate data and application workflows across environments, including mainframes, the cloud, and hybrid systems. It gives users a single place to schedule jobs, track progress, and handle dependencies.

Agentic AIOct 24

Building Personal AI Agents + 18 Agent Platforms and Tools

We spent the two days experimenting with real-world demos and tools to build personal AI assistants that can handle your tasks, such as scheduling meetings, managing notes, or sorting through emails. We will dive into three main approaches to building and using personal AI assistants, with real-world examples for each: 1.

Enterprise SoftwareOct 23

AI Utilities with Top 15 Use cases & case studies

Utility companies face several challenges such as energy cost volatility, supply-chain disruptions, increasing customer demands for decarbonization and clean energy, and the need for personalized experiences. AI adoption can help them streamline operations, optimize resource management, enhance customer interactions, and develop new digital services.

Enterprise SoftwareOct 21

Top 4 WAN Monitoring Software in 2026

We selected WAN monitoring software that offers bandwidth monitoring and traffic analysis, along with real-time tracking of network devices, servers, applications, and infrastructure across wide-area networks. See a comparison of popular WAN monitoring software: Selection criteria We selected WAN monitoring tools meeting these criteria: Top 5 WAN Monitoring Software 1.