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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

AIMar 14

AI Code Review Tools Benchmark

With the increased use of AI coding tools, codebases have become more prone to vulnerabilities, which increased the need for effective code reviews.

DataMar 13

Reproducible AI: Why it Matters & How to Improve it

Reproducibility is a fundamental aspect of scientific methods, enabling researchers to replicate an experiment or study and achieve consistent results using the same methodology. This principle is equally vital in artificial intelligence (AI) and machine learning (ML) applications, where the ability to reproduce outcomes ensures stable inference across model environments.

Enterprise SoftwareMar 13

Top 30+ Cloud Cost Management Tools: Focus & Pricing

Cloud spending is one of the fastest-growing costs for modern businesses. However, more than 80% of organizations consider managing cloud costs their top challenge. We provide concise comparisons and actionable information to make evaluating and selecting the right cloud cost management tools faster and easier for your organization.

AIMar 13

AGI Benchmark: Can AI Generate Economic Value

AI will have its greatest impact when AI systems start to create economic value autonomously. We benchmarked whether frontier models can generate economic value. We prompted them to build a new digital application (e.g., website or mobile app) that can be monetized with a SaaS or advertising-based model.

Agentic AIMar 13

RL Environments: The Infrastructure Behind Agentic AI

Reinforcement learning environments are controlled environments where AI agents take actions, observe outcomes, and receive feedback. They are becoming more useful as models move from one-shot answers to multi-step work in coding, browser tasks, customer support, and business software. RL environment companies Some companies sell custom environments for coding, finance, enterprise workflows, or computer-use tasks.

Enterprise SoftwareMar 12

Top 10 Globalscape Alternatives

We analyzed the leading alternatives to GlobalScape in the secure file transfer space. The right choice depends on what’s driving your search: * Ratings are based on Capterra and G2. The vendors are listed according to the review rates. GlobalScape EFT GlobalScape handles enterprise file transfers through folder monitoring and trigger-based automation.

Enterprise SoftwareMar 12

Linux Job Scheduler: Review, Guide & Alternatives

Linux job scheduler and ‘cron,’ a time-based job scheduler, are commonly used in Linux job scheduling. If you: * Linux Completely Fair Scheduler (CFS) ** Enterprise job schedulers include Stonebranch, ActiveBatch, RunMyJobs & JAMS Scheduler.

AIMar 12

Enterprise Generative AI: 11 Use Cases & Best Practices

Generative AI (GenAI) presents novel opportunities for enterprises compared to middle-market companies or startups, including: However, generative AI brings challenges unique to large organizations. For example: Explore our practical enterprise AI use cases to learn how large companies can build, deploy, and govern their own generative AI models effectively.

Enterprise SoftwareMar 12

Top RPA Tools / Vendors & Their Features

Based on our experience with RPA software during our RPA benchmark as well as external market presence metrics like number of reviews and employees, we selected the leading and emerging RPA providers.

Enterprise SoftwareMar 12

Top 10 ERP AI Use Cases & Case Studies

Enterprise resource planning (ERP) systems help organizations manage core business processes such as finance, operations, and human resources within a single platform. As business processes grow more complex and data-driven, companies are increasingly integrating AI capabilities, such as machine learning and conversational AI, into ERP systems to automate tasks, improve decision-making, and increase efficiency.