Cem Dilmegani
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
- Cem Dilmegani, Post-AI Banking: Millions of jobs at risk as banks automate their core functions. International Banker.
- Cem Dilmegani, Bengi Korkmaz, and Martin Lundqvist (December 1, 2014).Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Media, conference & other event presentations
- Answers to Korea24's questions on job loss due to AI, Korea24
- Real Estate and Technology, presented by Hofstra University’s Wilbur F. Breslin Center for Real Estate Studies and the Frank G. Zarb School of Business in 2023 and 2024.
- Radar AI session (June 22, 2023): "Increasing Data Science Impact with ChatGPT".
- Generative AI Atlanta meetup: Generative AI for Enterprise Technology.
Sources
- Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
- Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
- Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
- Science, Research and Innovation Performance of the EU, European Commission.
- EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
- Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
- We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.
Latest Articles from Cem
AI Adoption in Manufacturing: Insights from 100 Companies
Our analysis of the top 100 manufacturing companies by revenue from the Forbes Global 2000, spanning automotive, industrial equipment, chemicals, consumer electronics, and more across 15 countries, reveals two clear patterns in how manufacturers approach artificial intelligence. We evaluated three key metrics across all 100 companies: AI partnerships, open-source contributions, and AI initiative outputs.
Top 50 Deep Learning Use Case & Case Studies
Deep learning uses artificial neural networks to learn from data. When trained on large, high-quality datasets, it achieves high accuracy, making it valuable wherever you have abundant data and need accurate predictions. Below are real deep learning applications across industries and business functions, with concrete examples.
Top 9 PAM Solutions with Free Alternatives
We spent three days testing and reviewing popular Privileged Access Management (PAM) solutions. We used the free trials and admin consoles of BeyondTrust, Keeper PAM, and ManageEngine PAM360. For solutions that required registration, we relied on official product documentation and verified user experiences to assess their capabilities.
AI Text Generation: Top 17 Use Cases & 5 Case Studies
Generative AI, a subset of artificial intelligence, enables the creation of new content, such as text, code, images, designs, and videos, by learning from and building on existing data.
15 Procurement Case Studies & Lessons Learned
Effective procurement practices are necessary across all industries. By examining procurement case studies in various sectors, from non-profit to technology, healthcare, and beyond, we gain valuable insights into the impact of procurement solutions and best practices that can drive success in any industry.
RMM Pricing in 2026: 10 Products Analyzed
Understanding RMM software pricing models and factors is important for making informed decisions. Remote monitoring and management products may vary based on the pricing structure. Companies can evaluate product pricing based on the number of technicians or endpoints required. Here, we explore the structures of 10 software RMM pricing models.
10 GAN Use Cases
While GANs pioneered many early generative AI applications, particularly in image synthesis and style transfer, most consumer-facing generative AI tools today rely on diffusion-based architectures or related approaches such as flow matching and diffusion transformers (DiT).
Generative AI Copyright: Law, Litigation & Best Practices in 2026
We analyzed tens of court cases and licensing deals to answer the key questions about copyright and generative AI. This is not legal advice. Copyright law varies by jurisdiction and is evolving fast. The Three Big Questions 1.
Web Scraping for Recruiters: Top Tools & Techniques
Bright Data’s Data collector automatically extracts publicly available data from LinkedIn for recruiters.
Top 7 Open Source Sentiment Analysis Tools
Text analytics is estimated to exceed a global market value of US$ 56 billion by 2029. Sentiment analysis has gained worldwide momentum as one of the text analytics applications. Businesses that have not implemented sentiment analysis may feel an urge to find out the best tools and use cases for benefiting from this technology.
AIMultiple Newsletter
1 free email per week with the latest B2B tech news & expert insights to accelerate your enterprise.