Cem Dilmegani
Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, and Washington Post, global firms like Deloitte and 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 enterprise AI and software.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
- Hosted on American Variety Radio, answering Court Lewis' questions on AGI on April 25th, 2026.
- Answered Korea24's questions on job loss due to AI on November 5th, 2025. Recording available on: 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
Top 10 Open Source Sentiment Analysis Tools
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. Explore the top open source sentiment analysis tools and no-code solutions for businesses looking to pilot sentiment…
Best 14 Android Emulators
Android emulators let you run Android apps and games on PC, Mac, and browsers. Different emulators excel in different use cases. Below is a list of the top Android emulators categorized by their strengths from gaming to app development, security testing, and everyday Android app usage. We selected and tested several of these tools based…
XR/AR in Manufacturing: 7 Real-Life Use Cases
Recent industry research shows that XR device shipments (e.g. lightweight AR or smart glasses for industrial use) grew over 40 % year‑over‑year in 2025. With adoption accelerating, XR technologies are increasingly helping manufacturers improve efficiency, safety, and collaboration. Explore the top 7 use cases of XR/AR in manufacturing with real-world examples. Virtual reality solutions can…
AutoSys: Key Features and User Insights
Interest in Broadcom’s AutoSys is declining (Source: Google Trends) and it has a lower average rating on review platforms compared to most other workload automation tools. This may be partially explained by: Dive into AutoSys’s capabilities, user evaluations, and outlook to learn more: AutoSys was originally developed by CA Technologies and acquired by Broadcom in…
Top 20 Deception Technology Companies
Deception technology deploys fake assets to detect attackers who have bypassed perimeter defenses. Companies can use deception technology to detect and isolate a cyberattack before it reaches the organization’s actual systems. We cover the top 20 deception technology companies. This is possibly an incomplete list in an emerging field, feel free to suggest other vendors…
Generative AI ERP Systems: 10 Use Cases & Benefits
Enterprise resource planning (ERP) software helps businesses integrate workflows across finance and operations. Generative AI, alongside technologies like RPA, has the potential to enhance ERP processes. The financial use of Generative AI in ERP systems can cover the automation of entire procure to pay cycle and such as the accounts payable process. Another important element…
Python RPA: 8 Use-Cases for Developers
Robotic process automation (RPA) lets software robots run repetitive computer tasks. Python gives developers a flexible way to build those robots in code. The global RPA market sits at about USD 28 billion in 2025 and is forecast to reach roughly USD 247 billion by 2035. Yet between 30% and 50% of RPA projects fail,…
AI Data Quality: Challenges & Best Practices
Poor data quality delays the successful deployment of AI and ML projects. Even the most advanced AI algorithms can yield flawed results if the underlying data is of low quality. Explore the importance of data quality in AI, the challenges organizations encounter, and the best practices for ensuring high-quality data: Data quality is essential for…
Top 15 Training Data Platforms
A model is as good as the data it learns from. Supervised models need accurate, well-labeled examples to make correct predictions. Training data platforms cover the steps between raw data and a usable dataset: sourcing, labeling, and quality checks. See the top training data platforms, split by data marketplaces and data labeling tools, and mapped…
Top 8 Open Source AI Coding Agents
In prior evaluations, we benchmarked both open-source and proprietary Agentic CLIs, focusing on their performance in web development tasks, and some open-source agents performed as successfully as the paid options. Therefore, we also listed the top open-source coding agents for users with privacy concerns. For methodology, see the AI coding benchmark. For more details about…
AIMultiple Newsletter
1 free email per week with the latest B2B tech news & expert insights to accelerate your enterprise.