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
The 7 Layers of Agentic AI Stack
The rise of agentic AI has introduced a technology stack that extends well beyond simple calls to foundation-model APIs. Unlike traditional software stacks, where value often concentrates at the application tier, the agentic AI stack distributes value more unevenly. Some layers offer strong opportunities for differentiation and moat building, while others are rapidly becoming commoditized.
Top 15 Logistics AI Use Cases & Examples
Persistent inefficiencies, rising operational costs, and ongoing supply chain disruptions continue to challenge logistics functions globally. These pressures are straining traditional systems, reducing service reliability, and limiting organizations’ ability to scale. In response, companies are increasingly turning to artificial intelligence to enhance end-to-end visibility, strengthen resilience, and optimize core functions.
Top 100 RPA Use Cases with Real Life Examples
RPA can automate repetitive tasks in the front and back offices. A use case-focused approach is critical to optimizing the value of technology investments. We identify 100 use cases and real-life examples of Robotic Process Automation, illustrating its application in automating repetitive tasks across various business, industry-specific, and personal contexts.
MCP Benchmark: Top MCP Servers for Web Access
We benchmarked 8 MCP servers across web search, extraction, and browser automation by running 4 different tasks 5 times each. We also tested scalability with 250 concurrent AI agents.
Top 7 Open Source HRIS Tools with Key Features
Open-source HRIS software provides a more affordable alternative to closed-source code HR information system tools, although they have some limitations, such as vulnerabilities from open source. These systems are widely used for their flexibility and cost-effectiveness. We’ve gathered a selection of commonly used open-source HRIS tools, each with its own set of features.
Top 7 RPA Linux Software to Discover
Most robotic process automation (RPA) bot development is going on in Windows machines since most corporate end users rely on Windows. However, the Linux operating system has particular advantages over MacOS and Windows, and RPA tools can add value to Linux systems as well.
Top 10 IT Service Management Tools: Features & Pricing
We evaluated the top 10 IT service management tools based on user experience, performance, and feature set. Explore our findings to see how these leading solutions differ in areas including AI features, communication integrations, DevOps, monitoring & security connections, and deployment options.
Prices of Top 5 IT Service Management (ITSM) Software
IT Service Management (ITSM) tools that support incident, problem, change, and knowledge base management offer diverse pricing models. See IT service management pricing details of the top 5 providers and the feature guide for small businesses and enterprises. ITSM pricing comparison Note: Pricing information is obtained from vendor websites.
Large Multimodal Models (LMMs) vs LLMs
We evaluated the performance of Large Multimodal Models (LMMs) in financial reasoning tasks using a carefully selected dataset. By analyzing a subset of high-quality financial samples, we assess the models’ capabilities in processing and reasoning with multimodal data in the financial domain. The methodology section provides detailed insights into the dataset and evaluation framework employed.
Top 7 Penetration Testing Use Cases with Examples
According to IBM’s “Cost of a Data Breach Report,” the average financial impact of a data breach has surged to an alarming $4.45 million per incident. With the growing reliance on digital platforms and accelerated digital transformation, penetration testing has become an indispensable tool for businesses seeking to fortify their cybersecurity defenses.
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