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
Generative AI in Retail: Use Cases, Examples & Benefits
Retail businesses strive to enhance customer experiences and loyalty. This requires producing attractive content in various formats, effective marketing efforts, and exceptional customer service. With generative AI, retailers can resolve most of these issues through automation, particularly by enhancing their ability to analyze customer data for more personalized customer experiences.
Digital Transformation for Telecoms with Case Studies
The telecommunication or telecom sector is a ~$1.5 trillion market that makes communication possible worldwide. As remote work becomes more widespread, consumer needs continuously change in the telecom sector, demanding better services from telecom service providers. Like every other sector, the telecommunications sector can also benefit from digital transformation to improve its services.
AI in HR: Steps & Use cases with Real-Life Examples
Artificial intelligent (AI) usage in human resources (HR) has emerged as a game-changer by enhancing efficiency and reducing the risk of overlooking qualified candidates, where the average initial résumé screening time is just 7.4 seconds.
Best Design to Code Tools Compared: Detailed Analysis
The design to code landscape has transformed with AI-powered tools promising to bridge the gap between visual design and production-ready code. With 82% of developers now using AI coding assistants daily or weekly, the demand for effective design-to-code solutions has never been higher.
Generative AI for Email Marketing: Applications & Examples
Generative AI has evolved beyond basic email content creation to enable real-time personalization, multimodal interactions, and cross-channel orchestration that responds to customer behavior. While 60% of CMOs plan to prioritize AI adoption by 2026,current implementations often miss critical capabilities like dynamic content adaptation and voice-integrated workflows that are reshaping email effectiveness.
Automotive APIs: 7 Use Cases, Databases & Solutions
McKinsey claims that the overall market for automotive software and related electronic components will grow by 7% CAGR from 2020 to 2030.. In 2010, on average a car included 10 million lines of software code, while it ran on 100 million lines of code in 2018.
Agentic AI n8n Tutorial
We built an AI agent within n8n designed to provide investment advice, showcasing the platform’s capabilities for agentic AI. This process involved configuring the agent to perform technical and fundamental stock analysis by integrating 5 distinct tools and pulling financial data from various APIs.
Top 10+ Legal AI Use Cases & real-life examples
The legal AI software market is expected to quadruple in the next five years, as AI technology offers significant potential to help lawyers focus on higher-value tasks. Despite challenges such as biased forecasts and tracking changing regulations, there are many manual tasks within legal departments that can be automated.
Top 5 Insurance Chatbots with Real-life Use Cases
In 2024, the global insurance industry’s premium income increased by approximately 9%, totaling ~$8 trillion, highlighting strong demand and escalating digital investments. At the same time, the global insurance chatbot market is projected to reach a value of $5238 million by 2033, indicating the rapid growth of chatbots in the insurance industry industry.
Top 5 Technologies Improving Insurance Fraud Detection
According to the FBI, insurance fraud (excluding health insurance) costs more than $40 billion annually in the U.S. alone.(Insurance Fraud. FBI. Accessed: February/11/2025.) Technological tools such as artificial intelligence (AI), the Internet of Things (IoT), machine learning, and blockchain can be used by insurers to more effectively detect and prevent insurance fraud.
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