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
Top 10 Tungsten Automation (Kofax) Alternatives
With the acceleration of artificial intelligence (AI), businesses are constantly looking for tools to: Intelligent document processing (IDP) tools can do all this, and more. For this reason, the global Intelligent Document Processing (IDC) market sizeis expected to grow from USD 1.1 billion in 2022 to USD 5.
30 Network Performance Metrics to Measure Network Health
The ability to measure network performance is more crucial than ever for businesses to ensure seamless operations. To address this challenge, understanding and effectively utilizing network performance metrics becomes the key resolution.
Alphabet's AI Investments in 38 Companies
After acquiring DeepMind, and spending more than $13 billion to build data centers Google became one of the leading players in the AI field Driven by its AI investments and search engine investments the tech giant reported a strong profit growth of 25+% in the second quarter of 2024, beating analysts’ expectations.
AI eCommerce: 25 Use Cases to Optimize Sales and CX
AI is helping eCommerce businesses address key challenges like cart abandonment, inefficient customer support, and inventory mismanagement. AI eCommerce tools can reduce churn, optimize operations, and deliver personalized shopping experiences by analyzing customer behavior.. These capabilities not only enhance customer satisfaction but also drive sales growth in a competitive market.
Top 4 AI Blog Generators Benchmarked: Quality & UX
We evaluated the top 4 AI blog generators across more than 10 dimensions, examining their performance in content quality, language and style, technical optimization, usability, and feature sets. See the leading solutions: Benchmark results See how these scores were generated and our methodology.
Top 6 Data Collection Methods for AI and Machine Learning
While some companies rely on AI data collection services, others gather their data using scraping tools or other methods. See the top 6 AI data collection methods and techniques to fuel your AI projects with accurate data: Overview of AI data collection methods 1. Crowdsourcing Online talent platforms, such as crowdsourcing platforms, have various benefits.
Data Collection: 10+ Methods Across 6 Key Use Cases
The role of data has become paramount for digitally transforming enterprises. Whether it’s marketing or AI data collection, businesses have become increasingly reliant on accurate data collection to make informed decisions; it’s essential to have a clear strategy in place. This article explores the top techniques for data collection across different sectors and use cases.
55 Process Improvement Case Studies & Project Results
Business leaders know that process improvement reduces costs and increases customer satisfaction. Yet, it can be difficult for process experts and business analysts to understand the different process improvement approaches and process analysis tools. Explore typical process improvement project results, case studies and benchmarks to set targets for your improvement initiatives.
GPU Cluster: Key Things to Know & 5 Use Cases
A GPU cluster is a set of computers where each node is equipped with a Graphics Processing Unit (GPU). Computational demands are ever-rising, whether in cloud or traditional markets. In this context, having the right knowledge on GPU clusters is more important than before.
Top 15 Computer Vision Use Cases with Examples
With the global computer vision market projected to reach US$30 billion in 2025 (see the graph below), business leaders face a critical challenge: identifying where it delivers ROI, from healthcare diagnostics to automated logistics.
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