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 Utilities with Top 15 Use cases & case studies
Utility companies face several challenges such as energy cost volatility, supply-chain disruptions, increasing customer demands for decarbonization and clean energy, and the need for personalized experiences. AI adoption can help them streamline operations, optimize resource management, enhance customer interactions, and develop new digital services.
QC Companies: Guide Based on 4 Ecosystem Maps
Quantum computing, which has wide-ranging applications in optimization, research and cryptography, is driven by these organizations: Quantum hardware is an emerging computing technology which relies on complex hardware. As in the early days of personal computing, there are companies specialized on hardware, software and end-to-end solutions.
22 AutoML Case Studies: Applications and Results
Though there is a lot of buzz around autoML, we haven’t found a good compilation of case studies. So we built our comprehensive list of automated machine learning case studies so you can see how autoML could be used in your function/industry.
Best 7 AI Testing Platforms for QA
We evaluated AI testing platforms embedded with AI agents; most were overhyped Selenium/Playwright with marketing. A few were capable of writing/maintaining test cases or visual testing, though even these tools still have notable limitations. From these, we selected 7 platforms and categorized them by their primary focus areas.
Top 4 WAN Monitoring Software
We selected WAN monitoring software that offers bandwidth monitoring and traffic analysis, along with real-time tracking of network devices, servers, applications, and infrastructure across wide-area networks. See a comparison of popular WAN monitoring software: Selection criteria We selected WAN monitoring tools meeting these criteria: Top 5 WAN Monitoring Software 1.
Top 5 Customer Self Service Tools
Customer self service tools enable customers to find answers and resolve their issues without human intervention. improving overall customer satisfaction.
Top 10 Tools for Contact Center Automation
Contact centers must automate to remain competitive. Organizations can implement comprehensive end-to-end solutions or deploy targeted workload automation tools like RPA to address specific operational challenges. These technologies reduce costs while improving service quality and agent productivity.
Top 8 Observability Software with Pricing and Feature Comparison
Observability platforms promise complete visibility across distributed systems, but selecting the right one is hard when every vendor claims they do everything. We analyzed the top 8 observability software by looking at their documented capabilities, public pricing, verified customer reviews, and enterprise reference cases.
7 Network Monitoring Use Cases with Real-Life Examples
Effective network monitoring is a cornerstone of efficient IT management, especially for complex, hybrid cloud environments. Through real-world examples, we will illustrate the practical benefits and applications of network monitoring: Core Network Monitoring Use Cases 1. Performance Optimization Network monitoring spots bottlenecks and inefficiencies by analyzing traffic patterns and bandwidth usage.
Top 5 AI Services to Enhance Business Efficiency
AI adoption is rapidly increasing. Around 98% of companies are experimenting with AI, reflecting its growing accessibility and potential to improve operations. Yet only 26% have advanced beyond trials to achieve measurable business value, showing that many are still building the capabilities needed to scale AI effectively.
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