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
AI in Sales: 15 Use Cases & Examples
Artificial intelligence can enhance sales processes from lead generation to sales forecasting, helping businesses overcome low conversion rates and long sales cycles. Check out AI in sales use cases structured around key sales activities to show how sales AI tools can accelerate the sales cycle and enhance sales effectiveness: Sales forecasting is crucial in the…
Top 50 Deep Learning Use Case & Case Studies
Deep learning uses artificial neural networks to learn from data. When trained on large, high-quality datasets, it achieves high accuracy, making it valuable wherever you have abundant data and need accurate predictions. Below are real deep learning applications across industries and business functions, with concrete examples. Deep learning models identify, classify, and analyze structured data,…
Will Pi Network make you rich? No, but it can pay cents/hour
Users can invest their time or money into Pi Network. Nothing written here should be construed as investment advice. We don’t expect anyone except the founders to benefit from PI Network in a significant way because: Despite all this, we like their optimistic posts as they enter 2026 with a plummeting token price: It is…
Generative AI in Fashion: Top 13 Use Cases & Examples
89% of all companies across different sectors are switching to digital technologies, and the generative AI in the fashion industry is not an exception. McKinsey reports that fashion brands and companies invested approximately 2% of their income in emerging technologies. Moreover, they estimate the figure will rise to 3.5% by 2030.32 Blockchain technology, non-fungible tokens…
Web Crawler Benchmark to Feed Websites to AI
We benchmarked four crawl APIs across three domains of varying difficulty at three max depth levels (5, 10, 20) with a 1,000-page limit, measuring crawl coverage, execution time, link discovery, markdown link quality, and title extraction accuracy. If you aim to: You can read our benchmark methodology. Firecrawl consistently crawled around 100 pages on theregister.com…
Mobile AI Agents Tested Across 65 Real-World Tasks
We spent 3 days benchmarking four mobile AI agents (DroidRun, Mobile-Agent, AutoDroid, and AppAgent) across 65 real-world tasks using an Android emulator with applications such as calendar management, contact creation, photo capture, audio recording, and file operations. See benchmark results including real-world performance comparison, costs and execution times: Highest success rate (43%) with high cost…
Top LLMOps Tools & Compare them to MLOPs
LLMOps platforms handle the operational side of running large language models: deployment, monitoring, evaluation, and cost management. We examined top LLMOps tools, their core features, pricing models, and how they differ from each other to help identify the best fit for various use cases. A breakdown of each metric is provided below: LLMOps platforms support…
Best Design to Code Tools Compared: Detailed Analysis
Design-to-code tools have changed more in the past 18 months than in the decade before that. The category used to mean “export some CSS from Figma.” Now it spans full-stack app builders, bidirectional MCP integrations that write back to the canvas, and agentic platforms shipping production branches from Slack messages. The tools on this list…
10+ Agentic AI Trends and Examples
We reviewed and compared Agentic AI trends from several major industry reports, benchmarks, and vendor disclosures. The sources point out that the future of agentic AI is about integrating AI deeply and transforming business approaches by restructuring current frameworks. Key takeaways: As organizations scale their AI and analytics initiatives, maintaining high data quality across pipelines…
Best 50+ Open Source AI Agents Listed
Everyone has been building AI agents so after hands-on testing with popular AI coding agents, AI agent builders and tools use benchmarks to evaluate their real-world capabilities, we put together a curated list of the best 50+ open source AI agents. Click the category headers to jump straight to our top picks: Agent development &…
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