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
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. As adoption accelerates, AI is…
Top 12 SEO AI Use Cases with Case Studies
As algorithms change and consumer expectations rise, it has become more challenging to compete for accessibility in search results. Conventional SEO techniques, which depend on manual research and minor updates, frequently fall behind these developments. AI-powered SEO tools address this challenge by automating complex tasks and aligning content more precisely with user intent. Explore the…
20 Chatbot Companies To Deploy
With 200+ chatbot platforms on the market, the choice isn’t obvious. The right vendor depends on three things: how your team wants to build (drag-and-drop vs. code), which systems you need to connect to, and how much conversation volume you’re actually handling. We compared the 20 most widely used chatbot platforms for building production applications.…
Top 40 Chatbot Applications with Examples
The global chatbot market is valued at $10.32–$11.45 billion in 2026, up from $8.7 billion in 2024, and projected to reach $32.45 billion by 2031 at a 23.15% CAGR. The generative AI chatbot segment alone is valued at $12.98 billion and growing faster, at a 31.11% CAGR. That growth is real, but the more significant…
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,…
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 2030.77 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…
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…
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…
AIMultiple Newsletter
1 free email per week with the latest B2B tech news & expert insights to accelerate your enterprise.