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
15 AI Agent Observability Tools: AgentOps, Langfuse & Arize
Observability tools for AI agents, such as Langfuse and Arize, help gather detailed traces (a record of a program or transaction’s execution) and provide dashboards to track metrics in real time. Many agent frameworks, like LangChain, use the OpenTelemetry standard to share metadata with observability tools.
Specialized AI Models: Vertical AI & Horizontal AI in 2026
While ChatGPT grabbed headlines, the real business value comes from AI built for specific problems. Companies are moving beyond general-purpose AI toward systems designed for their exact needs. This shift is creating three distinct types of specialized AI – each solving different business challenges.
Top 30+ NLP Use Cases in 2026 with Real-life Examples
The NLP market will hit $53.42 billion this year. By 2031? We’re looking at $201.49 billion. But here’s what those numbers mean for actual businesses: companies are finally figuring out which NLP applications deliver results versus which ones just sound impressive in vendor demos. We analyzed 250+ deployments across industries.
Mobile AI Agents Tested Across 65 Real-World Tasks [2026]
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.
Top 20 Sustainability AI Applications & Examples in 2026
According to PwC, GenAI could improve operational efficiency, which might indirectly reduce carbon footprints in business processes. Companies can implement strategies to reduce energy consumption during the development, customization, and inference stages of AI models. By leveraging GenAI applications, companies can offset emissions in other areas of their operations.
Synthetic Data Generation Benchmark & Best Practices
We benchmarked 7 publicly available synthetic data generators sourced from 4 distinct providers, utilizing a holdout dataset comprising 70,000 samples, with 4 numerical and 7 categorical features, to evaluate their performance in replicating real-world data characteristics. Below, you can see the benchmark results where we statistically compare the synthetic data generators.
Top 10 Backup Management Software: Key Features & Benefits
With cybercrime costs reaching $10.5 trillion globally in 2025 and the backup software market projected to reach $18.2 billion by 2032 (growing at 8.9% CAGR), choosing the right backup solution can protect you from data loss that could cripple your business operations.
Top Image Recognition Tools Compared in 2026
We evaluated the real-world performance of top cloud vision tools for object detection tasks by benchmarking their default API configurations across 5 classes. This included contrasting performances, analyzing features, and comparing service offerings in relation to pricing. Benchmark Results Performance overview at IoU=0.
APIs in the Telecom Industry: Benefits, Technologies & Examples
Telecom customers care most about service quality and price. To meet these demands, telecom companies are turning to APIs as a practical way to improve services while cutting costs. . Telecom companies started to embrace new technologies and digital transformation to be able to provide high-quality services and reduce costs.
LLM Pricing: Top 15+ Providers Compared in 2026
LLM API pricing can be complex and depends on your preferred usage. We analyzed 15+ LLMs and their pricing and performance: Hover over model names to view their benchmark results, real-world latency, and pricing, to assess each model’s efficiency and cost-effectiveness. Ranking: Models are ranked by their average position across all benchmarks.
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