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
TinyML(EdgeAI): Machine Learning at the Edge
Applications of edge analytics transforming industries and the edge computing market is expected to reach ~$350 billion by 2027. However, the current approach to edge analytics involves machine learning models trained on the cloud. This introduces latency to the system and is prone to privacy issues.
Top 10+ Mobile Device Management Software with Pricing
Companies are expected to maintain an efficient and safe IT environment. In contrast to on-premise work environments, remote and hybrid work require careful IT configuration, with a special emphasis on mobile devices. Mobile Device Management (MDM) software is evaluated on security, ease of use, granular control, scalability, and pricing models.
Best Appen Alternatives in 2026 for Workers & Customers
Appen, an AI data service provider, faces challenges that may explain its declining popularity. We compared the top alternatives to Appen in the AI training data space. The alternatives to Appen depend on your goals. Explore alternatives for Appen’s: Appen alternatives for workers * Data is from Trustpilot, as it primarily consists of worker reviews.
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.
Top No-Code ML Platforms: ChatGPT Alternatives in 2026
We benchmarked 4 no-code machine learning platforms across key metrics: data processing (handling missing values, outliers), model setup and ease of use, accuracy metrics output, availability of visualizations, and any major limitations or notes observed during testing. No-code machine learning tools benchmark Note: Scores represent average performance across kNN and Logistic Regression where applicable.
20 Digital Twin Applications/ Use Cases by Industry
As more sectors explore virtualization, digital twin solutions are gaining mainstream traction. The global market for digital twins is expected to reach $74 billion by 2027, and the proliferation of IoT technology is accelerating this growth.
AI Ethics Dilemmas with Real Life Examples
Though artificial intelligence is changing how businesses work, there are concerns about how it may influence our lives. This is not just an academic or societal problem, but a reputational risk for companies; no company wants to be undermined by data or AI ethics scandals that damage its reputation.
Top 13 Training Data Platforms in 2026
Data is an essential part of the quality of machine learning models. Supervised AI/ML models require high-quality data to make accurate predictions. Training data platforms streamline data preparation from collection to annotation, ensuring high-quality inputs for AI systems.
Large Language Models: Complete Guide in 2026
Large language models (LLMs) are now at the core of enterprise search, customer support, software development, and decision-support workflows, often replacing or augmenting traditional analytics and rule-based systems. Built on transformer architectures and trained on massive text datasets, LLMs can interpret, generate, and summarize language at a scale that was previously impractical.
Top +100 RPA Use Cases with Real Life Examples
RPA can automate repetitive tasks in the front and back offices. A use case-focused approach is critical to optimizing the value of technology investments. We identify 103 use cases and real-life examples of Robotic Process Automation, illustrating its application in automating repetitive tasks across various business, industry-specific, and personal contexts.
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