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 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
Best 10 Serverless GPU Clouds & 14 Cost-Effective GPUs
Serverless GPU can provide easy-to-scale computing services for AI workloads. However, their costs can be substantial for large-scale projects. Navigate to sections based on your needs: Serverless GPU providers offer different performance levels and pricing for AI workloads. Compare the most cost-effective GPU configurations for your fine-tuning and inference needs across leading serverless platforms: You…
Top Open Source UEBA Tools & Commercial Alternatives
At their core, UEBA solutions identify patterns in data, whether from real-time streams or historical datasets. After reviewing the documentation for each open-source UEBA framework and tool, I selected the leading open-source behavior analytics technologies that provide standard SIEM-like capabilities, alerting, support for the MITRE ATT&CK threat intelligence framework, and API-based ingestion from data sources.…
Top 6 Data Collection Methods for AI and Machine Learning
While some companies rely on AI data collection services, others gather their data using scraping tools or other methods. See the top 6 AI data collection methods and techniques to fuel your AI projects with accurate data: Data crowdsourcing involves assigning data-collection tasks to the public, providing instructions, and creating a platform for sharing. Businesses…
Top 6 AS2 Software in 2026
Finding AS2 software that fits your budget and technical needs takes some digging. We’ve narrowed down the options to managed file transfer tools that actually deliver on AS2 support: JSCAPE MFT Server handles AS2 transfers with Drummond certification, which means it meets industry standards for encryption, digital signatures, and MDNs (Message Disposition Notifications). The platform…
Best Appen Alternatives in 2026 for Workers & Customers
We analyzed the top Appen alternatives by comparing worker review ratings from Trustpilot, crowd size, payment schedules, and publicly available company data. The alternatives differ significantly depending on what you need from Appen. Browse by role: * Data is from Trustpilot, as it primarily consists of worker reviews. ** Data gathered from worker reviews. In…
Top 15 Data Collection Services
Whether you need human-collected datasets, large-scale web data, or market insights, explore the options below to find the right data source for your project. Despite the efficiency of web data collection and synthetic data generation, human-generated data remains essential for AI development. Here, we compare the top 12 data collection services and data partners that…
Top 20 ITSM Case Studies
Leveraging IT Service Management (ITSM) tools is essential for businesses aiming to increase the efficiency of their IT operations and enhance service delivery. Explore ITSM case studies across various industries such as education, manufacturing, transportation, and telecommunications, and see how companies have leveraged ITSM solutions to overcome service management challenges, improve efficiency, and boost customer…
Vision Language Models Compared to Image Recognition
Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure). Mean Average Precision (mAP) served as our primary accuracy metric, supplemented by latency, cost and class-specific…
Pros & Cons of Top 7 RPA Alternatives to Consider
Robotic Process Automation (RPA) is a beneficial technology that can automate up to 70-80% of rules-based processes.35 However, ~40% of companies fail to reach their expectations of cost reduction after RPA implementation.36 This is because RPA is not the right fit for every process, and there are potential pitfalls of RPA implementation, such as costly…
DGX Spark vs Mac Studio & Halo: Benchmarks & Alternatives
NVIDIA’s DGX Spark entered the desktop AI market in 2025 at $4,699, positioning itself as a “desktop AI supercomputer”. It packs 128GB of unified memory and promises one petaflop of FP4 AI performance in a Mac Mini-sized chassis. See the benchmark results on value and performance compared to alternatives: When comparing systems on the demanding…
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