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
Traditional vs. Online Survey Research
Conducting survey research helps businesses collect data from customers, employees, or the public. Collecting data with traditional methods, such as paper-pencil or telephone, is costly, time-consuming, and cannot keep up with the digitally transforming world. Thanks to online survey research tools, businesses can quickly reach a broad audience’s opinion and make necessary adjustments.
Top companies in AI-powered medical imaging
Around 75% of all medical malpractice claims against radiologists are related to diagnostic errors. Many radiology errors can be traced back to breakdowns in communication during the imaging or reporting process. AI algorithms can be trained to analyze medical images and identify patterns and abnormalities that may be missed by human eyes.
7 Key Data Fabric Use Cases
In this article, we explain 7 key data fabric use cases such as data integartion, data analytics, data governance, and data virtualization.
Explainable AI (XAI): Guide to enterprise-ready AI
As AI tools become more advanced, more computations are done in a “black box” that humans can hardly comprehend. This approach is problematic since it prevents transparency, trust and model understanding. After all, people don’t easily trust a machine’s recommendations that they don’t thoroughly understand.
Reproducible AI: Why it Matters & How to Improve it
Reproducibility is a fundamental aspect of scientific methods, enabling researchers to replicate an experiment or study and achieve consistent results using the same methodology. This principle is equally vital in artificial intelligence (AI) and machine learning (ML) applications, where the ability to reproduce outcomes ensures the reliability and robustness of models and findings.
Model Retraining: Why & How to Retrain ML Models?
Only ~40% ML algorithms are deployed beyond the pilot stage. Such low rate of adoption can be explained with the lack of adaptation to new trends and developments such as economic circumstances, customer habits and unexpected disasters like Covid-19.
Multi Agent Systems: Applications & Comparison of Tools
Multi-agent systems(MAS) enable distinct AI agents to work together to achieve complex objectives. Every AI agent in the system possesses its specific characteristics and responsibilities that contribute to a greater goal. MAS provides a distinctive approach to managing multi-step tasks and enhancing efficiency.
Human Annotated Data
As the AI market grows (Figure 1), integrating AI solutions remains challenging due to time-consuming tasks like data collection and annotation. Many use automated annotation tools to streamline the tedious process of data annotation, but robust machine learning models still require human-in-the-loop approaches and human-annotated data.
Top 10 Conversational Commerce Use Cases
The goal of conversational commerce, a cutting-edge marketing and sales strategy, is to increase sales by boosting customer experience through interacting with them on messaging platforms. Conversational AI solutions such as sales chatbots and virtual assistants are used by conversational commerce enterprises to offer 24/7 client service and engagement.
Chatbot in South Africa (RSA): Top 10 Vendors
Businesses in South Africa can benefit from conversational AI. WhatsApp boasts a 96% monthly usage rate among South African internet users, and AI-related searches in Africa grew by 270% in the past year. Therefore, you should capitalize on your audience’s comfort level with conversational AI tools.
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