Cem Dilmegani
Cem has been the principal analyst at AIMultiple for almost a decade.
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, automation, cybersecurity (including network security, application security), data collection including web data collection and process intelligence.
Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and 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 (September 28, 2017). 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
Conference & other event presentations
- 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 (March 10, 2023): 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
Large Language Model Training
While using existing LLMs in enterprise workflows is table stakes, leading enterprises are building their custom models. However, building custom models can cost millions and require investing in an internal AI team.
5 Steps to OCR Training Data
The interest in optical character recognition (OCR) and intelligent character recognition (ICR) technology is falling as companies switch to more automated solutions, such as machine learning-enabled data extraction. However, due to its various benefits, many companies still use1 or plan to use tools powered by OCR technology in their paper-based operations.
7 Steps to Obtain Computer Vision Training Data
Computer vision (CV) technology is advancing rapidly in various industries. As demand for computer vision systems rises, so does the need for well-trained models. These models require large, high-quality, accurately labeled datasets, which can be costly and time-consuming to collect.
Top 10 Conversational AI Platforms
Enterprises need scalable conversational customization to affordably delight their customers and manage a high volume of queries. With over 200 conversational AI platforms available, choosing the right one can be challenging.
AI Chatbot Pricing: Chatbot Cost Comparison
Chatbots decrease customer support expenses while maintaining 24/7 availability, thus increasing revenues and customer saftisfaction. And with the rise of generative AI chatbots, like ChatGPT, more businesses could adopt chatbots. However, ambiguous chatbot pricing models can be a barrier to adoption.
Machine Learning in Test Automation: Benefits & Real Examples
Businesses aim to switch to automated testing because it provides faster and more efficient outcomes than manual testing. While test automation tools are valuable assets in achieving this, using Machine Learning (ML) in test automation tools enhances the QA experience considerably. The implementation of ML is gaining pace.
7 End-to-End Testing Best Practices
The end user determines the success of the apps, websites, and services that businesses offer. If the end product does not constantly fulfill the changing needs and expectations of the user, no matter how big the developer is, it will fall short.
Top 5 Chatbot Companies in India with Examples
India is a leading country for e-commerce chatbot usage, with a high demand for AI bots across various sectors. However, the abundance of Indian chatbot companies makes selecting the right vendor a challenge. To assist companies, we evaluated India’s top 5 chatbot companies and highlighted their best examples.
XR/AR in Manufacturing: 7 Use Cases with Examples
Extended reality (XR) technologies are increasingly adopted in manufacturing. Utilizing VR/AR technology in the manufacturing sector can provide a $360 billion boost to GDP by 2030. VR/AR solutions are still far from widespread adoption, and business leaders might be unaware of the use cases and benefits of implementing AR/VR in manufacturing operations.
Tech Industry Analysis: 7 Trends Managers Must Know
Technology industry is one of the world’s leading sectors. Each year, its share in global and regional GDPs is increasing. In this environment of advanced technologies and competition, it is important than ever to have a correct outlook of the sector. For this, tech industry analysis is a must for a successful technology sector leader.
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