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
Sentiment Analysis Machine Learning: Approaches & 5 Examples
It is not surprising that the use of AI in the workplace has increased by 270% from 2015 to 2019, considering the data available and its exponential growth.
Quantum Annealing: Practical Quantum Computing
Quantum annealing is a promising quantum technology for companies that have urgent optimization problems which take too long for traditional computers to solve. It can be used to solve optimization problems more effectively than traditional computers. However, it is still mostly used in academia and more R&D is required to build commercial quantum annealers.
Top 20 Manufacturing Analytics Case Studies
High maintenance costs, unexpected downtimes, and inefficient processes continue to challenge manufacturers. To stay competitive, companies are leveraging manufacturing analytics to optimize operations and enhance asset performance. Explore the top 20 real-world case studies where manufacturers used analytics insights to cut costs, reduce unplanned downtime, and boost productivity.
Layers & Components of IoT Architecture
Though businesses are investing in IoT, buyers may not be clear about all the components that they need to invest in.
What is Homomorphic Encryption? Benefits & Challenges
The increasing usage of cloud services and collaboration between companies to monetize data raises concerns over data privacy. Regulations such as the General Data Protection Regulations (GDPR) aim to protect consumers’ privacy, and businesses pay serious fines in case of non-compliance. This creates a tradeoff between data privacy and utility for companies.
State of OCR: Is it dead or a solved problem?
Optical Character Recognition (OCR) is one of the earliest areas of artificial intelligence research. Today OCR is a relatively mature technology and it is not even called AI anymore which is a good example of Pulitzer Prize winner Douglas Hofstadter’s quote: AI is whatever hasn’t been done yet.
Machine Learning Accuracy: True-False Positive/Negative
Selecting the right metric to evaluate your machine learning classification model is crucial for business success. While accuracy, precision, recall, and AUC-ROC are common measurements, each reveals different aspects of model performance. We’ve analyzed these metrics to help you choose the most appropriate one for your specific use case, ensuring your models deliver real value.
20 Chatbot Companies To Deploy
Enterprises need scalable conversational AI to delight customers and manage high query volumes. With over 200 chatbot companies, choosing can be challenging. Businesses should focus on key features to find suitable solutions, including integrations with their tech stack, integrations with customer platforms, and customization options for communication.
eCommerce Data Collection: Best Practices & Examples
As online shopping grows and customer expectations shift, eCommerce businesses face increasing pressure to stay competitive. Real-world data is key to making faster, smarter decisions. Failing to collect and utilize data properly can result in missed sales, inefficient operations, and poor customer retention.
Top 5 SAP Conversational AI (Joule) Use Cases
As of January 2023, SAP Conversational AI, the chatbot-building platform, has been discontinued and is now in maintenance mode. There is no direct replacement, as SAP has refocused on more advanced AI features; however, current enterprise clients can continue using it until their contracts expire.
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