
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
Top 5 Low-Code Test Automation Tools
We selected the top low-code test automation tools based on their ability to simplify the testing process, their integrations with low-code platforms. We also considered their test documentation, management, and reporting capabilities. You can follow the links below to see our rationale. Low-code test automation tools are gaining prevalence.
10 GAN Use Cases
Generative AI is one of the latest famous technologies with the capability of realistic images, textual and auditory content in a matter of minutes. Gartner predicts that by 2025, 10% of all generated data will be produced by generative AI.
Image Classification: 6 Applications & 4 Best Practices
Around 1.72 trillion1 photos are taken every year. Many are used to train digital solutions, such as self-driving systems powered by image recognition and computer vision (CV) technologies.
Large Language Models: Complete Guide
Large language models (LLMs) have generated much hype in recent months (see Figure 1). The demand has led to the ongoing development of websites and solutions that leverage language models. ChatGPT set the record for the fastest-growing user base in January 2023, proving that language models are here to stay.
BI Governance: 6 Implementation Best Practices
The global business intelligence market is projected to be $33.3B by 2025, with more business units adopting BI tools. The importance of business intelligence is increasing. Data-driven decision making, for instance, is five times faster via data access and data analytics.
10+ Large Language Model Examples & Benchmark
We have used open-source benchmarks to compare top proprietary and open-source large language model (LLM) examples. You can choose your use case to find the right model for it. Comparison of the most popular large language models We have developed a model scoring system based on three key metrics: user preference, coding, and reliability.
Hands-on Review: Top 6 Online Survey Participant Recruitment Tools in 25′
Companies conduct online surveys to understand market trends and their target audience. However, finding the right survey participants can be both challenging and time-consuming. Survey participant recruitment tools help businesses to find appropriate participants.
UiPath Pricing: 4 RPA Pricing Models Explained
UiPath is the most popular RPA vendor; however, it has a complex RPA pricing model. We examined 10,000 different price combinations to help business and tech leaders understand UiPath’s pricing and get a high ROI RPA solution from their UiPath partnership.
UiPath vs IBM RPA: 14 Features Compared
A comparison of IBM RPA and UiPath will be conducted across 14 categories. To minimize biases and ensure a user-driven benchmarking of the features, the winner of each category will be determined by the RPA platform with the highest number of positive user reviews.
Data Encryption: Types, Importance & FAQ
Digital information is constantly being shared and stored on the cloud and connected services. According to IBM, the average cost for a data breach involving 50 million to 65 million records is more than $400 million.
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