
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
ChatGPT for Customer Service: Top 10 Use Cases
Generative AI tools have gained widespread popularity recently, and ChatGPT is among the most popular ones. As one of the large language models, its primary function is text generation, but it also offers other benefits, such as enhancing customer service experiences.
Top 20 ChatGPT in Marketing Use Cases
The share of artificial intelligence in the marketing industry is rapidly increasing (see Figure 1). However, the use of relatively new tools, such as generative AI and, in particular, ChatGPT in marketing is not widely known.
Top 32 ChatGPT Automation Use Cases
Over the last two decades, we’ve helped companies deploy advanced analytics, mainly for automation. The solutions then prevailing were robust in some contexts, but they were not able to respond to change. Since it is a GenAI tool, ChatGPT is flexible and can serve as an enterprise employee copilot.
7 Master Data Management Use Cases
In this article, we explain 7 master data management use cases. Master data management has been frequently searched since the 2020s.
Data Federation vs. Data Virtualization
In this article, we compare data federation and data virtualization. We provide insights when data federation should be chosen over data virtualization and vice versa.
Generative AI in Marketing: Benefits & Use Cases
The artificial intelligence market in marketing was valued at approximately 15.84 billion USD in 2021 and is projected to exceed 107.5 billion USD by 2028.This rapid growth reflects the increasing reliance on AI-driven solutions to address marketing challenges such as content scalability, personalization, and campaign optimization.
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.
7 Integration Testing Best Practices
Integration testing is one of the crucial stages of the software testing process. With the growing complexity of software systems, effective integration testing becomes more critical to identify issues before they cause significant problems. There are several best practices regarding integration testing, and it can be challenging to know where to begin.
Healthcare Data Encryption: Compliance & Real-Life Use Cases
Healthcare generates 30% of the world’s data, making it a prime target for cyberattacks. Over 40 million U.S. patient records are compromised yearly, often due to weak security measures. Data encryption has become a critical component of healthcare data security to mitigate the risk of data breaches.
10 User Acceptance Testing Best Practices & Challenges
User Acceptance Testing (UAT) is a critical stage in software development. End users test the program to ensure it satisfies their needs and functions as intended in a practical setting before the software release. Quality Assurance (QA) teams should be aware of the essential best practices to ensure user acceptance testing is carried out successfully.
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