
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 15 Use Cases of RPA in the Automotive Sector
Robotic Process Automation (RPA) streamlines repetitive tasks, freeing employees for strategic work. Widely adopted across industries like education, retail, and manufacturing, RPA is now making significant impacts in automotive. It enhances order management, logistics, production, and telematics, boosting efficiency and precision. See how RPA reshapes automotive workflows: Order processing 1.
Top 15 Computer Vision Use Cases with Examples
With the global computer vision market projected to reach US$30 billion in 2025 (see the graph below), business leaders face a critical challenge: identifying where it delivers ROI, from healthcare diagnostics to automated logistics.
10 Computer Vision Agriculture Use Cases & Examples
Labor shortages, resource inefficiencies, and environmental pressures increasingly challenge agriculture. Climate change adds to this burden through extreme weather, water scarcity, and rising pest threats, further straining productivity and sustainability. Computer vision offers targeted solutions by enabling automation and data-driven insights across critical farming operations.
Top 16 Use Cases of RPA in Education
RPA uses software robots to automate time-consuming, repetitive tasks, freeing employees from manual, mundane tasks and allowing them to focus on more strategic activities. Their benefit to us is a lower workload and higher process execution accuracy. These benefits make RPA particularly suitable for educational institutions.
Top 20+ MLOps Successful Case Studies & Use Cases
Organizations have started to adopt machine learning operations (MLOps) practices to standardize and streamline their ML development and operationalization processes. Interest in MLOps has risen over the years as it proves to be beneficial for business; however, implementing MLOps is a compelling task, and there is much to learn.
Workload Automation vs RPA: Differences to Know
Workload automation (WLA) and robotic process automation (RPA) are valuable technologies for businesses’ automation infrastructure. Both technologies reduce the number of manual tasks in an organization by automating repetitive processes. Both have benefits such as decreasing human error and cost, increasing efficiency, and creating transparency.
Top 10+ SAP Workload Automation Software & Use Cases
According to the SAP Corporate Fact Sheet, 99 of the top 100 organizations worldwide use SAP for enterprise resource planning (ERP). These customers account for 87% of the total global commerce. It is common for SAP users to use non-SAP systems in parallel for enterprise resource management.
Top 7 Computer Vision Challenges & Solutions
Computer vision (CV) technology is revolutionizing many industries, including healthcare, retail, automotive, etc. As more companies invest in computer vision solutions, the global market is expected to multiply 9 times by 2026 to $2.4 billion.
AI Center of Excellence (AI CoE): Meaning & Setup
The adoption of artificial intelligence (AI) is increasing as companies try to capture value from enterprise AI applications. However, according to an IBM survey, challenges such as limited AI expertise, increasing data complexity, and lack of tools for AI development hinder AI adoption for enterprises. To reduce AI project failures, organizations need a dedicated unit to oversee AI initiatives.
How to Scrape X.com (Twitter) with Python and Playwright
We used Python and Playwright to test Twitter (X) data collection methods focusing on most prominent pages: Twitter scraping methodology We have performed all tests without logging in. Our aim is to collect public data.
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