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
CRM AI Systems: Top 5 Vendors and Key Features
AI-powered CRM systems leverage machine learning, natural language processing (NLP), and data analytics to enhance the capabilities of traditional CRM. The adoption of AI in CRM is driven by the need for more personalized customer experiences and efficient data management.
Synthetic Data Generation Benchmark & Best Practices
We benchmarked 7 publicly available synthetic data generators sourced from 4 distinct providers, utilizing a holdout dataset comprising 70,000 samples, with 4 numerical and 7 categorical features, to evaluate their performance in replicating real-world data characteristics. Below, you can see the benchmark results where we statistically compare the synthetic data generators.
Top 30 Affective Computing Applications: Emotion AI Use Cases
Thanks to affective computing, also known as emotion AI, computers start to recognize human emotions based on facial expressions, body language, or voice tone. Technology’s applications in different industries are expanded by significant investment in technology where some managers lack knowledge.
Top 15 Logistics AI Use Cases & Examples
Persistent inefficiencies, rising operational costs, and ongoing supply chain disruptions continue to challenge logistics functions globally. In response, organizations are increasingly turning to artificial intelligence to improve resilience, optimize operations, and achieve measurable gains across inventory, transportation, and procurement.
Quantum Artificial Intelligence
Quantum computing and artificial intelligence are both transformational technologies and artificial intelligence are likely to require quantum computing to achieve significant progress. Although artificial intelligence produces functional applications with classical computers, it is limited by the computational capabilities of classical computers.
Banking Chatbots: 7 Tools, 4 Use Cases & 5 Practices
Industries where customer service is a top priority face increasing costs due to the demand for excellent customer service. Banking chatbots allow customers to complete transactions using either voice or text, reducing operational costs while enhancing customer satisfaction.
Celonis Process Mining: Products, Features & Competitors
Celonis claims to be the process mining market leader with 60% market share. Its popularity has been increasing over the last 5 years (See Figure 1). However, recent acquisitions from tech giants, such as Myinvenio by IBM and Minit by Microsoft, have created formidable competitors.
Top 10 SEO AI Use Cases with Case Studies
Competing for visibility in search results has become increasingly difficult as algorithms evolve and user expectations rise. Traditional SEO methods, reliant on manual research and incremental updates, often fail to keep pace with these changes. AI-powered SEO tools address this challenge by automating complex tasks and aligning content more precisely with user intent.
55 Process Improvement Case Studies & Project Results
Business leaders know that process improvement reduces costs and increases customer satisfaction. Yet, it can be difficult for process experts and business analysts to understand the different process improvement approaches and process analysis tools. Explore typical process improvement project results, case studies and benchmarks to set targets for your improvement initiatives.
Top companies in AI-powered medical imaging
Around 75% of all medical malpractice claims against radiologists are related to diagnostic errors. Many radiology errors can be traced back to breakdowns in communication during the imaging or reporting process. AI algorithms can be trained to analyze medical images and identify patterns and abnormalities that may be missed by human eyes.
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