
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
AI Explained: Trends and Applications by Industry
Artificial Intelligence (AI) allows computers to learn from experience, adapt to new inputs and perform human-like tasks. Most of the AI examples you’ve heard about –from chess-playing machines to self-driving cars–rely heavily on deep learning, a subfield of AI.
Top RPA Tools / Vendors & Their Features
Based on our experience with RPA software during our RPA benchmark as well as external market presence metrics like number of reviews and employees, we selected the leading and emerging RPA providers.
AI eCommerce: 25 Use Cases to Optimize Sales and CX
AI is helping eCommerce businesses address key challenges like cart abandonment, inefficient customer support, and inventory mismanagement. AI eCommerce tools can reduce churn, optimize operations, and deliver personalized shopping experiences by analyzing customer behavior.. These capabilities not only enhance customer satisfaction but also drive sales growth in a competitive market.
Meta AI Applications and Research Examples
Rather than existing only in research labs, artificial intelligence now shapes the tools people use to connect, work, and create. Meta AI, formerly Facebook AI, drives this transformation by linking research in vision, language, audio, and robotics with applications that reach billions across its platforms.
Recommendation Systems: Applications and Examples
Recommendation systems benefit both businesses and customers by using data to personalize experiences. They help boost sales, increase customer loyalty, and reduce churn by simplifying choices and keeping users engaged. We’ve also created a benchmark of the top Python libraries for recommendation systems and included a step-by-step LightFM tutorial.
Top 25 Chatbot Case Studies & Success Stories
The global chatbot market currently stands at approximately $16 billion and is projected to reach $46 billion by 2029. Despite the hype around chatbots, stories of failure are common, while successes are rare. Therefore, designers of conversational interfaces must analyze these failures, as a few successes arise from many failures.
Top 40 Chatbot Applications with Examples
Chatbots have become essential tools that enhance customer interactions, operational efficiency, and user satisfaction across various industries. A recent survey found that 60% of U.S. consumers appreciate chatbots for their constant availability and time-saving abilities, while 45% value their immediate responses.
When Will AGI/Singularity Happen? 8,590 Predictions Analyzed
We analyzed 8,590 scientists’, leading entrepreneurs’, andthe community’s predictions for quick answers on Artificial General Intelligence (AGI) / singularity timeline: Explore key predictions on AGI from experts like Sam Altman and Demis Hassabis, insights from five major AI surveys on AGI timelines, and arguments for and against the feasibility of AGI: Artificial General Intelligence timeline
10+ Epic LLM/ Conversational AI/ Chatbot Failures
Effective chatbots are difficult to create because of the complexities of natural language. Many chatbots fail to engage users or perform basic tasks, resulting in widespread mockery. Due to the rapid advancement of AI, chatbots might eventually surpass human conversational skills. For now, let’s enjoy their funny failures.
Top 100 RPA Use Cases with Real Life Examples
RPA can automate repetitive tasks in the front and back offices. A use case-focused approach is critical to optimizing the value of technology investments. We identify 100 use cases and real-life examples of Robotic Process Automation, illustrating its application in automating repetitive tasks across various business, industry-specific, and personal contexts.
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