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Cem Dilmegani

Cem Dilmegani

Principal Analyst
706 Articles
Stay up-to-date on B2B Tech

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

Conference & other event presentations

Sources

  1. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
  2. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
  3. Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
  4. Science, Research and Innovation Performance of the EU, European Commission.
  5. EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
  6. Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
  7. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

Latest Articles from Cem

Enterprise SoftwareSep 30

eCommerce Technologies Use Cases & Examples

A few tech and retail giants dominate the eCommerce sector, which is growing at ~10%/year.To compete, smaller businesses should invest in tech to lower costs and increase customer satisfaction, and boost profitability.

DataJun 13

Reproducible AI: Why it Matters & How to Improve it

Reproducibility is a fundamental aspect of scientific methods, enabling researchers to replicate an experiment or study and achieve consistent results using the same methodology. This principle is equally vital in artificial intelligence (AI) and machine learning (ML) applications, where the ability to reproduce outcomes ensures the reliability and robustness of models and findings.

Enterprise SoftwareSep 8

APIs in the Telecom Industry: Benefits, Technologies & Examples

Service quality and price are the top factors influencing telecom customers.. Telecom companies started to embrace new technologies and digital transformation to be able to provide high-quality services and reduce costs. APIs are the cornerstone technology that can benefit the telecommunications sector by making it more innovative and efficient.

AIJul 21

Cryptocurrency Sentiment Analysis: Statistics & How It Works

The cryptocurrency market has grown up to more than $2.5 trillion in 2024. However, investing in cryptocurrency can be risky as there can be extreme fluctuations in the market.

AIJun 11

Top 10 Conversational Commerce Use Cases

The goal of conversational commerce, a cutting-edge marketing and sales strategy, is to increase sales by boosting customer experience through interacting with them on messaging platforms.  Conversational AI solutions such as sales chatbots and virtual assistants are used by conversational commerce enterprises to offer 24/7 client service and engagement.

DataJul 22

Sentiment Analysis Datasets

Sentiment analysis is a great way to understand the customers’ feelings toward a company and to see if they are associated with sales, investments, or agreements. Ensuring a reliable sentiment analysis depends on many factors, and one of its building blocks is the dataset used to train the models.

DataSep 26

Best Data Collection Services & Companies

AIMultiple collects data on hundreds of thousands of B2B vendors from the web and surveys. Based on our experience, if you are looking for data to Top 12 AI data collection services Despite the efficiency of web data collection and synthetic data generation, human-generated data remains essential for AI development.

Enterprise SoftwareApr 7

Top 3 NFT Marketplaces on the Stacks Blockchain 

Even though the NFT hype has cooled down in recent months, we anticipate that NFTs will continue to be relevant because of their applications in both the virtual and physical worlds.  NFT blockchains have experienced difficulties such as volatile transaction fees and security issues.

Enterprise SoftwareJul 4

Top 14 Use Cases of SAP Intelligent RPA

With ~ €31b revenue, SAP is one of the largest and oldest ERP vendors. With the rise of Robotic Process Automation (RPA) to automate routine, time-consuming, and menial tasks, users might wonder how RPA can automate business workflows in SAP. However, SAP touches almost every critical aspect of a business.

AISep 10

Top 5 Facial Recognition Challenges & Solutions

Facial recognition technology has rapidly integrated into daily life, powering applications ranging from access control systems to law enforcement investigations. Yet its widespread adoption has also exposed a range of technical, ethical, and societal challenges. Discover the top 5 facial recognition challenges and solutions to prevent fraud and misuse. 1.