Cem Dilmegani
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, agentic AI, cybersecurity (including network security, application security) and data including web data.Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and the 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, 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.
Media, conference & other event presentations
- Answers to Korea24's questions on job loss due to AI, Korea24
- 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: 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
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.
Data Labeling for NLP with Real-life Examples
NLP technology is increasingly being used to enable smart communication between people and their devices. Companies like Google, Amazon, and OpenAI have invested billions in NLP technologies that can understand, interpret, and generate human language with remarkable accuracy. However, behind every sophisticated NLP model lies an important foundation: labeled training data.
Ethical & Compliant Web Data Benchmark
As enterprises scale their web data operations, compliance, data, and risk executives increasingly evaluate the associated ethical, reputational, and legal risks. We benchmarked 5 leading web data collection services across 3 dimensions and tested each service with more than 20 potentially unethical scenarios.
Data Loss Prevention (DLP): Types & 5 Challenges
The increased mobility introduces risks of data loss or theft, which can lead to severe financial losses and reputational damage for companies. Effective Data loss prevention (DLP) software needs to prevent the unauthorized movement of private data and personally identifiable information (PII) to limit reputational and financial risk.
6 Web Scraping Challenges & Practical Solutions
Web scraping, the process of extracting required data from web sources, is an essential tool; however, it is a technique fraught with challenges. See below the most common web scraping challenges and practical solutions to address them.
Responsible AI: 4 Principles & Best Practices
AI and machine learning are revolutionizing industries, with 90% of commercial apps expected to use AI by 2025 as AI statistics shows. Despite this, 65% of risk leaders feel unprepared to manage AI-related risks effectively.
Compare Top 7 Generative AI Services & Vendors
Since OpenAI launched ChatGPT, generative AI technology has rapidly expanded across industries. This spread led businesses to utilize various services to build and implement generative AI tools effectively. Here, we explore seven types of generative AI services that help businesses gain a competitive edge: Table 1.
In-depth Guide to Knowledge Graph: Use Cases
Your organization has data everywhere: customer databases, financial systems, HR records, project files, and emails. But when you need to answer “Which customers bought Product X and also had support tickets last month?” you’re stuck searching multiple systems, copying data to Excel, and hoping you didn’t miss anything. This data chaos costs companies millions.
How to Implement Proxy Scraping Services
Websites track the IP address of every incoming request, and a high volume of traffic from a single IP is the signal of an automated bot. The solution is a proxy. A proxy server is an intermediary that stands between your scraper and the target website, forwarding your requests while masking your real IP address.
5 Reasons for Data Warehouse Automation
The drive for data-driven business decisions, the exponential increase in business data, diversifying data sources and inflexible legacy data warehousing approaches left enterprises relying on a myriad of data marts, enterprise data warehouses and multiple data management tools. This led to complex data warehouse processes.
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