
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 10+ External Attack Surface Management (EASM) Tools
Several attack surface management (ASM) and external attack surface management (EASM) tools have emerged recently. In this article, I picked the best 10+ platforms based on their asset discovery level and attack surface management capabilities. Here are my key takeaways: Asset discovery level See the explanation for asset discovery methods.
Top 5 E-commerce AI Agents: A Hands-On Review
I selected the best AI agents for e-commerce. In this review, I will highlight their real-world applications across multiple e-commerce workflows from content creation and SEO to product data management, campaign automation and operations management.
Top 9 AI Agents in Accounting
Tools like Dext, AutoEntry, and Hubdoc have automated data extraction and transaction posting. But these systems are fundamentally still rule-based, often requiring accountants to jump between spreadsheets.
Workload Automation Security: Best Practices & Examples
Businesses must secure workload automation at every level. The following sections outline key risks, best practices for securing automation environments, and real-world examples that highlight the importance of robust security.
Top AI Note Takers Tested: Motion, Fellow, Otter, and TL;DV
We tested each AI note taker to evaluate their accuracy and features during real world meetings. Follow the links to view our detailed reviews: AI note taker benchmark results Methodology for evaluating AI note taking tools: We tested AI note takers during a strategy session focused on improving sales in the rural market. 1.
Claims Processing with Autonomous Agents
We’ll use Stack AI workflow builder for claims automation and create an AI agent to enable users to upload accounting documents like claim forms and automatically convert them into structured JSON using OCR and GPT-based processing. The extracted data can then be sent to a Google Sheet or used in custom apps and databases.
Top No-Code ML Platforms: ChatGPT Alternatives
We benchmarked 4 no-code machine learning platforms across key metrics: data processing (handling missing values, outliers), model setup and ease of use, accuracy metrics output, availability of visualizations, and any major limitations or notes observed during testing.
Agentic AI n8n Tutorial
We built an AI agent within n8n designed to provide investment advice, showcasing the platform’s capabilities for agentic AI. This process involved configuring the agent to perform technical and fundamental stock analysis by integrating 5 distinct tools and pulling financial data from various APIs.
Text-to-SQL: Comparison of LLM Accuracy
I have been relying on SQL for data analysis for 18 years, beginning with my days as a consultant. Translating natural-language questions into SQL makes data more accessible, allowing anyone, even those without technical skills, to work directly with databases.
10+ Agentic AI Trends and Examples
The future of agentic AI isn’t just about improving tools or streamlining business workflows. It’s about integrating AI deeply and transforming business approaches by restructuring current frameworks. Key takeaways: 10+ agentic AI trends and examples 1.
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