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
Linux Job Scheduler: Review, Guide & Alternatives
Linux job scheduler and ‘cron,’ a time-based job scheduler, are commonly used in Linux job scheduling. If you: * Linux Completely Fair Scheduler (CFS) ** Enterprise job schedulers include Stonebranch, ActiveBatch, RunMyJobs & JAMS Scheduler.
Enterprise Generative AI: 11 Use Cases & Best Practices
Generative AI (GenAI) presents novel opportunities for enterprises compared to middle-market companies or startups, including: However, generative AI brings challenges unique to large organizations. For example: Explore our practical enterprise AI use cases to learn how large companies can build, deploy, and govern their own generative AI models effectively.
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.
Top 10 Enterprise Job Scheduler Software
AIMultiple vetted top job scheduling software based on the features, pricing, and market presence. Follow the links below to see our rationale for each selection: Enterprise job scheduling software market leaders **Score is based on B2B review platforms.
Top 12 Alternatives to Windows Task Scheduler in 2026
Windows Task Scheduler, like open-source job schedulers, has no license costs. However, our review found that Task Scheduler’s Windows focus and limited scheduling capabilities may be not sufficient for complex IT scenarios and hybrid cloud requirements of enterprises. Users seeking alternatives to Task Scheduler typically fall into three categories.
Compare Top 5 Stonebranch Alternatives
Stonebranch is a SaaS workload automation solution with a wide range of community-driven pre-packaged integrations. However, Stonebranch alternatives may suit specific users. See our rationale for selecting each tool by following the links below: ~30 WLA tools exist in the workload automation software landscape.
Top 10 ERP AI Use Cases & Case Studies
Enterprise resource planning (ERP) systems help organizations manage core business processes such as finance, operations, and human resources within a single platform. As business processes grow more complex and data-driven, companies are increasingly integrating AI capabilities, such as machine learning and conversational AI, into ERP systems to automate tasks, improve decision-making, and increase efficiency.
Top 8 Agentic CRM Platforms in 2026
Customer relationship management tools are getting smarter. Instead of just storing data, agentic CRM platforms can plan tasks, execute workflows, and adjust strategies autonomously. Think of them as CRM systems with built-in intelligence that actually do the work instead of waiting for you to click buttons.
Generative AI in Fashion: Top 13 Use Cases & Examples
89% of all companies across different sectors are switching to digital technologies, and the generative AI in the fashion industry is not an exception. McKinsey reports that fashion brands and companies invested approximately 2% of their income in emerging technologies. Moreover, they estimate the figure will rise to 3.5% by 2030.
Compare Google Dialogflow and Its Competitors
Tech giants such as Google, IBM, Microsoft, Amazon, and Facebook are investing in conversational AI to enable developers to build chatbots easily. These AI-powered chatbots can automate various routine tasks such as sending emails, searching for information on search engines, etc.
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