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 enterprise AI and software.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
- Hosted on American Variety Radio, answering Court Lewis' questions on AGI on April 25th, 2026.
- Answered Korea24's questions on job loss due to AI on November 5th, 2025. Recording available on: 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
Enterprise Generative AI: 11 Use Cases & Best Practices
Generative AI (GenAI) presents novel opportunities for enterprises compared to middle-market companies or startups, including: Enterprise generative AI use cases. The opportunity to build your company’s models without exposing private data to 3rd parties. However, generative AI brings challenges unique to large organizations. For example: 36% of enterprises cite concerns about proprietary data exposure when…
Top 15 Edge AI Chip Makers with Use Cases
The demand for low-latency processing has driven innovation in edge AI chips. These processors are designed to perform AI computations locally on devices rather than relying on cloud-based solutions. Based on our experience analyzing AI chip makers, we identified the leading solutions for robotics, industrial IoT, and embedded systems. SolutionPerformance (TOPS)*Power ConsumptionPrimary Applications NVIDIA Jetson…
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. We have collected essential information about Google Dialogflow and compared it to its main…
eCommerce Technologies Use Cases & Examples
The eCommerce sector continues to expand by ~10% each year as more consumers shift their purchasing habits online and seek faster and more convenient digital experiences.50This growth is also accompanied by increasing competition, making it essential for businesses to understand how technology is shaping customer expectations. As these expectations evolve, organizations need to stay informed…
AI Deep Research: Claude vs ChatGPT vs Grok
AI deep research offers users a wider range of search results than AI search engines. To see performance across different AI deep research tools, we are introducing three new benchmarks: DR-50 (Deep Research 50) Bench, which evaluates tools across 50 questions spanning six question types, DR-2T (Deep Research 2 Task) Bench, which assesses tools through…
Top 13 Use Cases of Generative AI in Education
According to the OECD Digital Education Outlook, 57% of lower secondary teachers state that AI helps them create or improve lesson plans.73Used with a clear teaching purpose, generative AI technologies can improve learning and support skills such as critical thinking, creativity, and collaboration. Explore the top 13 use cases to learn how generative AI can…
Top 5 AI Network Monitoring Use Cases and Real Life Examples
Network downtime costs enterprises an average of $5,600 per minute, yet traditional monitoring tools generate so many alerts that engineers miss the ones that matter.86 AI-driven monitoring addresses this by correlating data across the full network stack and surfacing root causes rather than symptoms. Below are five real-world deployments that show what AI monitoring looks…
Top 8 Observability Software with Pricing Including Solarwinds
Observability platforms promise complete visibility across distributed systems, but selecting the right one is hard when every vendor claims they do everything. We analyzed the top 8 observability software products by reviewing their documented capabilities, public pricing, verified customer reviews, and enterprise reference cases. Datadog leads the observability market with roughly 40-44% search share over…
A-CODE-LLM Bench: Agentic Coding Benchmark
We benchmarked the top Large Language Models (LLMs) across 10 software development tasks using an agentic CLI tool. We executed ~3,500 automated validation steps per model across both API and UI layers. A-CODE-LLM Bench results Each alias ran 3 times across 10 tasks (30 samples per alias, 290 cells per iteration). See more details on…
Cloud LLM vs Local LLMs: Examples & Benefits
Cloud LLMs, powered by advanced models like GPT-5.5 and Claude Opus 4.7, offer scalability and accessibility. Conversely, Local LLMs, driven by open-source models such as Llama 4, DeepSeek V4, and Qwen3.6-Plus, ensure stronger privacy and customization. Explore what are cloud LLMs, strengths and weaknesses, most common case studies with real-life examples, and how they differ…
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