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Cem Dilmegani

Cem Dilmegani

Principal Analyst
687 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, 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

Media, 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

DataSep 10

Insight Engines: Top 3 Real-Life Use Cases & 19 Tools ['26]

Enterprise search has been a game-changing technology in terms of increasing the productivity of organizations. Enterprise search engines combined with the power of a modern search engine with the company’s internal data.

AISep 10

10 Generative AI Supply Chain Use Cases in 2026

Artificial intelligence, particularly generative AI, presents new opportunities to address longstanding supply chain challenges. By analyzing large volumes of historical and real-time data, generative AI can produce actionable insights that improve decision-making, efficiency, and resilience. One notable example is Microsoft Dynamics 365 Copilot, an AI-driven assistant integrated into CRM and ERP systems.

Enterprise SoftwareSep 10

30 Intelligent Automation Case Studies / Success Stories

One of the most effective ways to understand how new technology can benefit your organization is through reading case studies of successful implementations.  For this purpose, we have aggregated case studies about intelligent automation from numerous sources. You can filter or sort them by industry (e.g.

Enterprise SoftwareSep 10

Top 25 Use Cases / Examples of Intelligent Automation ['26]

Traditional automation approaches can be effective in simple tasks but they often rely on rigid, pre-defined rules and are limited in their ability to adapt to changing circumstances. This can lead to inefficiencies and errors, especially when dealing with complex tasks or data.

Enterprise SoftwareSep 10

Pros & Cons of Top 6 RPA Alternatives to Consider in 2026

Robotic Process Automation (RPA) is a beneficial technology that can automate up to 70-80% of rules-based processes. However, ~40% of companies fail to reach their expectations of cost reduction after RPA implementation.

AISep 9

Top 20+ Agentic RAG  Frameworks in 2026

Agentic RAG enhances traditional RAG by boosting LLM performance and enabling greater specialization. We conducted a benchmark to assess its performance on routing between multiple databases and generating queries. Explore agentic RAG frameworks and libraries, key differences from standard RAG, benefits, and challenges to unlock their full potential.

Enterprise SoftwareSep 8

Top 7 Meter-to-Cash Solutions: A Comprehensive Guide

In the utilities sector, the meter-to-cash process is essential for revenue generation and efficient operations. It involves numerous intricate steps and systems. Meter-to-cash solutions have emerged as an indispensable tool for utility providers.  Selecting the right vendor for meter-to-cash solutions can be difficult since there is little information about them.

Enterprise SoftwareSep 8

Top 10+ SAP Workload Automation Software & Use Cases

According to the SAP Corporate Fact Sheet, 99 of the top 100 organizations worldwide use SAP for enterprise resource planning (ERP). These customers account for 87% of the total global commerce. It is common for SAP users to use non-SAP systems in parallel for enterprise resource management.

AISep 5

Hospitality Chatbots: Top Use Cases and Case Studies ['26]

According to PwC, the hospitality industry can charge the second-highest premium for excellent customer experience, with a 14% margin. Fast and easy-to-engage digital channels are part of the excellent customer experience. Engaging with many customers 7/24 via live agents is not an efficient strategy for the hotels.

AISep 5

Top 6 Use Cases of Generative AI in Banking in 2026

Gartner identified generative AI as a top technology trend for the banking and investment industry in recent years. Generative AI’s contributions to data privacy, fraud detection, and risk management can be critical to financial services companies. Key use cases include fraud detection, customer service automation, credit risk assessment, and document processing.