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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

AIJul 21

Cryptocurrency Sentiment Analysis: Statistics & How It Works

The cryptocurrency market has grown up to more than $2.5 trillion in 2024. However, investing in cryptocurrency can be risky as there can be extreme fluctuations in the market.

Enterprise SoftwareJul 21

RPA Developer: Everything You Need to Know in 2026

Although plenty of resources online about RPA skills and training exist, job seekers still struggle to understand where to start. We’ve compiled the most comprehensive resource on RPA developer skills, salary, and jobs to help job seekers explore where to start and what they need to do to excel as an RPA developer.

Enterprise SoftwareJul 21

ERP Pricing in 2026: 5 Vendors, 5 Models & 6 Factors

ERPs are popular for providing end-to-end solutions, with the ERP market projected to reach ~$52bn in 2024. However, 47% of organizations faced cost overruns in their ERP implementations in 2023, often due to unclear pricing This article explores ERP pricing models, factors influencing costs, and the pricing structures of 5 vendors.

Enterprise SoftwareJul 20

5 Unsuitable Processes for RPA in 2026

RPA adoption is rapidly increasing in businesses from different sectors. From banking to automotive, RPA’s potential to automate error-prone, repetitive, and time-consuming tasks can save companies time, money, and human resources that can be spent better elsewhere.

AIJul 19

LLM Data Guide & 6 Methods of Collection in 2026

In the expanding AI and generative AI market (Figure 1), large language models (LLMs) have emerged as pivotal. These models empower machines to generate human-like content, heavily reliant on quality data. Here, we present a guide for business leaders on accessing and managing LLM data, offering insights into collection methods and data collection services.

DataJul 19

Top 4 Field Agent Competitors & Alternatives in 2026

Monitoring retailers across different countries can pose a challenge for manufacturers of CPGs (consumer packaged goods) and FMCGs. Planogram audit services or retail audit companies offer solutions to help overcome these challenges. Field Agent is a service provider specializing in retail monitoring services for consumer packaged goods (CPG) producers.

AIJul 18

XRay AI: Definition, Use Cases & Examples in 2026

The integration of artificial intelligence (AI) to radiology is not a futuristic vision; it’s already redefining clinical workflows, particularly in X-ray imaging. AI tools are now embedded into imaging systems, enabling real-time decision support and improving workflow efficiency, image quality, and clinical accuracy.

AIJul 18

Top 6 Radiology AI Use Cases for Improved Diagnostics

Radiology teams are under pressure from growing scan volumes, staff burnout, and the risk of diagnostic mistakes. These challenges are making it harder to deliver timely and accurate care. AI is helping to ease the burden by accelerating image analysis, minimizing errors, and facilitating more informed decisions.

AIJul 18

Therapist Chatbots: Top Use Cases & Challenges in 2026

The World Health Organization (WHO) reports that one in eight people globally suffers from a mental disorder, impacting about 970 million individuals. Furthermore, approximately 70% of those with mental health issues do not receive treatment across the globe. Therapist chatbots can help close the mental health treatment gap and contribute to a happier society.

AIJul 17

AI in Healthcare: Challenges & Best Practices in 2026

Although AI holds great promise for advancing healthcare systems, its real-world impact has often fallen short of expectations. For instance, less than 1% of AI tools developed during the COVID-19 pandemic were successfully deployed in clinical settings.