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Cem Dilmegani

Cem Dilmegani

Principal Analyst
724 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

AIOct 31

Top 40 Chatbot Applications with Examples

Most companies use chatbots wrong. They slap a bot on their website, watch it frustrate customers, then wonder why adoption stays low. The reality: chatbots work brilliantly for specific tasks and fail miserably at others. A recent survey found 60% of U.S. consumers appreciate 24/7 availability, while 45% just want faster answers.

CybersecurityOct 31

IT Asset Management (ITAM) Pricing Comparison

Finding the right IT Asset Management (ITAM) solution is key to controlling costs, reducing risks, and gaining full visibility into your IT infrastructure. Designed for IT managers, procurement teams, and SMEs, this comparison highlights how different pricing models and feature sets align with varying business needs.

Agentic AIOct 31

Top 8 Agentic CRM Platforms

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.

AIOct 31

Cloud GPUs for Deep Learning: Availability& Price / Performance

If you are flexible about the GPU model, identify the most cost-effective cloud GPU based on our benchmark of 10 GPU models in image and text generation & finetuning scenarios. If you prefer a specific model (e.g. A100), identify the lowest-cost GPU cloud provider offering it.

DataOct 31

Top 5+ Geonode Alternatives: Pricing & Features

Proxy services are essential for companies to use technologies such as web scraping, ad verification, and market research. We reviewed Geonode and its top competitors including Bright Data, Webshare, Oxylabs, Decodo, SOAX, and IPRoyal.

CybersecurityOct 31

Top 20+ Network Security Audit Tools

Network security audit tools provide real-time insights into a network’s security by scanning tools across the environment and alerting administrators to emerging threats, vulnerabilities, or new patches. Given the broad scope of their functions, these tools vary significantly.

CybersecurityOct 30

Top 10+ RMM Software with Pricing & Features

Based on our RMM benchmark, user reviews & feature comparisons, here are the top RMM software. See why we selected them by following the links below: RMM software components help keep networks secure and efficient, thanks to features like patch management.

AIOct 28

GPT-5: Best Features, Pricing & Accessibility

We now have GPT-5, the latest and one of the most advanced language models. GPT-4 vs. GPT-5 The interactive comparison below shows how GPT-5 differs from GPT-4 across architecture, performance, and pricing. Historical Progression Release & Architecture What’s Different in GPT-5 Multiple Models, One System GPT-4 ran every prompt through the same model.

AIOct 28

Custom AI: When to Build Your Own Solutions

While ready-made AI tools can meet many business needs, they often fall short in areas that require deep data understanding or specialized workflows. Organizations working in complex or niche industries may find that generic systems don’t fully align with their operations or leverage their proprietary data.

AIOct 28

10 Steps to Developing AI Systems

IBM identifies the top AI adoption challenges as concerns over data bias (45%), lack of proprietary data (42%), insufficient generative AI expertise (42%), unclear business value (42%), and data privacy risks (40%).These obstacles can hinder AI implementation, slow innovation, and reduce the return on investment for organizations adopting AI technologies.