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Cem Dilmegani

Cem Dilmegani

Principal Analyst
288 Articles
Stay up-to-date on B2B Tech
Cem has been the principal analyst at AIMultiple since 2017.

Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, and Washington Post, global firms like Deloitte and 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 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

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

Enterprise Software
Insight
Sep 2

Blockchain Case Studies Across Key Industries

We collected the top 20 real-world blockchain case studies to help executives identify mature and high-impact investment opportunities. Business challenge: The pharmaceutical supply chain needed to comply with the U.S. Drug Supply Chain Security Act, which requires interoperable tracking of prescription drugs through changes of ownership. The industry also faced risks from counterfeit drugs, fragmented…

AI
Insight
Sep 2

No-Code AI: Benefits, Industries & Key Differences

No-code AI tools allow users to build, train, or deploy AI applications without writing code. These platforms typically rely on drag-and-drop interfaces, natural language prompts, guided setup wizards, or visual workflow builders. This approach lowers the barrier to entry and makes AI development accessible to users without a programming background. Recently, no-code AI has expanded…

Enterprise Software
Feature Comparison
Sep 2

Top 6 SAP Job Scheduler Alternatives

We selected the SAP job scheduler alternatives based on the features, pricing, and market presence metrics of leading solutions. Follow the links below for these tools’ benefits and case studies: Explore top SAP job scheduler alternatives considering their unique features and advantages against SAP’s offering: Note that tools are listed basted on their B2B user…

AI
Insight
Sep 2

Top 20+ Predictions from Experts on AI Job Loss

As a McKinsey consultant, I helped enterprises adopt new technologies for a decade. My quick answers: Note: The size of the plots is correlated with the size of the job loss prediction. The percentages referenced in our analysis are derived from assumptions about overall job displacement. In specific scenarios, these assumptions included potential job gains…

AI
Feature Comparison
Sep 2

AI Video Pricing: Compare Synthesia & Invideo AI

AI video pricing can differ significantly across platforms, influenced by factors such as output quality, customization options, and features. As more businesses and creators turn to AI for efficient video production, understanding these pricing models becomes essential. Dive in for a detailed comparison of the top AI video tools, highlighting what each service provides at…

AI
Insight
Sep 1

Top 125 Generative AI Applications

Based on our analysis of 30+ case studies and 10 benchmarks, where we tested and compared over 40 products, we identified 125 generative AI use cases across the following categories: For other applications of AI for requests where there is a single correct answer (e.g., prediction or classification), check out AI applications. You can also…

AI
Insight
Sep 1

10 Risks of Generative AI & How to Mitigate Them

With industries prioritizing generative AI for innovation and automation, its potential grows. However, risks of generative AI like accuracy and ethical concerns remain. Addressing these challenges is key to ensuring AI benefits humanity. Explore the top 10 risks of generative AI and steps to mitigate them: Generative AI tools like ChatGPT rely on large language…

AI
Insight
Sep 1

LLM Fine-Tuning Guide for Enterprises

Follow the links for the specific solutions to your LLM output challenges. If your LLM: The widespread adoption of large language models (LLMs) has improved our ability to process human language. However, their generic training often results in suboptimal performance for specific tasks. To overcome this limitation, fine-tuning methods are employed to tailor LLMs to…

AI
Insight
Sep 1

Generative AI Ethics: How to Manage Them

Generative AI raises important concerns about how knowledge is shared and trusted. Britannica, for instance, filed a lawsuit against Perplexity, alleging that the company illegally and knowingly copied Britannica’s human-verified content and misused its trademarks without permission.153 Explore what generative AI ethics concerns are and best practices for managing them. AI models learn patterns from…

AI
Insight
Sep 1

10+ Large Language Model Examples

We have gathered open-source benchmarks to compare leading proprietary and open-source large language models. Choose your use case to find the right model. You can evaluate large language models by examining their benchmark performance and real-world latency (available by clicking each model’s name in the table), and by reviewing their pricing to assess overall efficiency…

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