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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

Enterprise SoftwareJun 18

Workload Automation vs RPA: Differences to Know in 2026

Workload automation (WLA) and robotic process automation (RPA) are valuable technologies for businesses’ automation infrastructure. Both technologies reduce the number of manual tasks in an organization by automating repetitive processes. Both have benefits such as decreasing human error and cost, increasing efficiency, and creating transparency.

Enterprise SoftwareJun 18

RPA Accounting: 6 Processes & Real-Life Examples in 2026

During my 2 decades of experience helping enterprises adopt automation & AI, accounting and other financial processes were a focus area for me due to their rules-based nature.

DataJun 18

10-Point Retail Audit Checklist with Case Studies in 2026

Retail audits are essential for consumer product goods (CPG) or fast-moving consumer goods (FMCG) companies to ensure success at their retail end. While some brands use retail and planogram audit services, others handle these audits internally. This article presents a 10-point checklist to help CPG brands in executing comprehensive retail audits.

Enterprise SoftwareJun 17

Top 10 Use Cases of IoT Manufacturing in 2026

The market for IoT manufacturing is expected to be valued $400B by 2026. The ability to collect and analyze accurate data from connected IoT devices and sensors in real-time provides manufacturers with unprecedented insights into their industrial processes.

DataJun 16

10 Open Source Data Labeling Platforms in 2026

Data labeling, the process of annotating raw data (such as images, text, or audio), is essential for training ML models to perform tasks like classification and recognition. While pre-built solutions exist, they may not always meet specific needs, making open-source platforms a more flexible and customizable alternative. See the top 10 open-source data labeling tools.

Enterprise SoftwareJun 16

12 Digital Transformation Trends & Use Cases in Education

The COVID-19 pandemic has accelerated digital transformation in education as nearly 1.5 billion students worldwide became distanced from their classrooms. However, online education is not the only way digital technologies transform the teaching and learning experience. We explore how digital transformation affects education with key technologies and trends.

CybersecurityJun 16

Top 10 Open Source Network Security Software in 2026

Network security statistics show that data breaches impacted ~350 million people in the U.S. Open source network security software can prevent unauthorized access to network services and identify the most common cyber attack vectors. These software continuously monitor a network for malicious activity and take action to prevent it.

DataJun 16

Traditional vs. Online Survey Research in 2026

Conducting survey research helps businesses collect data from customers, employees, or the public. Collecting data with traditional methods, such as paper-pencil or telephone, is costly, time-consuming, and cannot keep up with the digitally transforming world. Thanks to online survey research tools, businesses can quickly reach a broad audience’s opinion and make necessary adjustments.

DataJun 16

Top companies in AI-powered medical imaging in 2026

Around 75% of all medical malpractice claims against radiologists are related to diagnostic errors. Many radiology errors can be traced back to breakdowns in communication during the imaging or reporting process. AI algorithms can be trained to analyze medical images and identify patterns and abnormalities that may be missed by human eyes.

DataJun 13

7 Key Data Fabric Use Cases in 2026

In this article, we explain 7 key data fabric use cases such as data integartion, data analytics, data governance, and data virtualization.