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Cem Dilmegani

Cem Dilmegani

Principal Analyst
706 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, automation, cybersecurity (including network security, application security), data collection including web data collection and process intelligence.

Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and 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

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 24

Chatbot Intent Recognition & 5 Intent Examples

Chatbot intent is the user’s goal during interactions, but when misinterpreted, it can lead to frustrating experiences, missed opportunities, and damaged customer relationships. Even sophisticated chatbots fail to meet basic user needs without proper intent recognition. Effective chatbot intent recognition for business leaders directly impacts operational efficiency and customer relationships.

AIJun 19

Top 5 SAP Conversational AI (Joule) Use Cases

As of January 2023, SAP Conversational AI, the chatbot-building platform, has been discontinued and is now in maintenance mode. There is no direct replacement, as SAP has refocused on more advanced AI features; however, current enterprise clients can continue using it until their contracts expire.

Enterprise SoftwareOct 19

Smart trade coin is most probably a scam, stay clear of it

This is about an investment related topic, so please read our disclaimer about investment related topics first. Smart trade coin claims to enable users to automatically earn significant amounts of money without any effort. This is of course too good to be true.

Enterprise SoftwareSep 2

RPA Market Size and Popular Vendors

Robotic Process Automation (RPA) first emerged in the early 2000s, with UiPath, Blue Prism, and Automation Anywhere releasing their products and libraries around 2003. RPA started as a way to reduce outsourcing costs, with business leaders finding new revenues to automate in each industry, such as finance, healthcare, and HR.

AISep 12

Top 10 Chatbots in Healthcare: Insights & Use Cases

Healthcare chatbots are AI-powered tools that interact with patients through text or voice conversations. The healthcare chatbot market is projected to reach $1.49 billion in 2025, soaring to an estimated $10.26 billion by 2034. AI-driven chatbots are expected to save the healthcare industry $3.

Enterprise SoftwareSep 3

15+ Use Cases & AI Applications of Augmented Reality

Augmented Reality (AR) is a digital media platform that allows the user to integrate virtual context into the physical environment in an interactive, multidimensional way. Implementing AI enhances the AR experience by allowing deep neural networks to replace traditional computer vision approaches and add new features such as object detection, text analysis, and scene labeling.

Enterprise SoftwareMay 23

Timestope is possibly a big waste of time for its users

Timestope claims to have the aim of decentralizing crypto ownership by helping users earn from the advertisement served to them. Please read our disclaimer about investment related advice before reading our analysis.

Enterprise SoftwareJun 18

RPA Accounting: 6 Processes & Real-Life Examples

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.

Enterprise SoftwareSep 2

Top 20 RPA SAP Use Cases & Examples

SAP is one of the oldest and most valuable ERP systems, with ~ €31 billion in revenue. Though an ERP suite offering automation in many areas, most SAP processes are manual and repetitive, such as accounting processes, transaction management, and reporting.

Enterprise SoftwareJul 4

Top 9 RPA Use Cases & Examples in Finance

We focus on RPA use cases in finance, such as automated record-keeping and financial control. Some of those use cases are: Why is RPA important in finance? RPA’s usage is growing in the finance department because it is effective in handling repetitive, mundane, back-office tasks.