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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

AISep 30

Top 25 Generative AI Finance Use Cases & Case Studies

Most of my decade-long consulting career involved serving financial services firms and helping finance leaders. I selected top generative AI finance use cases with their real-life examples.

AIAug 18

Top 10 Use Cases of Conversational AI in Retail

Modern retail faces challenges in providing personalized customer service at scale. Customers expect instant responses, 24/7 support, and tailored shopping experiences. Conversational AI addresses these challenges by enabling personalized interactions, improving customer satisfaction, and automating various online retail operations.

Enterprise SoftwareSep 29

Top 6 Alternatives to Fortra's JAMS

Based on our analysis of 20+ WLA software, we chose the top alternatives to Fortra’s JAMS. You can click the links to see each vendor’s section, where we explain our rationale behind this selection: Fortra’s JAMS Scheduler is a prominent workload automation tool that manages jobs and tasks across platforms and systems.

AISep 10

10 Generative AI Supply Chain Use Cases

Artificial intelligence, particularly generative AI, presents new opportunities to address longstanding supply chain challenges. By analyzing large volumes of historical and real-time data, generative AI can produce actionable insights that improve decision-making, efficiency, and resilience. One notable example is Microsoft Dynamics 365 Copilot, an AI-driven assistant integrated into CRM and ERP systems.

AIJun 2

12 GPT Accounting Use Cases & Benefits

Accounting software has automated data entry tasks and workflows however enterprise accounting remains manual and expensive. Recent advances in large language models (LLMs) and AI used in AP functions show the potential to significantly increase automation rates in accounting. AI tools, specifically language models using GPT technology can automate various aspects of the accounting process.

AIAug 22

In-depth Guide to Knowledge Graph: Use Cases

Your organization has data everywhere: customer databases, financial systems, HR records, project files, and emails. But when you need to answer “Which customers bought Product X and also had support tickets last month?” you’re stuck searching multiple systems, copying data to Excel, and hoping you didn’t miss anything. This data chaos costs companies millions.

DataSep 17

Machine Learning in Data Integration: 8 Use Cases & Challenges

Integrating and analyzing data from disparate sources effectively has become paramount. Data integration often presents challenges, ranging from managing AI data quality to ensuring security. As organizations grapple with these obstacles, Artificial Intelligence (AI) and Machine Learning (ML) are emerging as transformative technologies, offering innovative solutions to simplify and enhance data integration processes.

Enterprise SoftwareSep 12

Top 5 Price Monitoring Tools

A key challenge for businesses is maintaining competitive pricing while adapting to market fluctuations. Price monitoring tools help solve this challenge by tracking competitors’ prices and providing insights for more dynamic pricing decisions.

AIJul 26

Generative AI Legal Use Cases & Examples

Generative AI legal applications are set to significantly impact the legal industry, with a survey showing that 95% of over 1,000 UK lawyers anticipate a noticeable effect. Also, Goldman Sachs economists predict AI could automate 44% of legal work (Figure 1), indicating a potential transformation in legal services and professional roles.

AIOct 3

Conversational AI for Sales: Applications & Real-Life Examples

By combining natural language processing, machine learning, and integration with customer data systems, conversational AI tools enable sales teams to handle routine tasks, qualify leads, and engage in personalized conversations with prospects and customers.