
Cem Dilmegani
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
- Cem Dilmegani (September 28, 2017). Post-AI Banking: Millions of jobs at risk as banks automate their core functions. International Banker
- Cem Dilmegani, Bengi Korkmaz, and Martin Lundqvist (December 1, 2014).Public-sector digitization: The trillion-dollar challenge.McKinsey & Company
Conference & other event presentations
- Real Estate and Technology, presented by Hofstra University’s Wilbur F. Breslin Center for Real Estate Studies and the Frank G. Zarb School of Business in 2023 and 2024.
- Radar AI session (June 22, 2023): "Increasing Data Science Impact with ChatGPT".
- Generative AI Atlanta meetup (March 10, 2023): Generative AI for Enterprise Technology.
Sources
- Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
- Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
- Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
- Science, Research and Innovation Performance of the EU, European Commission.
- EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
- Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
- We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.
Latest Articles from Cem
Lazarus AI: Extractive & On-Prem AI for Regulated Industries
Generating insights from unstructured data has long been a strategic aim among organizations that Lazarus AI builds foundation models (e.g. RikAI) to solve complex and urgent problems involving large amounts of unstructured private data. Lazarus is active in these industries: Government (e.g. defense), insurance (e.g. damage assessment of catastrophic events), healthcare, and banking.
Large Action Models: Hype or Real?
Following the launch of Rabbit, an AI device that can use mobile apps, the term large action models (LAMs) is getting popular. These models move beyond conversation by turning LLMs into “agents” that can connect the siloed, app-driven world without requiring a user to click on apps or integrate an API.
Top 4 Free ITAM Software
IT asset management software comes with different pricing plans including paid, free, and open source options. See our rationale for below recommendations by following the links on product names. Businesses can choose from free or open-source software to manage their assets.
Mobile Device Management Pricing Comparison: 20 Products
Understanding pricing structures and other aspects of Mobile Device Management (MDM) software is necessary to make wise decisions. Depending on the pricing structure, mobile device management products can range in price. See how Mobile Device Management pricing is structured and compare MDM products.
Network Monitoring Service Pricing Comparison
Network monitoring service pricing is shaped by several factors. Providers typically offer different pricing models such as per-device, per-host, or per-technician billing.
5 Steps from Chatbots to Secure Enterprise AI Agents
Though LLMs are great at text generation, their Enterprise AI agents are being built by leading SaaS vendors to address these issues. These bots need to be able to: While these are table stakes, how they are implemented is important.
Compare 20+ AI Agent Builders
After reviewing the documentation and spending several hours tinkering with these AI agent builders, we listed the best open-source frameworks and low-code/no-code platforms. To highlight AI agent builder use cases we provided a tutorial on building a product expert agent with CrewAI.
10 Procurement Case Studies: Examples & Lessons Learned
Effective procurement practices are necessary across all industries. By examining procurement case studies in various sectors, from non-profit to technology, healthcare, and beyond, we gain valuable insights into the impact of procurement solutions and best practices that can drive success in any industry.
IT Asset Management Pricing: Compare Top Providers
We compared the prices of 8 ITAM solutions to help IT managers, procurement teams, and SMEs evaluate which tools best align with their needs. Key differences in cost structure, features, and scalability are highlighted to support informed decision-making.
DLP in Banking: Best Software & Practices
To protect against the rising data threat, banks and financial institutions must implement effective data loss prevention software and strategies tailored to their unique banking sector needs. Here, we list the best DLP software compared with banking and finance-specific criteria, and provide some best practices to help your business protect its confidential data. 1.
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