
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
RPA for Mac: 13 RPA tools That Can Run on Mac
RPA is a popular automation technology with various tools available across different platforms. The chart above shows that Windows dominates search interest for RPA platforms, which explains why many RPA tools primarily target Windows. Finding an RPA solution specifically designed for macOS becomes challenging. But that doesn’t mean RPA for Mac doesn’t exist.
45 Statistics, Facts & Forecasts on Machine Learning
Machine learning is the study of computer algorithms that learn through data. Machine learning is regarded as a subset of artificial intelligence. Surveys and market research are the best way to understand the overall view of the machine learning market, as numbers can reveal key metrics, from the market’s importance to its challenges.
Top 5 AI Services to Enhance Business Efficiency
AI adoption is on the rise. 98% of companies are experimenting with AI, while 26% are advancing to generate tangible value. Explore the top 5 types of AI services that can accelerate your business’s AI adoption journey. 1.
Bias in AI: Examples and 6 Ways to Fix it
Interest in AI is increasing as businesses witness its benefits in AI use cases.
50 RPA Statistics from Surveys: Market, Adoption & Future
RPA has gained popularity since the 2000s due to quick implementation and digital transformation.
15 Digital Twin Applications/ Use Cases by Industry
As more sectors explore virtualization, digital twin solutions are gaining mainstream traction. According to Deloitte study, the global market for digital twins is expected to grow with 38% CAGR to reach $16 billion by 2023, and the proliferation of IoT technology accelerating this growth.
Custom AI: When to Build Your Own Solutions
Although off-the-shelf AI tools support many enterprise needs, they often fall short in high-impact, data-specific use cases. Businesses operating in complex or niche environments often find that generic AI solutions can’t effectively accommodate their unique workflows or leverage proprietary data.
Top 10+ Legal AI Use Cases & real-life examples
The legal AI software market is expected to quadruple in the next five years, as AI technology offers significant potential to help lawyers focus on higher-value tasks. Despite challenges such as biased forecasts and tracking changing regulations, there are many manual tasks within legal departments that can be automated.
Manufacturing AI: Top 15 tools & 13 real life use cases
The industrial manufacturing industry is the top adopter of artificial intelligence, with 93 percent of leaders stating their organizations are at least moderately using AI. Manufacturers are frequently facing different challenges such as unexpected machinery failure or defective product delivery.
Explore Top 10 Privacy Enhancing Technologies
Though data privacy legislation such as GDPR in the EU and CCPA in California are meant to prevent privacy breaches, consumer’s privacy is frequently invaded by hackers, companies and governments. Data leakages increase as businesses share consumers’ data with third-party companies in order to increase network visibility.
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