Premium
Services
Premium
Sıla Ermut

Sıla Ermut

Industry Analyst
93 Articles
Stay up-to-date on B2B Tech

Sıla is an industry analyst at AIMultiple covering AI models, AI infrastructure, AI governance, and enterprise applications of AI.

Research interests

Sıla’s research focuses on the use of AI in marketing, healthcare, supply chains, and sustainability. She also covers AI evaluation, governance, ethics, and adoption.

Her work includes researching and comparing AI technologies, analyzing their business applications, and contributing to AIMultiple’s technology benchmarks.

Professional experience

Sıla previously worked as a recruiter and worked in project management and consulting firms.

Education

She holds:
  • Bachelor of Arts degree in International Relations from Bilkent University.
  • Master of Science degree in Social Psychology from Başkent University.

Her Master's thesis was focused on ethical and psychological concerns about AI. Her thesis examined the relationship between AI exposure, attitudes towards AI, and existential anxieties across different levels of AI usage.

Latest Articles from Sıla

Agentic AI
Open World Evaluation
Oct 13

15 AI Agents in Marketing Tools & Examples

Research shows that 50% of organizations using generative AI plan to launch agentic AI pilot programs.AI agents in marketing introduce systems that can reason, make decisions, and act with minimal human oversight. These intelligent agents analyze customer data, generate actionable insights, and coordinate campaigns across multiple platforms in real-time. We evaluated the top 15 AI…

AI
Insight
Oct 13

Enterprise Generative AI: 11 Use Cases & Best Practices

Generative AI (GenAI) presents novel opportunities for enterprises compared to middle-market companies or startups, including: However, generative AI brings challenges unique to large organizations. For example: Explore our practical enterprise AI use cases to learn how large companies can build, deploy, and govern their own generative AI models effectively. The web is full of B2C…

Enterprise Software
Insight
Oct 13

8 Network Monitoring Use Cases with Real-Life Examples

Network monitoring is one of those things that IT teams notice when it is missing. When it works well, problems get caught before users know anything is wrong. When it is absent, a minor connectivity issue can quietly escalate into a major outage. See our examples below to show how organizations are actually putting these…

AI
Insight
Oct 13

Top 20+ Predictions from Experts on AI Job Loss

As a McKinsey consultant, I helped enterprises adopt new technologies for a decade. My quick answers: Note: The size of the plots is correlated with the size of the job loss prediction. The percentages referenced in our analysis are derived from assumptions about overall job displacement. In specific scenarios, these assumptions included potential job gains…

AI
Insight
Oct 13

Top 11 AI in Fashion Use Cases & Examples

Faced with creative bottlenecks, inefficient supply chains, and rising consumer expectations, fashion brands are seeking smarter solutions. McKinsey estimates that generative AI could boost operating profits in the fashion, apparel, and luxury sectors by up to $275 billion by 2028. Explore the top 11 use cases of AI in fashion to help fashion brands cut…

Enterprise Software
Open World Evaluation
Oct 12

Top 8 Network Monitoring Software

We compared the top 8 network monitoring tools for their performance, ease of setup, and real-world usability. The table is sorted based on the number of reviews. We list our subscribers at the top. Vendor selection criteria: We narrowed down our network monitoring software comparison using three main factors: For definitions of the features mentioned…

AI
Insight
Oct 12

20+ Healthcare AI Use Cases with Examples

A recent study shows that hybrid teams of human clinicians and AI systems make more accurate medical diagnoses, largely because they tend to make different and complementary errors that help correct one another. These findings indicate strong potential of AI to enhance patient safety and promote more equitable healthcare. How do healthcare AI systems perform?…

AI
Insight
Oct 9

No-Code AI: Benefits, Industries & Key Differences

No-code AI tools allow users to build, train, or deploy AI applications without writing code. These platforms typically rely on drag-and-drop interfaces, natural language prompts, guided setup wizards, or visual workflow builders. This approach lowers the barrier to entry and makes AI development accessible to users without a programming background. Recently, no-code AI has expanded…

AI
Open World Evaluation
Oct 9

Top 20 Supply Chain AI Tools with Examples

From demand forecasting and inventory optimization to last-mile delivery and supplier negotiations, AI enables supply chain companies to process complex data, respond to disruptions more quickly, and make more informed decisions across global networks. Discover the top 20 supply chain AI tools and learn how they utilize AI to address real-world challenges and enhance performance…

AI
Insight
Oct 8

AGI/Singularity: 10,000 Predictions Analyzed

Artificial general intelligence (AGI) is when an AI system matches human cognitive abilities across all tasks. We analyzed 10,000 AI researchers‘, leading entrepreneurs‘, and community predictions about the AGI timeline: Will AGI/singularity happen? AGI is inevitable according to most AI experts. When will we reach AGI? Between late 2020s and early 2030s. AGI timeline shortened…