Sıla Ermut
Sıla is an industry analyst at AIMultiple focused on email marketing and sales videos.
Research interests
Sıla's research areas include email marketing, eCommerce marketing campaigns and marketing automation.She is also part of AIMultiple's email deliverability benchmark. She is designing and running email deliverability benchmarks while collaborating with the AIMultiple technology team.
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
Top 10 AI Infrastructure Companies & Applications
Many organizations invest heavily in AI, yet most projects fail to scale. 10-20% of AI proofs of concept progress to full deployment.1 A key reason is that existing systems are not equipped to support the demands of large datasets, real-time processing, or complex machine learning models. As AI becomes more central to business strategy, infrastructure…
IT Asset Management (ITAM) Pricing Comparison
Finding the right IT Asset Management (ITAM) solution is key to controlling costs, reducing risks, and gaining full visibility into your IT infrastructure. Designed for IT managers, procurement teams, and SMEs, this comparison highlights how different pricing models and feature sets align with varying business needs. With clearer insight into each provider’s offerings, decision-makers can…
Prices of Top 6 IT Service Management (ITSM) Software
IT Service Management (ITSM) tools that support incident, problem, change, and knowledge base management offer diverse pricing models. See IT service management pricing details of the top 6 providers and the feature guide for small businesses and enterprises. Note: Pricing information is obtained from vendor websites. Explore IT asset management pricing to discover additional vendors…
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 2028.12 Explore the top 11 use cases of AI in fashion to help fashion brands cut…
20 Strategies for AI Improvement & Examples
AI models require continuous improvement as data, user behavior, and real-world conditions evolve. Even well-performing models can drift when the patterns they learned no longer match current inputs, leading to reduced accuracy and unreliable predictions. Changes in regulations, product requirements, or customer expectations can also introduce new constraints that existing models were not designed to…
AI Image Detector Benchmark
As these synthetic visuals grow more realistic and accessible, the ability to detect them has become a critical concern for upholding generative AI ethics, combating misinformation, and ensuring image authenticity. We compared the top 7 AI image detectors across 5 dimensions and found that most perform no better than a coin toss. See insights into…
Top 4 AI Guardrails: Weights and Biases & NVIDIA NeMo
AI security failures are expensive and increasingly common. Many incidents stem from weak governance, particularly gaps in access control, data permissions, and oversight of model usage. AI guardrails reduce this risk by setting enforceable boundaries for how AI systems access data, generate outputs, and interact with users or business workflows. Explore how AI guardrails operate,…
AI Fail: 10 Root Causes & Real-life Examples
Whether it’s a self-driving car crash, a biased algorithm, or a breakdown in a customer service chatbot, failures in deployed AI systems can have serious consequences and raise important ethical and societal questions. By identifying and addressing the underlying issues, companies can mitigate the risks associated with AI and ensure that it is used safely…
AI Energy Consumption Statistics
A recent forecast predicts AI will use over half of data center electricity by 2028.54As compute-intensive workloads such as generative AI expand, total electricity demand is also expected to rise. We covered data from the IEA, MIT, and major cloud providers to identify AI energy consumption efficiency trends and policy responses and best practices. We…
15 AI Agents in Marketing Tools & Examples
Research shows that 50% of organizations using generative AI plan to launch agentic AI pilot programs.66AI 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…
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