Hazal Şimşek
Hazal is an industry analyst at AIMultiple.
Research interests
Hazal focuses on
- process intelligence including process mining
- enterprise automation including IT automation and low-code no-code (LCNC) automation
Professional interests
She has experience as a quantitative market researcher and data analyst in the fintech industry.Education
Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.
Latest Articles from Hazal
Compare Top 21 Manufacturing AI Solutions & Software
Manufacturing AI solutions can lower maintenance costs and customize product designs. After reviewing over 50 manufacturing AI tools, we identified the top options in the market. Sorting by alphabetic order within their specific group, except the subscribers which are placed at the top. We typically consider B2B reviews, but since large manufacturing AI providers have…
AI Utilities: Top 20 Use Cases & Case Studies
AI utilities refer to AI solutions leverage real-time sensor, meter, and imagery data to forecast demand, automate inspections, optimize distribution, and improve customer service. Learn 30 tools and 20 specific real-life use cases of AI utilities: AI automates plant inspections by analyzing data from cameras and sensors in real time, reducing reliance on human workers…
Top 15+ IT Automation Software Compared
88% of organizations automate at least one business function by using AI or other IT automation software.36 IT automation software and their categories: See leading tools in their respective categories. Follow the links to learn more: * Tools are sorted in alphabetical order in their relevant categories with the exception of subscribers which are placed…
WLA Migration: Best Practices & Vendor Approaches
67% of organizations are transitioning to more functional workload automation tools, as the right choice can improve operational efficiency by 56% and reduce costs by 39% according to the State of IT Automation Report.45 Explore workload automation (WLA) migration, best practices, what to pay attention to, and the differing approaches from different vendors. WLA (Workload…
Kubernetes Cost Optimization: 8 Steps, 23 Tools & Case Studies
Kubernetes clusters can look entirely healthy while the bill climbs. Autoscaling is configured, dashboards are green, and spend rises anyway. In a survey, 42% of 455 platform engineers named cost as their number one Kubernetes challenge, while 88% saw total cost of ownership rise year on year.52 We gathered 68 Kubernetes cost optimization case studies…
100+ AI Use Cases with Real Life Examples
Exploring AI use cases can help companies identify 44% more opportunities and lower external funding needs by 39.5% before implementation. During my nearly 20 years of experience of implementing advanced analytics & AI solutions at enterprises, I have seen the importance of use case selection. I analyzed 100+ AI use cases, their real-life examples and…
Enterprise AI Companies: Landscape Breakdown
Artificial intelligence is revolutionizing every industry with various use cases. Demand for AI products grows as more companies shift their legacy systems to digital products to survive in the competitive business landscape. However, the AI vendor landscape is crowded, and most executives or decision-makers have limited knowledge of the AI landscape. Check out our comprehensive…
Top 10 Cloud Workload Automation software & 7 Use cases
Although 71% of companies run public cloud data warehouses, integrating fragmented multi-cloud environments while controlling cloud costs poses a dual challenge.78 However, cloud workload automation can orchestrate the data pipelines feeding these platforms to optimize both connectivity and resource efficiency. Explore the differences between cloud and hybrid workload automation, the top tools, and use cases…
Responsible AI: 4 Principles & Best Practices
65% of leaders feel unprepared to manage AI-related risks effectively. 81 Developing and scaling AI applications with responsibility, trustworthiness, and ethical practices in mind is essential to build AI that works for everyone. Explore four principles for responsible AI (RAI) design and recommend best practices to achieve them: AI tools are increasingly being used in…
Agentic Mesh: The Future of Scalable AI Collaboration
Theoretical discussions around AI agents dominate the market, but production implementations lag behind. McKinsey introduced the agentic mesh to solve this gap, yet real-world deployments still hit severe bottlenecks in integration, agent isolation, and operational reliability.99 Below, we analyze these live failure points and demonstrate how an event-driven mesh architecture enables controlled scaling at enterprise…
AIMultiple Newsletter
1 free email per week with the latest B2B tech news & expert insights to accelerate your enterprise.