Anodot is thrilled to share a comprehensive recap of our roundtable on AI-driven financial operations, where our esteemed panel of experts discusses the challenges of delivering success in FinOps and explores its future.
Our panel of experts includes Sean Donaldson, CTO of Protera, Corné van der Vaart, Technical Cloud Project Manager of A.C.A. Group, Nir Raz, Ran Blumenfeld, FinOps & Customer Success, Cloud FinOps Director of Nice, Inbal Tadeski, a Data Scientist at Anodot, and Melissa Abecasis, Customer Success Director at Anodot.
Experts discuss the challenges of transitioning from traditional business practices to cloud adoption. Still, the shift to public cloud platforms like AWS and Azure is changing the game, albeit not without its challenges.
The key obstacles include:
- Architecting cloud servers properly
- Managing costs,
- Aligning security with business goals.
The panel recognizes that establishing a FinOps organization can address these issues. Automation, predictive analytics, and AI are the future of FinOps, enabling cost optimization in government and private sector companies.
Also Read: Mitek Named Winner at FinTech Finance 2023 FF Awards Ceremony
According to Inbal Tadeski, Anodot’s Data Scientist, leveraging AI-driven methods and machine learning is crucial to controlling and optimizing cloud costs. Inbal was a main contributor to Anodot’s Cost GPT tool that takes data exploration to a new level using natural language.
Moreover, she added, predictive analytics and forecasting can help organizations plan and budget while giving them confidence in their decisions. Focused-based recommendations, such as suggesting saving plans based on current usage, can help organizations save money.
“Forecasting assists in effective planning and budgeting, instilling confidence in decision-making,” explains Inbal Tadeski, Data Scientist at Anodot. “Anodot is also actively developing targeted recommendations, including proposing savings plans based on your current usage.”
Our roundtable believes that AI will improve by making recommendations and predictions, allowing organizations to focus on reducing cloud waste and finding ways to modernize and plan commitments. However, there is a need to balance human knowledge with AI. While AI enhances FinOps analysts’ effectiveness, human involvement remains essential.