AI Foundations
Explore foundational concepts, tools, and evaluation methods that support the effective development and deployment of AI in business settings. This section helps organizations understand how to build reliable AI systems, measure their performance, address ethical and operational risks, and select appropriate infrastructure. It also provides practical benchmarks and comparisons to guide technology choices and improve AI outcomes across use cases.
Custom AI: When to Build Your Own Solutions in 2025
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.
Explainable AI (XAI) in 2025: Guide to enterprise-ready AI
As AI tools become more advanced, more computations are done in a “black box” that humans can hardly comprehend. This approach is problematic since it prevents transparency, trust and model understanding. After all, people don’t easily trust a machine’s recommendations that they don’t thoroughly understand.
Demand Forecasting in the Age of AI & Machine Learning
Businesses face different inventory challenges when they are dealing with supply chains. Addressing supply chain issues is paramount. Demand forecasting enables businesses to reduce supply chain costs and achieve significant improvements in financial planning, capacity planning, profit margins, and risk assessment decisions.
100+ AI Use Cases with Real Life Examples in 2025
During my ~2 decades 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 categorized them by business function and industry.
AI Explained: Trends and Applications by Industry in 2025
Artificial Intelligence (AI) allows computers to learn from experience, adapt to new inputs and perform human-like tasks. Most of the AI examples you’ve heard about –from chess-playing machines to self-driving cars–rely heavily on deep learning, a subfield of AI.
When Will AGI/Singularity Happen? 8,590 Predictions Analyzed
We analyzed 8,590 scientists’, leading entrepreneurs’ and community’s predictions for quick answers on Artificial General Intelligence (AGI) / singularity timeline: Explore key predictions on AGI from experts like Sam Altman and Demis Hassabis, insights from five major AI surveys on AGI timelines, and arguments for and against the feasibility of AGI: Artificial General Intelligence timeline
Google's AI Strategy and 11 Key Developments in 2025
Google’s current artificial intelligence strategy emphasizes advanced integration of AI models into enterprise solutions, with significant investments focused on improving functionality, accuracy, and efficiency. Check out 10 recent developments for businesses considering implementing Google’s AI tools and platforms into their workflows. 1. Gemini 2.5: Google’s advanced multimodal AI Google DeepMind launched Gemini 2.