Explore how AI for business improves productivity, customer experience, decision-making, and operations—plus key use cases, risks, and a practical adoption strategy. Artificial intelligence is no longer just a technology trend. It is becoming a business capability. In 2024, 78% of organizations reported using AI, up from 55% the year before, according to Stanford’s 2025 AI Index . McKinsey’s 2025 global survey also found that companies are moving beyond experimentation and beginning to redesign workflows and assign leadership responsibility for AI governance . For business leaders, that changes the question. The real issue is no longer “Should we use AI?” It is “Where can AI create measurable value, and how do we deploy it responsibly?” The strongest business case for AI is not hype. It is better productivity, faster decisions, improved customer experience, and the ability to scale knowledge across teams. Research from the National Bureau of Economic Research found that access...
Explore how memory empowers agentic AI systems—why memory matters, how it’s built, what types exist, what challenges and design-patterns to use, and how memory transforms reactive tools into truly autonomous agents. Introduction In the era of large language models and generative AI, we’re increasingly talking not just about “tools” but about “agents” — systems that act autonomously, set and pursue goals, adapt to their environment, and engage over time. This paradigm of agentic AI is rapidly gaining traction across enterprise and consumer domains. Aisera: Best Agentic AI For Enterprise +1 But what elevates an AI “agent” above a one-off prompt/response model? At the heart is memory — the ability to remember, recall, learn, adapt, and thereby behave more like a persistent collaborator than a stateless tool. In this article we’ll explore: what memory means in agentic AI, why it matters, what types exist, how it’s engineered, best practices and challenges, real world use cases and...