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AI in commerce: Essential use cases for B2B and B2C

IBM Big Data Hub

This includes trust in the data, the security, the brand and the people behind the AI. Recent advancements in artificial intelligence (AI) are transforming commerce at an exponential pace. Successful integration of AI in commerce depends on earning and keeping consumer trust.

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Unlocking value: Top digital transformation trends

IBM Big Data Hub

Digital transformation trends that drive a competitive advantage Trend: Artificial intelligence and machine learning We’re entering year two of widespread adoption of generative AI tools. But organizations still need humans to decide what actions to take based on what the ML-analyzed data shows.

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The most valuable AI use cases for business

IBM Big Data Hub

When thinking of artificial intelligence (AI) use cases, the question might be asked: What won’t AI be able to do? But right now, pure AI can be programmed for many tasks that require thought and intelligence , as long as that intelligence can be gathered digitally and used to train an AI system.

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5 SLA metrics you should be monitoring

IBM Big Data Hub

If an e-commerce website experiences an outage during a high traffic time such as Black Friday, or during a large sale, it can damage the company’s reputation and annual revenue. By monitoring metrics and KPIs in real time, IT teams can identify system weaknesses and optimize service delivery.

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6 ecommerce trends to watch

IBM Big Data Hub

As the ecommerce market grows exponentially, six trends projected to heavily impact the global market are artificial intelligence (AI), augmented reality, live commerce, online-to-offline ecommerce, social commerce and voice assistants. They also expect the ability to use the payment option of their choice.

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5 types of chatbot and how to choose the right one for your business

IBM Big Data Hub

However, more advanced chatbots can leverage artificial intelligence (AI) and natural language processing (NLP) to understand a user’s input and navigate complex human conversations with ease. However, this system is evolving with artificial intelligence.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. AGI can boost productivity by providing a hardcoded understanding of architecture, dependencies and change history.