AI’s significant benefits are enhanced products and
processes— and better decisions.

Despite the benefits, there are several main factors that can slow down the adoption of artificial intelligence for Digital Business:

1. Culture. From getting executives buy-in until educating employees, integrating AI solutions into their day-to-day activities might become a challenge.
2. Use cases. Organizations need to have a clear strategy or practical use cases to implement AI on their business process.
3. Talent. The same as as most digital skills that organizations require for their transformation, AI and ML talent can be difficult to source.

Artificial intelligence in digital business

1. Customer experience
   AI and machine learning technologies could deliver meaningful customer experiences, customized products, engaging them on a deeper, more personal level. The practical use cases are from using sentiment analysis to get actionable insights into what your customers think about the company to implementing specific technologies to improve customer experience, such as chatbots, recommendation engines, etc.
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2. Cybersecurity
   Machine learning can be used to detect malicious behavior and anomalies that might be an indication of a security violation. Algorithm-based systems are more reliable while a person can make mistakes. This use case is typically applied for the business operations to respond to incidents in and resolve it in a timely manner, minimizing the downtime and improving data security in general.
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3. Decision making
   Machine learning algorithms can identify specific patterns, deliver actionable insights into business performance, potential risks, and opportunities. This could minimize business risks. Other than predicting the outcomes of each decision, AI systems can also take a prescriptive approach and suggest specific actions to achieve the required results.