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Artificial intelligence needs to speak the language of business, not the other way around

 


AI business is business

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Nearly all business leaders on the planet (94%) believe AI will be critical to their success over the next five years. Still, many companies are still falling short of delivering the value they expected, according to the latest Deloittes survey on the state of AI, with a 29% increase in the percentage of respondents who believe AI is underachieving compared to last year. doing.

According to Deloitte research, issues undermining the impact of AI include challenges to improving business value and a complete lack of executive commitment. Industry leaders and observers on the ground agree that it is these organizational problems, not technical ones, that are holding back progress.

The bottom line is that AI must serve customers and help businesses put them front and center.

Most AI projects fail to deliver value because they do not start with business realities, such as the benefits of correct predictions, the cost of incorrect predictions, and constraints such as the size of marketing budgets. If an AI project looks like a lab experiment and experts are talking about log loss etc. instead of revenues, profits and costs, it is almost certain that the AI ​​will not be able to deliver results.

The key is to make decision makers more comfortable with AI, build organizational support for AI, and keep a direct focus on how AI can help customers. Boomi chief Rajesh Raheja, his engineering officer, says organizations are more likely to adopt his AI-based approach if it ties directly to demonstrable customer value. . For example, based on learned and proven best practices, a recommendation engine that can suggest next steps to implement in a business process is more likely to help a business than the same engine that simply shows more products for a business to purchase. much more helpful for Both require sophisticated AI models, but the former clearly brings value to customers.

I have the tools but I don’t know how to apply them. Adoption of AI will depend on the value it creates and his ROI compared to efforts to train a model that require the appropriate resources and skills to set up a powerful data pipeline. The output of machine learning changes with data, algorithms, and their evolution. Fear of unknown decisions that cause unexpected liability is another factor that makes mainstream businesses cautious.

As an example, Raheja adds that AI-driven loan applications that reject certain sections of the population after updating the model could be an error, or an inherent bias introduced into the data and model.

A lot of this also has to do with the timeliness of AI data. AI is actually perishable, he says, Sengupta. If the AI ​​takes months to create, the AI ​​is no longer up-to-date because it was trained on data months ago and the world has changed in the meantime. To get value, you need to build and deploy AI in days, not months, and iterate as the world changes.

There are many innovative business cases that can be developed to accelerate the adoption of AI. Examples Raheja gives include using AI to analyze, format, and semantically check customer data as it enters the system. Natural language processing and automated chatbots for customer relationship management are other use cases.

Remember, AI adoption is limited by the availability of data scientists. You can’t train how to get out of that problem, he adds Sengupta. We are not teaching AI to speak business, we are teaching business users to speak AI. Before asking business users to learn Python, stop and say: Why can’t AI understand my business needs and automatically generate Python code? The Internet Revolution never happened because everyone learned how to code to interact with the World Wide Web. This happened because the Netscape browser is almost universally available.

Sources

1/ https://Google.com/

2/ https://www.forbes.com/sites/joemckendrick/2022/11/27/artificial-intelligence-needs-to-speak-the-language-of-business-not-the-other-way-around/

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