Category: Implementation of AI

As shown in this chapter, when approaching implementing AI, it’s critical to look at two paths. The first is to get the maximum use of any third-party systems that use the technology. But there should also be a focus on data quality. If not, the results will likely be off the mark. The second path…

Even when you build an AI model that works, there is still more work to do. You need to find ways to deploy and monitor it. This requires change management, which is always complex and difficult. AI is different than a typical IT implementation since it involves using predictions and insights for decision-making. This means…

There are a myriad of AI frameworks, which provide end-to-end systems to build models, train them, and deploy them. By far the most popular is TensorFlow, which is backed by Google. The company started development of this framework in 2011, through its Google Brain division. The goal was to find a way to create neural…

There are many tools for helping create AI models, and most of them are open source. Even though it’s good to test them out, it is still advisable to first conduct your IT assessment. By doing this, you should be in a better position to evaluate the AI Tools. Something else: You may realize that…

How large should the initial team be for an AI project? Perhaps a good guide is to use Jeff Bezos’ “two pizza rule.”10 In other words, is this enough to feed the people who are participating? Oh, and there should be no rush to build the team. Everyone must be highly focused on success and understand…

Founded in 1976, HCL Technologies is one of the largest IT consulting firms, with 132,000 employees across 44 countries, and has half the Fortune 500 as customers. The company also has implemented a large number of AI systems. Here’s what Kalyan Kumar, who is the corporate vice president and global CTO of HCL Technologies, has…

If you plan to implement your own AI models, what are the main steps to consider? What are the best practices? Well, first of all, it’s critically important that your data is fairly clean and structured in a way to allow for modelling (see Chapter 2). Here are some other steps to look at: Let’s take…

Using AI in a company generally involves two approaches: using vendor software or creating in-house models. The first one is the most prevalent—and may be enough for a large number of companies. The irony is that you may already be using software, say from Salesforce.com, Microsoft, Google, Workday, Adobe, or SAP, that already has powerful AI capabilities.…