Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. While there is a lot of excitement about how advances in artificial intelligence will help the enterprise sector, the reality is that most efforts fail. Study after study shows that organizations of different sizes are struggling to bring machine learning into their operations, and many initiatives end up being shelved or used in a very limited capacity. The adoption of applied AI is very difficult and costly, wrought with pitfalls, and requires fundamental changes at different levels. However, as the tools and processes mature, more companies will be able to take advantage of enterprise AI while reducing the risks and costs of adoption.

Christopher Savoie, PhD is the CEO & founder of Zapata Computing. He is a published scholar in medicine, biochemistry and computer science. In the coming weeks, the Chinese fintech giant Ant Group is set to raise $34 billion in the world's largest-ever IPO. Although it only spun out of Alibaba in 2014, Ant's valuation, at $310 billion, will be comparable to that of JPMorgan Chase, whose origins date back to 1799. In their 2018 book, Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Harvard Business School professors Marco Iansiti and Karim R. Lakhani make the case that Ant's stunning growth can be directly attributed to its use of artificial intelligence (AI).

Artificial Intelligence is becoming more common place with enterprises today. Fueled by the popularity and success of applications like Netflix, Amazon, Alexa etc. which use AI technologies to a considerable degree, companies are vying with each other to emerge on top. But there are a number of areas that need to be optimized before the success can be ensured. How do companies ensure that the technology is well-governed, scalable, cost-effective & trust worthy? The answer is having a well-defined strategy in place which can be derived by studying the enterprises who are succeeding with it. We have worked with Fortune 500 enterprises, in defining their strategy and delivering successful & cutting-edge analytics and AI projects.

Today, businesses are under a lot of pressure to get their Artificial Intelligence (AI) strategies right. But when it comes to implementation, they are facing serious challenges around the technology and infrastructure required to support it. AI technology requires an immense amount of processing power and the ability to transfer large amounts of data. As such, it's become clear that businesses need the right environment to deploy these applications with both latency and cost considerations in mind. Further, businesses are seeing that scaling and operating efficient AI deployments require high-density compute infrastructure and associated power and cooling capacities.

A chatbot is the most in-your-face use case of AI, but it's easy to underestimate the opportunities that AI can help us realize. By some estimates, by 2023 around 40% of all internal operations teams in Enterprises will be AI-enabled. The flip side is that even though the growth opportunities are huge, it will take time, effort, and a concerted strategy to realize the true potential. Let us look at the key considerations to factor in while embarking on the AI journey. It is imperative to have a definite use case in mind before one thinks of implementing AI in your Enterprise.