The Blurb On The Back:

Adopt AI-solutions to meet real-world business problems.

Artificial Intelligence In Practice is a practical resource that demystifies how Artificial Intelligence (AI) and machine learning can be used to solve common business challenges and open the door to opportunities that often exceed expectations.  The book is filled with insights from some of the most important AI giants including Google, Microsoft, Amazon, ALibaba, and other forward thinking industry leaders.  It also presents compelling case studies from traditional businesses and startups, that detail how AI is being applied in the real world of business. 

Bestselling author and AI expert Bernard Marr offers detailed examinations of 50 companies that have successfully integrated AI into their business practices.  He provides an overview of each company, describes the specific problem AI addressed and explains how AI offered a workable solution.  Each case study contains a comprehensive overview, some technical details as well as key learning summaries.

Artificial intelligence and machine learning are the most important modern business trends that are driving today’s (and tomorrow’s) successes.  As the book’s myriad cases demonstrate, AI can be used in industries ranging from banking and finance to media and marketing.  By adopting AI technology, any business, no matter what size, sector or industry, can advance innovative solutions to their most demanding challenges.  

You can order Artificial Intelligence In Practice by Bernard Marr and Matt Ward from Amazon UK, or Waterstone’s.  I earn commission on any purchases made through these links.

The Review (Cut For Spoilers):

Bernard Marr is a futurist and author who owns a digital transformation consultancy where Matt Ward works as research lead.  This shallow book (little more than a collection of press statement extracts and industry clippings) looks at how 50 companies have used AI but there’s no analysis here, no consideration of hurdles and little thought to the ethical implications, making it a disappointing read that I got little use from.

There are some big name companies featured in this book from Walt Disney Company to Uber, Facebook, Coca-Cola and McDonald’s.  However with a few exceptions, it’s clear that Marr and Ward haven’t done much first hand research for this book – the footnotes all cite either press releases from the company concerned or other industry pieces looking at the company and what it’s done.  There are some chapters where Marr draws on what he’s been told by contacts (e.g. General Electric) but these are few and far between and the contribution is limited to reporting what’s been said without any attempt to interrogate or challenge the same.  

As such, all you’re really getting here is a brief description of where a company has introduced AI to resolve an issue, with some limited colour from the industry press.  That’s interesting if you’re looking for a broad look at how businesses are seeking to deploy AI and the data sets they’re seeking to utilise but if you’re looking for something that you can use yourself within your own business, it’s basically useless.  

This is a shame because there’s a lot of scope here to analyse how companies are doing what they’re doing and to the extent that’s supported or hindered by the regulatory environment where they’re based.  For example, the clear support given by the Chinese government to companies like JD and Alibaba when it comes to individual’s personal data gives them a clear competitive advantage when developing AI to assess consumer need and targeting as compared to the tighter regulation that European companies are subject to but this doesn’t come out at all within the book.  

Nor do Marr and Ward really consider the privacy implications for individuals, which I found quite disturbing and while they do mention the risk of introducing discrimination into the algorithms powering AI, this gets no analysis when it comes to the companies cited here.  Indeed, Marr and Ward seem more interested in assuring readers that use of AI won’t necessarily mean people losing their jobs to robots (even though JD’s business model seems geared towards this specific end) and in the ethical concerns of self-driving cars, which get a lot of attention within the book with Volvo, Tesla, Uber, Google and BMW all getting chapters, although Marr and Ward at no point mention the duplication of research, effort and resource or the implications of the same for this winner-takes-all approach.

What you do get from the book is a sense of how much businesses are trying to hoover up as much data as possible to make these AI developments run.  You also get some sense of the enormous amount of resource being spent on it as businesses look to AI as a way of saving costs, improving customer targeting and leading product development.  However, you’d get that sense of scale and information from virtually any decent business magazine and you’d get more business insight with that to boot together with analysis of what it means for the wider economy and society.

Ultimately, as someone who is interested in AI and business generally, I came away from this book feeling that I’d got very little from it.  In fact, for the cost of it, I think you’re better off waiting for a publication like The Economist to do one of its in-depth looks at the topic if you’re truly interested in the subject.

Thanks to the Amazon Vine Programme for the review copy of this book.