Businesses are using machine learning to improve all sorts of outcomes, from optimizing operational workflows and increasing customer satisfaction to discovering to a new competitive differentiator. Despite the explosion of options in the last few years, the results vary from organization to organization based on several factors. If you want to avoid some of the common pitfalls and drive more value from your efforts, resolve to do the following in 2019. Many organizations are so focused on the potential benefits of machine learning that they forget to consider the potential risks. In glossing over the details, it's tempting to transform the entire business when it's wiser to start with a use case or two, learn from the experience and build on the successes.
In the last decade, the world of business has changed considerably due to the impact of technological innovation. In particular, cloud computing has grown into one of the most important paradigms in business. As such, it has become imperative for any business to adopt cloud technology. History has shown that whenever there is a new change in technology, organizations are forced to either hire new talent who possess the relevant skills or to train existing employees to adapt to that new technology. Today, it has become very essential for all organizations to bridge the skills gap in cloud technologies.
FOR the second straight year, Deloitte surveyed executives in the US knowledgeable about cognitive technologies and artificial intelligence,1 representing companies that are testing and implementing them today. We found that these early adopters2 remain bullish on cognitive technologies' value. As in last year's survey, the level of support for AI is truly extraordinary. These findings illustrate that cognitive technologies hold enticing promise, some of which is being fulfilled today. However, AI technologies may deliver their best returns when companies balance excitement over their potential with the ability to execute. A year later, and the thrill isn't gone. In Deloitte's 2017 cognitive survey, we were struck by early adopters' enthusiasm for cognitive technologies.4 That excitement owed much to the returns they said cognitive technologies were generating: 83 percent stated they were seeing either "moderate" or "substantial" benefits. Respondents also said they expected that cognitive technologies would change both their companies and their industries rapidly. In 2018, respondents remain enthusiastic about the value cognitive technologies bring. Their companies are investing in foundational cognitive capabilities, and using them with more skill. Thirty-seven percent of respondents say their companies have invested US$5 million or more in cognitive technologies. Another reason is that companies have more ways to acquire cognitive capabilities, and they are taking advantage.
Utilities around the world are making big investments in advanced analytics. Getting the full value, however, requires rethinking their strategy, culture, and organization. Advanced analytics can deliver enormous value for utilities and drive organizations to new frontiers of efficiency-- but only with the right approach. There's little to be gained from just bolting on a software solution. The real value comes from embedding data analytics as a core capability in the organization and using it to detect pain points, design solutions, and enable decision making.