As artificial intelligence continues to capture the imagination of the tech and mainstream media, customer intelligence professionals need to take a pragmatic view of what AI can do for business.

Breakthroughs from major companies, including Google, Apple and Amazon, have placed AI high on the technology agenda. However, business leaders are struggling to make sense of how this technology could and should be deployed in their organisations.

To put it mildly, this is confusing for businesses: what is real and what is snake oil? AI will significantly disrupt the way organisations win, serve and retain customers … eventually. To do this, it will take massive amounts of data to train artificially intelligent systems to perform their jobs well enough to replace their human counterparts.

As storage and processing power advances, AI is gaining some traction among businesses, allowing companies to generate insights and engage with their customers.

AI is uniquely suited to help optimise customer interactions across touch points and channels. This is largely driven by the technology’s ability to process huge amounts of data, which can inform real-time action. Moreover, businesses will soon be able to blend technologies such as facial scanning, text analytics, machine learning and natural language generation to better engage with their customers.

AI can also surface insights automatically, with banks today already using such technologies to detect anomalies that might point to fraudulent transactions. Combing through massive data sets will also allow for better data analysis, particularly when it comes to unstructured data.

Despite these early successes, it may take time and work before the real benefits of AI will be realised.

AI is not a homogenous set of technologies, and some tasks will take longer to automate than others. And, even though the goal of AI technology is to free humans from some intelligence tasks so that they may more effectively focus on others, the process of creating this state has significant challenges for human designers and engineers.

One of the main challenges facing the adoption of AI into mainstream business is the lack of a clear business case. The research and academic communities were the first to develop and deploy AI technologies, and businesses are only now jumping onto the bandwagon. Organisations still require a clear ROI to justify an AI investment.

Time and skills are also potential hurdles. Artificially intelligent systems require massive amounts of training data to learn to perform specific tasks. While some vendors offer pre-trained solutions, even these will require many additional hours of training and refinement before they can be deployed.

When it comes to skills in the field, there is a clear dearth of talent. If data scientists are unicorns, then specialists in AI are their even more rarely mentioned winged cousin, Pegasus. There are a handful of notable researchers in academia who specialise in deep learning and AI, but the talent pool for businesses is extremely shallow. Additionally, since AI adoption for businesses is so nascent, there are even fewer people with the ability to deploy AI in a business context.

Identifying and analysing the current and future prospects of 12 AI technologies and solutions, two technologies can be placed in the Creation phase, six in the Survival phase and four in the Growth phase. None are in the Equilibrium or Decline phases due to the relative immaturity of AI. When it comes to AI, we are still in chapter one.

Despite many doom-mongers, AI will not be a threat to most jobs. While there may be some losses in the call centre and other positions, for the most part AI will free employees from banal or onerous tasks with little value-add. There is no imminent rise of the machines about to take place and humankind is not facing an immediate threat. In fact, it is the role of the customer intelligence leader to separate the myth from reality.