Digitisation and data are now everywhere. The ability to leverage data can drive value, satisfaction and loyalty from customers. The process is a simple one – businesses need to collect data, refine and mine so they can deliver actions from it. The crucial element is to ensure that when collecting data, it’s retained in its natural form.
The conversation about deriving value from data is becoming ever more closely linked to the subject of artificial intelligence (AI). We regularly hear about AI being the next big thing, however, this was also the case in the late 1980s but this, in fact, turned out to be data mining. Now, when people think about AI more often than not they think of autonomous cars, yet in reality, AI’s most prevalent use is in chatbots. 53% of service organisations are expecting to use chatbots within 18 months, which equates to a growth rate of 136%.
Applying AI to data
As businesses begin to think about where they can apply AI to have a real impact, it’s likely we’ll see it being used to enhance decision making in areas such as fraud prevention, loyalty programmes and new revenue opportunities.
So, if AI was first slated to become mainstream more than thirty years ago, why is now the right time for this technology?
Quite simply the models used get better with the more data they are fed and there is no shortage of data, with worldwide data creation expected to grow to an enormous 163 zettabytes by 2025. More data also means the accuracy of models will improve. Also, with unlimited processing power, this means real-time delivery.
With businesses starting to embark on an AI strategy, it’s vital they not only consider the level of data they can store, but they also need to think about it as connected not converged. It’s important to remember data doesn’t need to be all in one place, and so businesses can play with the data where it lies. Some of the data you want to capture may not be created by you – for example – it could be your web services provider. Also, it’s important you don’t apply too much cleansing to data as you may lose some of the interesting insight.
When thinking of AI technology, the emergence of open source means it’s important to build flexible data fabric, rather than a one-size fits all solution. Alongside this, it’s also important to consider the data governance policy – who has access to what? And how do you govern that?
AI is here now and won’t be going away. The end audience has higher expectations than ever, so it’s essential that businesses don’t let their past interfere with their future.
Ultimately AI is a business mandate – it needs to be transformational, aspirational and measuring it with C-level objectives will create focus and attention. In a world where data is growing exponentially, InterSystems technology is perfectly placed for users to succeed in today’s customer-centric world.