20/03/2017 11:20 GMT | Updated 21/03/2018 05:12 GMT

A.I And Cognitive Computing: Key Opportunities And Challenges

By closely examining current marketing and data architecture, and the way systems, tools and data presently connect (or fail to connect as the case may be) organisations can gather a clearer idea of where there is a genuine need for cognitive computing and A.I technologies and how these will drive success.

The next big thing

By all accounts, 2017 is set to be the year of A.I and cognitive computing. Forrester predicts that A.I will 'drive the insights revolution in 2017' and Gartner claims that A.I and machine learning have reached 'a critical tipping point'. Indeed, Gartner goes so far as to predict that by 2020, 30% of web browsing will happen without a screen.

While there have been a limited amount of practical applications of this technology to date, there is no doubt that the concept is set to dominate the landscape for some time. However, although these technologies are undeniably exciting and revolutionary, they present as many challenges as they do opportunities.

Taking baby steps towards cognitive computing

The next few years will see organisations start to get to grips with what A.I and cognitive computing can offer. While there is much fascination with the potential of cognitive, there is still an element of nervousness from many organisations, especially when it comes to A.I. To use driverless cars as an example, the technology for these is almost perfect, but it will be a while before people are comfortable with the concept.

In addition, it will take at least two years for organisations to be mature enough to practically apply cognitive solutions, although it is important that they start to address their cognitive strategies now. This is very often the case with new technology, in that a lot of work needs to go on behind the scenes to get a business ready to properly integrate and utilise it. There was a huge amount of noise about real-time decision-making and real-time next best action marketing a few years ago, but it is only now that organisations are beginning to apply these in practice.

Understanding true cognitive computing

A large part of harnessing the opportunities cognitive computing and A.I can bring is in truly understanding how these technologies work and how they can benefit an organisation. There is often some confusion between predictive systems and cognitive systems, for example.

Predictive marketing is based on analysing huge amounts of data and automating responses on the right platform at the right time. It relies on being fed a constant stream of data - yet people are increasingly reluctant to share personal data!

True cognitive computing is teaching a system to think like a person and learn as you train it. It can take data (which does not have to be personal) and learn from this. This, in conjunction with A.I technology opens up a huge range of new ways to reach and interact with customers.

Importantly, although cognitive computing is designed to learn and run independently, it will always work best in partnership with people. For example, cognitive technology can run automate tasks such as reporting or email campaigns, freeing up people to focus on creativity and delivering better customer experiences, such as Augmented Intelligence.

Don't be seduced by gimmicks

All too often, we see organisations either rushing to buy marketing and data technology, or investing in new technology, such as A.I or cognitive, which does not then deliver on its promise or expectation. They are all driven by a desire to stay one step ahead of the competition and carve out an advantage in an increasingly crowded and fast-paced environment.

Businesses need to look beyond a 'gimmick-led' application of these technologies and instead investigate how it can be applied to actively improve personalised customer experience.

To do this, organisations need to step back and start with the customer. Understand how your customers are interacting with your brand and what kind of experience they are looking for. People don't necessarily want a relationship with a brand, they just want a good experience.

The North Face is one example of where cognitive computing is being practically applied to deliver this kind of experience. Users visiting The North Face website can have a similar experience online as in-store, thanks to intelligent natural language processing technology that helps customers choose a jacket by asking a series of questions and learning from the answers supplied. Powered by IBM Watson cognitive computing technology together with Fluid XPS, the retailer can provide customers with outerwear suggestions tailored to their needs, creating a more engaging, relevant and personalised shopping experience.

Getting your house in order

Perhaps more fundamentally though, businesses first need to get their own houses in order before embarking on implementing new technologies such as cognitive or A.I. Before purchasing any new technology, organisations first need to fully understand the systems they already have. In particular, the majority of organisations have much to do in terms of joining up silos and sharing data between departments, ensuring they have the right skills and teams in place and a clear roadmap and business case for how any new technology is going to deliver value.

By closely examining current marketing and data architecture, and the way systems, tools and data presently connect (or fail to connect as the case may be) organisations can gather a clearer idea of where there is a genuine need for cognitive computing and A.I technologies and how these will drive success.

Innovating and pushing the boundaries of what is possible through the use of exciting technologies is of course great. However, in order to gain value from groundbreaking technology and turn it in to something that will deliver significant improvement to their customers, it is vital that organisations strike the right balance. As Kevin Kelly, author and founder of Wired famously said "perfect what you know".