Businesses are coming under increased pressure to offer consumers the more personalised services many have now come to expect
Demand for these offerings is so high that businesses that are unable to deliver them, due to a lack of agility, are likely to become less meaningful to consumers and ultimately fall to the wayside.
As organisations attempt to respond to consumers’ changing requirements, artificial intelligence (AI) has been shown to be effective in helping them to provide the goods and services their customers desire. However, this technology is equally giving consumers themselves access to streamlined online tools which empower them to tailor products and services to their own personal preferences on demand. For instance, when booking a holiday, online platforms now allow consumers to build it from scratch themselves by sourcing different options for everything from flights and hotels, to car rentals and activities. While great for holidaymakers, this trend threatens the traditional package holiday and providers of those.
Consequently, to be competitive, more organisations should be providing a customer experience that steps beyond what is now commonplace, into a more intelligent understanding of people’s needs and how to meet them.
As such, businesses need a foundation of good data and the application of AI to enable far greater personalisation and more persuasive targeting with offers, recommendations, guidance and advice. However, businesses need to strike the right balance: providing information, goods, and services to customers based on their personal preferences, but in a way that is not too intrusive or insistent.
The barriers to AI adoption
The majority of businesses know they should be using AI to provide better and more personalised services, however, they often struggle to put it into practice. There can be a number of reasons for this, including a lack of understanding of data science to train and develop AI models, not collecting enough data or a lack of knowledge about what kind of data they should be collecting.
Further to this, it is often the case that businesses are unaware of where they should apply AI to gain broader benefits. Cultural barriers also remain high in some businesses where senior teams have yet to grasp just what AI will deliver.
Broad-scale adoption of AI can be very difficult for people to understand, especially if they work outside the digital technology sector. Therefore, a democratisation of AI is needed, with software and solutions providers building in capabilities that enable more businesses to realise the significant benefits of AI in their day-to-day operations. Providing access to more pre-built, off-the-shelf AI solutions will make it easier for even smaller businesses to implement them.
Unfortunately, data remains a significant barrier to AI adoption. An AI solution is only as good as its training model, but many organisations still don’t know how to obtain the quality and quantities of data needed to feed such models. However, smart data fabrics, a new architectural approach, have emerged as a way to overcome this issue and enable organisations to fully leverage their data.
Still a fairly new concept, smart data fabrics interweave data from multiple sources and different formats, using a multi-tier approach that cleans data and employs an integration layer to make it usable. The fabric does this while leaving the data where it is, with lineage tracked for every item, enabling users to see where it has come from. Machine learning incorporated in the fabric enables dynamic queries and data analytics, along with API management capabilities. This will help businesses to more easily gain critical insights from their data which they can deploy for a wide range of purposes, including new services and products.
By adopting a smart data fabric, businesses will gain access to clean, dependable data they can use for more advanced applications that meet the expectations of today’s consumers. These applications will use the data to adapt services to each customer’s personal preferences, history, and potential, optimising interactions and streamlining processes.
With this type of data architecture in place, even small AI implementations will help businesses demonstrate its value to overcome any internal cultural barriers. From here, it will become clearer with every application of AI just how much of an impact its adoption can have. Not only will it enable the business to offer increased personalisation to meet changing consumer expectations, but it will also give them the ability to adapt rapidly and more profitably to sudden shifts in demand – all of which will ultimately give them a strong competitive advantage.
About the Author
Jon Payne is Manager – Sales Engineering at InterSystems. InterSystems is the engine behind the world’s most important applications in healthcare, business and government. Everything we build is designed to drive better decisions, actions, and outcomes for the people who stake their lives and livelihoods on our technology. We are guided by the IRIS principle—that software should be interoperable, reliable, intuitive, and scalable.
Featured image: ©Paul