As consumers continue to demand increasing personalisation of services, businesses are under growing pressure to answer this desire and those who are unable to deliver, due to a lack of agility, will likely fall to the wayside, becoming less meaningful to consumers.
Artificial intelligence (AI) has been shown to be effective at helping businesses to respond to consumers’ changing requirements and make it easier for them to get the goods and services they want, says Jon Payne manager sales engineering at InterSystems.
But this technology is also giving people access to streamlined online tools which enable them to tailor products and services to their own personal preferences on demand. Within the travel industry, in particular, this is becoming the norm as online platforms allow consumers to build their perfect get-away by sourcing different options for flights, hotels, and car rentals, for example threatening the traditional package holiday.
As such, 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.
This requires 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. Of course, it must also be accurate and relevant.
Democratisation of AI
Although the majority of businesses know they should be using AI to provide better and more personalised services, putting it into practice can be challenging. This is often because they lack the understanding of data science to train and develop AI models, while many do not collect enough data or understand what kind of data they should be collecting.
Many businesses are also unaware of where they should be applying 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. Meanwhile, those closer to the shopfloor may want change but fear the implementation of AI is full of risks. Consequently, businesses are left contemplating how to adopt the right solutions.
In small or medium-sized businesses, leaders often see no role for AI in what they do and collect very little data. They may not see how predictive capabilities would help them prepare better for seasonal variations, or for events and trends that trigger surges or troughs in supply and demand.
Broad-scale adoption of AI is often very difficult for people to understand, especially if they work outside the digital technology sector. Smaller businesses need access to more pre-built, off-the-shelf AI solutions that make it easier for them to implement. To democratise AI, software and solutions providers need to build in capabilities that enable more businesses to realise its significant benefits in their day-to-day operations.
Harnessing data to power AI
Data remains a significant barrier to AI adoption. An AI solution is only as good as its training model, but many organisations still do not know how to obtain the quality and quantities of data required to feed such models. To overcome this issue and gain the capabilities to fully leverage their data, organisations should look to smart data fabrics, a new architectural approach.
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.
Implementing a smart data fabric will give businesses access to clean, dependable data they can use for more advanced applications that meet the expectations of today’s customers. Applications will use the data to adapt services to each customer’s preferences, history, and potential, optimising interactions and streamlining processes.
After taking the necessary steps to change how they approach and manage their data, even small AI implementations will help businesses demonstrate the value of the technology to overcome internal cultural barriers.
With every application of AI it will be clearer to everyone from those in the boardroom to employees on the frontline of the impact its adoption can have, from enabling the business to meet the changing consumer expectations, to adapting rapidly and more profitably to sudden shifts in demand.
The author is Jon Payne manager sales engineering at InterSystems.
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