Despite being around since the late 1980s, until fairly recently, artificial intelligence (AI) has mostly been used for what we now consider to be datamining.
Today, thanks to having the required mathematics and computing power, AI is able to offer much more than that.
AI and the capabilities it delivers are playing an essential part in businesses, highlighted by the current global pandemic. With sufficient data, AI can improve the quality of a business’s decisions as demonstrated by its use within finance, food retail, and logistics industries, often underpinning organisational survival.
It is possible that the events of this year will form a cusp that forces organisations to revaluate their computing infrastructure investment. As a result, they will need to consider where they can apply technologies such as AI, machine learning (ML) and robotic process automation (RPA) to evolve their organisations and cater to ever-changing needs.
These are three areas in which AI can be implemented for significant business impact:
Our research found that it currently takes 41% of UK organisations up to two weeks to process data, which leaves them ill-equipped to make the quick decisions which could drive their business forward in rapidly evolving landscapes. By adopting an AI-driven business model, organisations could process data in real-time and feed that back into their business, which would be a marked improvement for the 41% of organisations that currently only do so weekly. Faster insights would increase the opportunity to make timely decisions and respond to changes as needed, which under current circumstances is crucial. For example, this will allow retailers to see and respond to surges in demand for products, such as toilet roll and antibacterial gel, or to increase the number of online delivery slots available to customers. By implementing AI in elements of their business, particularly, the supply chain, retailers and other organisations can be confident that they are able to keep up to date with and meet any fluctuations in demand.
Customer loyalty schemes
For many decades, retailers used loyalty schemes to understand their customers’ shopping habits to target them with offers and products that matched their persona profile. However, they used data lakes with consequential processes that took hours, days, and even weeks to complete. AI can transform such insight and response to affect immediate consumer buying decisions, as well as manage the end-to-end supply chain. These techniques will help bricks-and-mortar retailers provide more convenient or differentiated customer experiences to encourage a return to the high street post-pandemic.
With current circumstances requiring society to conduct every element of their life at home, online shopping has grown by 129% week-on-week in the UK and Europe. For some, this may become a lasting habit even when they are allowed to return to the high street, where as the restoring of normality could also drive increased numbers to go out shopping. It is those businesses with an omnichannel capability, powered by AI insight, that will be best placed to capture customers and lead ahead of the rest.
Virtual customer interactions
Recent events are likely to accelerate the transformation of bank branches and closures that have taken place over the last decade. As this happens, AI will be instrumental to helping banks continue to deliver personalised and high-quality customer experiences online and over the phone. As AI has become more intelligent, so too have chatbots. This means organisations can use the technology to automate entire customer interactions with banks predicted to able to use it to automate up to 90% of customer interactions by 2022.
This use of AI illustrates one of the fundamental future trends in which AI will free most people of basic or mundane work so that they can create value within their organisation and forge closer relationships with customers.
Looking to the future of AI in business
Data is the fuel of the overall economy, with information-based economies (info-economies) the new business landscape in which data brokers cut new paths. We need to treat data as if it is money. The seismic shift in the demand for data is married with a need for governance. Therefore, there needs to be an equal shift in business culture and strategy that plants AI into its core with the governance to manage its bias and quality. This is particularly important as Gartner predicts that by 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset. Without that balance, businesses will not be able to find and sustain their optimum position in this new world.
The pragmatic and disciplined use of AI will enable organisations to run their business better, and run a better business. As they adapt to the new normal in a post-pandemic society, this capability will prove invaluable.