While artificial intelligence (AI) has been slated to be the next big thing, its early use from the late 1980s to fairly recently was mostly for what we now call datamining. Its current popularity is different. We’ve had the required mathematics for several decades but now we have the requisite computing power as well.
We can store and process the vast amounts of data needed to adequately and widely drive value from the use of AI, and we’ve found myriad ways to use it.
Today, AI and the capabilities it delivers are playing an essential part in businesses, brought into stark highlight by the current global pandemic.
Across most industries we see that with sufficient data, AI can improve the quality of a business. In fact, in today’s caustic business environment, notably in the finance, food retail, and logistics industries, AI is needed to underpin organisational survival.
It is possible that the events of this year will form a cusp that forces organisations to revaluate their computing infrastructure investment.
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.
Where can AI be implemented to drive business?
Product development
Research from InterSystems found that currently, it takes 41% of UK organisations up to two weeks to process data, which leaves them ill-equipped to make 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 is a marked contrast to 41% of organisations that currently feed the data they generate back into the business weekly.
Faster insights would increase the opportunity to make timely decisions and respond to changes as needed, which under current circumstances is crucial.
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.
AI can also be used to analyse customer pre-sales questions and after-sales feedback to drive product development.
Businesses often already hold a wealth of data on how their customers use their products. AI can discern from the data those features that are being used and which aren’t, which can inform product development, sales training, customer documentation, and after-sales services to improve experiences.
Enterprises can reiterate their product and service designs to align ever closer to what its ideal customers want.
Indeed, perhaps the current downtime many organisations are experiencing provides an opportunity to explore unused data they already have.
As the crippling business effects of the pandemic subside, it seems as though those organisations that have experience of how to use AI to drive business transformation will be leaders in their markets.
Detecting patterns of behaviour
Whether used as predictive or prescriptive, AI can enhance decision making and detect patterns, especially in images or behaviour.
Retailers have for many decades used loyalty schemes to understand their customers’ shopping habits to target shoppers with offers and products that matched their persona profile.
However, they used data warehouses 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 retailers with a physical presence provide more convenient or differentiated customer experiences in order to encourage a return to the high street post-pandemic.
This is particularly important owing to the current circumstances requiring society to conduct every element of their life at home and largely online, resulting in online shopping growing by 129% week-on-week in the UK and Europe.
For some, this may form habits that will be hard to break, as they conclude that there is no need to go to the high street or superstore to shop.
Alternatively, with the physical shopping experience being temporarily denied, the restoring of normality could drive an increased number of people to go out shopping.
It is those businesses with an omnichannel capability, powered by AI insight, that will be best placed to capture and lead ahead of the rest.
Virtual customer interactions
According to Which?, more than a third of the UK’s bank branches have closed since 2015, while hundreds of those that remain have reduced opening hours, and recent events are only likely to accelerate the transformation of branch closures.
However, AI will be key to helping banks continue to deliver personalised and high-quality customer experiences online and over the phone.
The powerful combination of natural language processing, AI and ML is revolutionising the use of RPA, akin to the impact of the introduction of robots into factories.
As AI has become more intelligent, so too have chatbots. No longer are they merely able to answer basic customer queries via a website.
They now automate entire customer interactions. It is predicted that by 2022, banks will be able to use this technology to automate up to 90% of customer interactions.
One of the fundamental future trends is that AI will free most people of their basic or mundane work so that they create value within their organisation and forge closer relationships with customers.
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.
The seismic shift in the demand for data is married with a need for governance. We need to treat data as if it is money.
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, particularly 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.
Few foresaw what this year would bring, and few can predict how businesses will emerge afterwards.
The current environment in which businesses must operate won’t last forever. Organisations must also be prepared for the long tail of the pandemic.
What was already clear before the pandemic is that data-driven businesses can respond and adapt faster to significant disruption.
Over the coming months as organisations big and small navigate their existential challenges, using AI as a catalyst to adapt their operating models will become a clear business mandate.
Those who lack the computing infrastructure for AI with governance will find it hard to compete or even survive.
One lesson we can predict, is that the post-pandemic world will be littered with the remnants of those that refuse or are unable to evolve.
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July 17, 2020 at 03:04PM
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Succeeding in a new world: How to step up your IT strategy - Data Economy
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