Which areas of business can we expect AI to transform in the next decade? Almost all of them, experts say. Here’s half a dozen to start the revolution.
Copyright: technologymagazine.com – “Six of the best future uses for artificial intelligence”
Artificial intelligence (AI) has secured its ‘must-have’ technology status, enabling companies to move faster and further than rivals to sharpen predictions, boost efficiencies, and optimise real-time pricing or stock control.
But as we wrote in the November issue of Technology Magazine, most boardrooms and bosses don’t yet fully understand the potential use-cases for AI and machine learning (ML). “Stakeholders often don’t know what to ask for in order to get the right benefits out of the technology,” says Elliott Young, CTO, Dell Technologies UK. “This means they don’t really know what their business could be missing out on.”
Overhyped AI scares people and masks the real benefits these technologies can offer, says Anthony J. Bradley, Gartner’s Group Vice President of Emerging Technologies and Trends Research. “This can lead to slower adoption, and even sociopolitical fear and government regulation that will stifle progress.”
We take a closer look at six sectors that will attract a lot of future attention.
Predictions and forecasting
AI is migrating from its position as a technology identifying relationships in data and predicting existing trends more accurately to a technology that spots future shifts in everything – from leisure spending and travel patterns to company creditworthiness – by analysing preferences and sentiments, says Sian Townson, Partner, Oliver Wyman.
“As AI model explainability improves, along with more reliable ways to monitor performance, robustness and fairness, these more complex models have in turn become more reliable with their methods and results more understandable, hence more feasible and creative applications,” she explains. “AI can recognise disruptors by making connections between embedded characteristics.”
Risk and insurance
Boosting efficiencies and fairness in areas such as credit risk, insurance, human resources, and conducting surveillance, machine learning (ML) will read through forms and review voice and video recordings, highlighting where the reviewer’s attention should be focused, how a call should be routed, or simply if an attachment has been forgotten, details Oliver Wyman’s Townson.
“AI is currently used to automate customer-facing steps, from chatbots to processing an order; some companies will also use it to improve their customer service, actually making processes more transparent and objective.”
Advances in quantifying fairness and mitigating bias allow AI-based approaches to be more equitable, transparent and objective than previous human attempts – even if quantifying fairness can sometimes be a painful first step, says Townson.[…]
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