AN EYE FOR AI
We all know that AI (artificial intelligence) and machine learning are among the buzzwords that frequently come up in meetings or discussions around innovation and problem solving. It’s also heavily mooted as a key part of proposed requirements by some supply partners.
So, what is AI and how should it be approached to deliver organisational benefits? There are numerous definitions out there, so I’ve tried to take the best of what’s on the web and consolidate it.
• AI is designed to replicate cognitive tasks and/or simulate human intelligence.
• AI is often ‘trained’ for a particular requirement or task.
• AI systems can be defined as weak (narrow AI) or strong (artificial general intelligence), based on their ability to find a solution when presented with unfamiliar tasks and without the need for further human interaction.
We’re probably all using ‘AI’ in areas of our businesses already, without even realising it. Your marketing department is probably using AI-based applications for their online campaigns and social media activity. Many banking applications, in both our personal and business lives, have AI running in the background, and we use machine learning to help improve document production, and workflow and data management.
Only 8% of businesses consider themselves
digitally transformed. There’s still substantial scope to introduce new ways of working and better process automation across all sectors and business areas
And yet, only 8% of businesses consider themselves digitally transformed. There’s still substantial scope to introduce new ways of working and better process automation across all sectors and business areas. Gartner reports that global spend on AI is over $1.2bn (£990m) a year – which is considerable, particularly when you realise that is just a small section of the digital-workspace opportunity. So, where’s it all going?
McKinsey tells us that 45% of all work activities have the potential to be augmented with machine learning and AI – and consumers are receptive to the idea.
And 69% of customers say they would talk to a bot before a human in order to get instant answers – albeit only to a point, with around 67% of customers preferring agent-assisted customer services over a purely self-service model.
Because of the general public’s views around the perceived risks of AI (no doubt driven by Hollywood), there’s been a movement to refer to AI as ‘augmented intelligence’, to more realistically reflect the jobs it can perform. The data science community has also looked to put key principles in place around the design and use of AI tools. These include ethics, shared benefits, privacy and working for the common good. More information can
be found at The Future of Life Institute.
With all this hype, you could be forgiven for thinking we’re all just about to be replaced by robots. The truth is, thankfully, very different. The potential uses for AI in business are still yet to be fully recognised, and wanting to transition to a new way of working and actually delivering it are two very different propositions.
We need to fully engage with our technology partners – but we should do so with a longer-term view, and remember that people-based decisionmaking is still at the heart of how we innovate in business.
I borrow the last word on the subject from Roy Amara, whose adage is often called ‘Amara’s law’: we tend to overestimate the effect of a technology in the short run, and underestimate the effect in the long run.
This article can be found in Briefing’s September edition: Hot data
