Suddenly, everyone is talking about artificial intelligence (AI). This has been seen first-hand at Ceterna in the ongoing discussion and debate that the launch of Salesforce Einstein continues to generate.
The difference between AI as ‘next big thing’, however, and, say, the cloud, big data or any other widely-discussed technology, is that AI discussions go a long way beyond the IT, and even the sales and marketing departments. This time, the topic is being hotly debated by sociologists, economists and even politicians.
Everyone has heard the dire warnings predicting job losses. A recent research note produced by the Oxford Martin Group and Citi, “Technology at work: V2.0″, concluded that 35% of jobs in the UK are at risk of being replaced by automation, 47% of US jobs are at risk, and across the OECD as a whole an average of 57% of jobs are at risk. In 2015, the Bank of England chief economist, Andy Haldane warned that up to 15 million jobs in Britain are at risk of being lost to an age of robots.
>See also: Artificial intelligence could add ‘£232BN to UK GDP by 2030’
However, future employment prospects are far less bleak than this implies. After all, there is still a huge gap between all the highly advanced AI work and typical organisations, most of which will have heard of AI, but don’t really have any idea how they would use it. Most wouldn’t be able to afford AI at the moment anyway, because the knowledge and infrastructure demands are just too huge.
That’s frustrating of course because the positive potential of AI in business is considerable (and starting to be realised by the early adopters) – from speech recognition systems to help deliver secure banking to machine learning algorithms that provide users with relevant content.
So is there a way to make AI practical and within reach of most companies not just the technological pacesetters? The tech giants – Amazon, Google and Salesforce, for example – are certainly working on it while at the same time building their knowledge of the commerciality of the technology and how it can support their respective platforms. They have their research and development teams and have targeted appropriate acquisitions.
They see the technology working as decision support, adding value to the workforce and helping to meet strategic goals and drive business advantage – not to completely take over the world.
>See also: A trillion dollar industry: the economic impact of AI on CRM
But, however advanced and complex they are, technologies only really reach the mass market when they become streamlined and the knotty challenges ironed out, so there’s no need for highly-skilled but also highly-paid experts such as data scientists to develop and customise.
Albert Einstein’s quote: ‘the definition of genius is taking the complex and making it simple,” is highly apposite here. This is why Salesforce has named its AI technology after the great man and has decided to include it as an integral part of its CRM and other software.
This now puts AI capabilities in the hands of all customers. Powered by advanced machine learning, deep learning, predictive analytics, natural language processing and smart data discovery, Einstein’s models will be automatically customised for every business. It will learn, self-tune and become smarter with every interaction and additional piece of data. Its intelligence will be embedded within the context of the business, automatically discovering relevant insights, predicting future behaviour and proactively recommending next best actions.
For example, Einstein might be monitoring the LinkedIn pages or other social media of a prospect. It alerts its company that this prospect has hired a new sales director or some other news, giving the company the opportunity to contact its target. Or suppose you are about to close a sale, but have an inkling that things may not be smooth-sailing. Einstein might inform you that there’s no email traffic or phone calls and your contact has just requested to become a LinkedIn contact with a competitor.
>See also: Making business smarter: 3 misconceptions about AI
On the marketing cloud side, Einstein will again analyse social media to measure customer sentiment and suggest the best targets. Manufacturers will be able to use it in conjunction with the Internet of Things, quickly pinpointing, for example, not just that devices are failing, but in what area this is happening and what might be the cause.
Even for Einstein, it’s still early days. Salesforce may be the first of the big names to consolidate all their acquisitions and bring the results to market but the software is still evolving and will, no doubt continue to do so. Salesforce partners have a huge role to play here in working with customers to first show them that AI will complement their skills to help them work and act smarter and then help them implement the technology in the best way for their organisation.
The best way to do this is to give real-life scenarios where Einstein could help them become more productive. For example, what if their whole day was scheduled and rearranged depending on traffic? Einstein could even send out emails to make new appointments – so not replacing people, only complementing their lives.
>See also: The value of artificial intelligence in business
It’s not surprising that some organisations are wary. The business world has been battered by successive waves of new technologies over the past few years and AI could ultimately prove to be the tsunami of them all. But this is very unlikely – and failing to embrace it could mean missing out on an opportunity for early transformation.
Sourced from Sean Harrison-Smith, managing director, Ceterna
