It is early days for SAP on its machine learning journey, though. According to Noga: "We have screened over 180 machine learning use cases. The first wave prioritised horizontal apps near our core and we are currently prioritising a second layer and all spaces that are of value to our customers, such as the Internet of Things (IoT) and analytics, specifically predictive capabilities."
He adds: "We recognise that not every customer has machine-learning expertise, and they shouldn't need to. This is why we have an application-led strategy and ready-made solutions for the most pressing business problems and they deploy like any application. So you don't have to be an expert in how the app is designed."
Paul Chong, director of Watson Group EMEA at IBM told the AI Summit in London: "We want to get to this stage where you simplify the use of the technology to the point where you actually put it in the hands of the business owners."
IBM Watson was commercialised in 2015 and IBM has been working on bringing cognitive computing to business projects, with the likes of CitiGroup, Imperial College London, Under Armour and various healthcare organisations.
"We're creating the cognitive platform to be the API economy of choice for you to build cognitive systems. We're making this open, we believe there are a huge number of opportunities and I think about the number of clients we are working with and it is varied.
"Our hopes and aspirations are that the platform Watson, or others in terms of AI, will start to be infused through the API economy with all business processes. It won't be just the client or for the decision maker, it will be open to all," said Chong.
Adam Evans, CTO at cloud computing pioneer Salesforce.com, tells ComputerworldUK: "AI is technology that Salesforce is incredibly interested in. At Salesforce we have moved from systems of record to systems of engagement and now we are moving towards systems of intelligence."
Salesforce already has machine learning and predictive capabilities baked into products like its customer relationship management (CRM) platform SalesforceIQ, as well as Marketing Cloud Predictive Intelligence and the Service Cloud Intelligence Engine.
Evans explains: "SalesforceIQ's technology unifies customer data by leveraging data science to automatically capture, analyse and surface information and predict patterns, and then proactively recommends actions."
Some of the biggest enterprise software vendors are suspiciously quiet on the AI front. Obviously there are predictive capabilities with Oracle's database product if you have the right people in-house to leverage it, but the software giant has yet to launch any products or services with an obvious machine-learning layer.
Microsoft laid out its enterprise AI vision at Build 2016, and it seems like it is banking on bots, as well as investing in predictive capabilities to make its Cortana digital assistant even smarter through the Cortana Intelligence Suite for developers.
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