In the year just gone, Alexa and Siri became pseudo personal assistants that put AI into everybody's pocket.
Yet in 2017, despite Amazon and Apple advancing the market, the vendor landscape will remain heterogeneous and fragmented, with use cases still scarce.
Rather, the next 12 months will see CIOs partner with marketing and CX colleagues to reap the benefits of AI, as it will increasingly be integrated into existing architectures and applications as a way to drive innovation throughout the year.
"Previously, any talk of AI almost always meant robots performing human tasks," ManageEngine vice-president, Sridhar Iyengar, recalled. "There was no talk about how such smart machines would be built."
In the 1990s, Iyengar said the AI conversation started to take the form of a "software brain" that could use data mining techniques to leverage data and discover meaningful patterns.
"But conversations are now focused around deep learning and machine learning," he observed. "Apart from discovering patterns, AI can make recommendations that businesses can use to strategise and win customers."
With AI set to become "commonplace in everyday life" by 2020 - Iyengar believes adoption will be driven by three key factors.
Firstly, data is not scarce anymore, with the copious amounts of information available helping to build quantitative models that make use of algorithmic techniques such as machine learning, deep learning and predictive analytics.
Secondly, computing power has become very affordable in the modern era, meaning that the once-expensive AI techniques are now in the reach of ordinary businesses.
Thirdly, Iyengar believes businesses are primarily motivated by providing the best customer experience possible, with AI capable of reacting and responding in real-time to meet changing requirements.
In short, data is the fuel for machine learning, with adoption driven by the ability to automate systems for recurring routine tasks, which translate to major productivity improvements.
"The shift is enabled by improved processing power, better algorithms, and the availability of big data - structured and unstructured - which is fundamentally changing the way humans and machines work together," SAP Innovation Centre Singapore vice-president, Christian Boos, said.
In addition, Boos said most use cases of AI in business fall into two categories - automating transactional knowledge work in shared services environments, and developing cognitive platforms simplifying employees' everyday lives and allowing them to focus on higher value tasks.
"Businesses should want to deliver enterprise software systems that can learn how to fully automate business processes at unprecedented levels, react to real-time changes and provide the best possible results for today's digital businesses," Boos added.
Customer demand pushes AI agenda
Across Australia, CIOs will have a greater need for speed in 2017, with customer demand expected to push businesses to the limit in the coming year.
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