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LONDON, UK - The basic concepts behind AI have been around for decades. But with today’s easy access to Big Data and cloud computing and new AI algorithms, adding cognitive capabilities to an enterprise is easier than ever.
Today, AI can comb through data sets to uncover hidden business insights, and it can do it much more quickly and at greater scale than can be done by humans. Which customers are most inclined to respond to which new offers? Where are an organization’s greatest sources of fraud risk? How should a pharma company direct drug discovery based on previous data and medical intelligence? Which university students are at the most risk of not graduating on time – and why? AI can provide the answers to questions like these.
Of course, insight without action delivers no value. The key is to look at AI as a component of a comprehensive strategy for intelligent automation that not only uncovers insights, but also orchestrates the actions resulting from those insights. Most of those actions will be carried out by human beings who can now make more effective and profitable decisions in real-time customer interactions. A sub-set of the actions resulting from AI insights may require no human intervention at all, and those can be executed via Robotic Process Automation or straight-through Business Process Management.
This intelligent automation perspective gives an organization the ability to use AI – and RPA, and chatbots, and anything else – primarily to augment how humans do the things they naturally do well, like making decisions and interacting with other people, while pushing the high-volume, repetitive, and error-prone drudge work to the digital workforce. Automation drove the Industrial Revolution. Intelligent automation is driving the Digital Revolution.
End-to-end intelligent automation means better enablement of people by advanced technologies. When you remove the burden of repetitive tasks from people, you'll find the workforce is happier and able to use their natural skills to provide a superior customer experience.
This combination of end-to-end automation and enhanced human interaction can ultimately create more personal and engaging customer interactions. That's what drives new revenue, ROI, and competitive advantage. At the same time, the business benefits from greater efficiency, more visibility, higher quality, and greater regulatory compliance - all of which reduce cost.
"Don't start out trying to create a sentient being. Use AI strategically."
However, although it is a trend that neither the C-Suite nor developers can afford to ignore, many enterprises are still discovering how to apply AI within their business. Part of the problem is scope. People want to jump right in and boil the ocean; create the self-driving car, or a fully autonomous robot. Businesses should start smaller.
Agile development techniques can be very valuable here. Understand your processes, data, and use cases while planning for a small-scale, iterative introduction of AI into business operations. With each delivery cycle, measure the results, see the impact of AI, and use that to raise awareness with the C-Suite on how AI can transform operations.
Many packaged cognitive services, such as optical character recognition, sentiment analysis, or speech to text, are very easy to implement. However, to leverage these appropriately, one must understand how each solution can fit within overall business processes and where it must be applied to accelerate intelligent automation.
Beyond plug-and-play cognitive services, organizations can start to explore custom machine learning algorithms to create unique predictive models based on their business data. Accessing the technology to enable this is straightforward, but understanding an organization's unique data and process requirements to apply machine learning to maximum impact remains the biggest challenge.
Organizations should approach this as they would common process improvement and automation exercises:
Don't start out trying to create a sentient being. Use AI strategically, and in areas that will help you to predict future behaviour and adapt your processes in real-time.
Ultimately, this evolving world of digital business requires both consumers and technology providers to look at things from a new perspective. Businesses must capture what Gartner calls 'business moments'; real-time, fleeting customer opportunities that organizations can exploit dynamically based on the interconnection of many different technologies, from the IoT and big data to cloud computing and machine learning.
What this means is that IT architectures need to be more fluid and agile in how they dynamically assemble and deliver services to the business and to customers. Those services are coming from many different vendors. For example, Appian provides native cognitive services like AI-based sentiment analysis, but our customers also want to benefit from huge investments by public cloud cognitive platform providers such as Google Cloud Platform, Amazon Web Services, and Microsoft Azure. We've made sure those integrations require no coding.
What's required now is an ecosystem of technology and business services. We believe we can play a central role in the smart orchestration of that ecosystem, and that's really what our AI-focused partnerships with KPMG, Genesys, and others are all about.
As told to Ciarán Daly
Malcolm Ross is the VP of Product Marketing at Appian. Malcolm has been directly involved in the management and implementation of enterprise software solutions for over 18 years. Malcolm is a frequent speaker and writer covering the application of BPM technology to solve real-world business problems. Catch Malcolm and the Appian team at The AI Summit London, June 13-14.