In recent years, artificial intelligence has moved from a fringe tool for enterprise to a technology with vast potential for business applications. In particular, products such as chatbots have demonstrated immense value to organisations, removing the need for humans in many customer interactions.

Dr Chitra Dorai, fellow and CTO of cognitive services, IBM

But this is only a minor part of what’s to come, and while much has been made of the automation side of AI, when it comes to using artificial intelligence to augment workers’ abilities and knowledge bases, businesses are currently under-utilising the technology’s potential. IBM, however, plans to change that.


“Our position is that the AI solutions we are building should help us reimagine the way we work, take out the time and give us better insight in order to equip us with confidence to make better decisions,” explains Dr Chitra Dorai, fellow and CTO of cognitive services at IBM, during a talk at Web Summit. “Therefore it’s all about augmenting our intelligence.”


Such a term has a distinct whiff of sci-fi about it, conjuring up images of brain-implanted workers that are part-computer and part-human. But augmented intelligence is not a twisted computer-driven fantasy, but instead a practical and valuable way to give workers ever-present support and insight that will make them better and more efficient at their jobs.


And with the first products already available in this space, its poised to become the next big AI-driven trend for enterprise.

Meet augmented intelligence: the next major enterprise AI trend

Augmented intelligence is not so much a new AI technology, but a new application that is, as Dorai puts it, “making our work, ordinary work, extraordinary”.


“We are at an important watershed moment where professions can be reimagined, professionals can reimagine the way they work with the assistance of AI systems helping us to do better, helping us to work more efficiently, more effectively, but at high quality,” she says.


“Think of a call centre agent fielding 25+ calls everyday, talking about complex subjects. They cannot have all the facts in their heads so often they put the callers on hold in order to go get details. 


“Think about a chatbot or a voice assistant whispering into their ears in response to the caller's question. Now they don't have to put the caller on hold, but rather appear competent because now they have these answers. And now we have taken the ordinary work of answering enquiries into the extraordinary because now the agents are performing at a much higher level of effectiveness.”

“We are at an important watershed moment where professionals can reimagine the way they work with the assistance of AI systems”

This approach keeps humans at the fore of the work, but equips them with unprecedented tools that allow them not only to be instant experts at the subject at hand, but also on a particular client, situation or scenario.


“The real excitement comes from infusing cognitive capabilities into the allocation. Imagine a system where there could be a chatbot or a voice assistant, whatever manner of chat it is, it collects data, understands the context of what the user wants,” she explains.


“And it is able to reason about that because it has a history of that person from previous interactions and be able to recommend the right kind of product and services, as well as pay back into the back-end systems in order to carry out the action on behalf of the user. 


“That's where the world is heading to. We are doing a number of projects with clients all over the world in terms of pushing that frontier of automation where the cognitive systems are collaborating with human beings in order to take the most effective positions.”

Contact centres: Keeping the human in customer support

One of the most immediate areas for this approach to AI to bring value is contact centres, and with products already available in this space, it’s clear this is a market that’s going to grow. 


IBM, for example, has developed what Dorai describes as agent assist software for contact centres in several markets, which demonstrate the potential of augmenting intelligence in this field. 


“Rather than putting chatbots in front of the customers, we are actually using chatbots to empower the agents with the right kinds of answers – so that they are always providing the right answers consistently and the right time of need – so the customer experiences improve,” she explains.


“We have developed the agent assist chatbots in many different domains. We know how to speak HR, procurement, travel etc, so in so many different domains we have been able to deploy these agent assist solutions.”

“Rather than putting chatbots in front of the customers, we are actually using chatbots to empower the agents with the right kinds of answers”

This type of approach has already shown significant operational value, cutting call times while improving customer feedback.


“We have found that we are able to shave off a minute of the calls on average and then customer satisfaction improves and issue reopen rate drops,” says Dorai. “So we are really finding the use of agent assist solutions making a real difference in the context of the transformation.” 

AI’s power to support enterprise decision making

While an obvious application of this technology is in contact centres, it also has very real potential in other aspects of enterprise. 


“The AI work doesn't stop at the front office, actually it goes beyond into the middle office, and also to the back office operations,” says Dorai.  


“We have actually taken procurement, finance and HR from current recruitment to development to HR operations, we have figured out the right kind of AI solutions that will make a big difference in the way practitioners work across the globe. And we've actually been able to show tangible business outcomes out of it, whether it is increasing the retention or reducing the recruitment time.”


Decision making, however, is one area that has particular potential, with better, more deeply insightful data being immediately provided to allow quicker and more reliable choices to be made.


“Think about a procurement specialist who has to understand what are the main positions of the big suppliers that they are working with. Currently they have lots of enterprise data about the supplier, about the history of the supplier, but what they don't know is whether there is a reputational risk associated with the supplier, whether the supplier is going through some mergers and acquisitions that is going to impact on the supply chain,” explains Dorai.


“All the externally available information currently needs to be manually trawled through by the procurement specialist so we can therefore imagine an AI system taking that place, looking through all the data, merging the externally available data with internal enterprise data and providing this holistic view of the suppliers so that the specialist can go and make the right decision.”

“Sometimes we have to be prompted about what might be lurking in the data, and often that leads to the proposal of the new business model or discovery of new products and services.”

While in earlier stages than contact centre-focused agent assist products, decision support is something that IBM believes is set to become a major market in the coming years. 


“The amount projected, we are seeing, is $2tn across many industries. There's so much to do here in terms of choosing the right kind of problem, the right process and reimagining the way people do their work,” she says. 


“And the current pattern is discovery. Discovery is very important, it's not always that we know what we are looking for: sometimes we have to be prompted about what might be lurking in the data, and often that leads to the proposal of the new business model or discovery of new products and services a company has to come up with.”


It’s clear that AI has potential for intelligence augmentation across many aspects of operations, with experts such as Dorai as the heart of their development.


“Yes, we're all excited about chatbots and voice assistants helping us order a pizza, but my passion is to go beyond that, to actually move AI, machine learning, cognitive computing into the very fabric of enterprises.”

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