How AI and human-machine collaboration is driving transformation across sectorsTeam YS
Even a decade ago, the mention of Artificial Intelligence (AI) might refer to the fear that it would take away human jobs and render them expendable. Cut to the present and that fear has now been replaced with a more rational approach where AI is being seen as a way to extend human capabilities in an increasingly digital era.
The potential of AI to transform the way business is done and benefit individuals, communities and society as a whole is amply evident across a number of spheres – from recommendation engines that note customer preferences and suggest relevant items that they may want to buy, to chatbots that can enhance the customer experience to making healthcare and diagnostics more accurate and affordable, or even ensuring public safety.
When humans and machines collaborate, there is a lot more that can be achieved than when there is singular effort, and the following are just a few instances of how AI is helping redefine every aspect of our life.
Making everyday life easier and more efficient
When shopping online, you cannot miss those suggestions to buy items that pop up on your screen which seem to have an uncanny insight into your mind. Today, recommendation engines driven by AI and ML are a significant part of e-commerce, and play a huge role in the customer experience journey.
In the financial sector, AI is used across a variety of functions, from detecting and handling frauds, to assessing risks, and in advisory services, all of which work to ensure that your money is safe.
When we hail a cab or use the map feature on our smartphone to navigate, it is AI which is getting us to our destination. It’s the same when we ask our smart device to stream our favourite song.
In short, today, AI plays a big role across all aspects of everyday human lives: from how we shop, how we bank, commute or unwind.
Exploring a new frontier in healthcare
AI is completely changing how we look at and deal with health-related issues and patient outcomes. It brings into play more meaningful insights and more intelligent processes with a focus on reducing manual work, providing more accurate services and impactful interventions to patients, as well as long term savings for everyone involved.
From robotic surgeries for accurate and precise operations, to electronic health records easily accessible by all stakeholders, virtual health assistants which stay ahead in managing patients’ health, and accurate diagnostics, the emergence of use cases for AI in healthcare are on the rise.
Enhancing customer service through bots
Today’s customers expect an “always-on, always-me” experience. Here is where conversational bots, i.e.AI-powered messaging solutions, are saving the day. Users can interact with such bots, using voice or text, to access information, complete tasks or execute transactions.
In a survey by Accenture, 56% Of CIOs and CTOs surveyed said that conversational bots are driving disruption in their industry, while 57% agreed that conversational bots can deliver large ROI for minimal effort.
These bots are capable of performing complex tasks by combining one or more interfaces. With advancements in technology, in the future, bots will be able to act without human intervention and take relevant actions.
Despite the scepticism around bots on whether they will be able to appropriately incorporate history and context to create the personalised experiences desired by a customer and adequately understand what he or she requires via human input, businesses are embracing bots. Today, these virtual agents help enhance human agents’ productivity, deliver timely, conversational and contextual customer interactions and help resolve issues in a speedy and satisfactory manner.
Explainable AI to serve the ‘missing middle’ space in human-machine interaction
The rapid adoption of AI and related technologies notwithstanding, there will always be some jobs that will be done exclusively by humans. And then there are others which can be fully automated and taken care of by intelligent automation. But the maximum roles will see a combination of humans and machines working together. This space is something termed as “the missing middle” by Accenture
There are situations where an AI-driven decision on its own is not enough and we also need to know the reasons and rationale behind it. These roles will require people to apply their human skills and intelligence. Explainable AI complements and supports humans enabling them to make better, more accurate and faster decisions.
As collaboration between humans and machines increases, this space will see more action. For example, large enterprises have to manage a huge number of projects which means interacting with multiple vendors, clients and partners. The risks involved for each of these interactions is different, and often companies go wrong because of the complex nature of these interactions. Accenture Labs applied Explainable AI and developed a five-stage process to explain the risk tier of projects and contracts at each tier, along with valid reasons for these predictions, making it easier for decision makers to take more informed decisions.
Accenture Ventures’ Applied Intelligence Challenge
We have seen how AI’s footprint extends across industries, sectors and use cases, and helps make things better, faster and more efficient. Now let’s talk something even cooler: Applied Intelligence. Accenture’s unique approach to combining AI with data, analytics and automation helps transform businesses — not in silos, but more comprehensively across all functions and processes, helping them maximise existing investments, extending new technologies and scaling opportunities as they arise.
The second edition of Accenture Ventures ‘Applied Intelligence’ Challenge 2019 is looking for deep-tech growth stage start-ups with the most innovative Business to Business (B2B) use cases in Artificial Intelligence, Data, Analytics, Automation and Industrial AI.
For further updates on the challenge, visit https://events.yourstory.com/accentureventureschallenge2019.