Article by: Suman Nambiar, Head of AI Practice at Mindtree
The range of technologies that comprise artificial intelligence (AI), including natural language processing-driven bots, machine learning (ML) and deep learning, along with robotic process automation (RPA), are changing the ways in which business is done across a number of industries, from insurance, to legal and financial services, through to retail, travel, hospitality and transportation.
The impact of AI on these particular industries is hard to overstate. What we are seeing here across the board is far more than a trend. These technologies are revolutionising and re-inventing these industries in ways that go far beyond just automation – they are speeding up and reshaping existing business processes, while enabling new ones that were not possible earlier. Similarly, as some job roles disappear, many others will be created to help train, explain and sustain these algorithm-driven business processes.
Rarely a day goes by without a new story hitting the headlines relating to the impact that AI is having on specific industries or particular businesses. The range of opinions, from hype and excitement about the technology’s possibilities, to fear and apprehension about its negative impact on society, is evidence that AI is fast becoming one of the most misunderstood technologies of our time.
AI boosts efficiency in the legal profession
A recent story suggested that British legal firms can improve their efficiency by 50% by using the latest AI technologies available on the market. This bold proposition was made by a virtual data room provider called Drooms, who say that the legal sector has been considerably slower than many others in terms of adopting new methods of automating business processes, due to its conservative nature and inherent scepticism. While the hype around AI can be deafening at times, this often obscures the fact that enterprises are seeing real benefits from using these technologies, which are maturing rapidly.
As the area of Language Comprehension and Idea Learning progresses, driven by advances in deep learning, we see increasing potential for using AI in the legal industry. AI can help identify risks in contracts; flag up compliance issues across complex contracts; enable much quicker, more intelligent search of documents based on concepts rather than keywords or strings and even estimate the probability of legal actions succeeding or failing. A lot of these technologies are already out there – legal firms who experiment and adopt these ahead of the curve will see benefits in productivity and speed that outstrip their peer group.
Where threats to hourly billing models are concerned, firms that use these tools to improve the quality of advice and service to their clients are more likely to see the benefits in greater client loyalty. Furthermore, they will be in the best position to take advantage of the new kinds of jobs that the advent of AI will throw up, where clients will need expert advice to help them understand issues like agency, accountability, fairness and decision making in an algorithm-driven world.”
From business efficiencies to more exciting, personalised retail and travel experiences
The rapid growth and business adoption of AI is transforming lives and businesses globally, by helping companies to automate previously routine and monotonous tasks and by offering consumers a choice of much-improved, personalised experiences and services across the world.
When it comes to industries such as retail and travel, for example, it’s vital that businesses adopt the latest technologies to recognise and respond to the needs, wants and desires of their consumers. That’s why retailers and travel companies have been ahead of the curve over the last decade when it came to web and mobile e-commerce innovation. Amazon, AirBnB and Uber have completely changed the nature, perception of and consumer expectations around retail, hospitality and transportation.
While these companies have been using AI at the heart of their business for a while now,
other retailers and travel companies are discovering how to harness it to predict consumer preferences, to personalise services and stores, to complete bookings and sales and to address even unstated customer service needs.
In travel, for example, there are a number of opportunities for AI to help improve the customer experience. Firstly, biometrics and facial recognition technologies can remove the time-consuming need for documents to be checked at regular steps of a journey. Secondly, machine learning models can help predict consumer preferences at a granular level, enabling enterprises to construct a ‘360-degree view’ of the consumer in real-time, which then enables them to create hyper-personalised product and service offerings. The impact on conversion rates and customer loyalty can be transformational for the enterprise that implements these. Next, conversational apps and voice-driven virtual assistants are offering time-poor travellers a more personalised way to interact with organisations, to make bookings or to get specific information to meet a need in a particular time and place.
There are many more opportunities – automated social media analysing tools can provide travel companies with real-time insight into how their customers are feeling in a given situation and help companies to offer instant solutions to any problems their customers might be facing due to traffic problems, flight cancellations or one of the many other variables that can cause travel issues. And of course, predictive machine learning algorithms are transforming demand planning, operations, marketing and back-office operations across the entire enterprise.
How Big Data and AI are transforming financial services and insurance
It’s easy for modern consumers, travellers or holidaymakers to see and understand these latest AI-led developments in travel and retail, but what about in other industries. How, for example, is AI changing financial services and insurance?
The phenomenon of digitalisation, the spread of the Internet and particularly mobile computing over the past 20 years has resulted in the availability of enormous amounts of data, particularly in the financial and insurance domains, which is feeding the AI revolution.
It is almost impossible for humans to navigate this immense bank of data, let alone try to draw any meaningful insights from, or patterns in the data and that is exactly where AI comes in. Insurance companies, banks and financial services businesses are increasingly turning to automation, AI and machine learning-powered predictive analytics tools that use self-learning algorithms to continuously evolve with new data points and user analysis.
A great example here is Mindtree’s recent partnership with Tookitaki, a predictive analytics platform that demonstrably assists banks and financial services companies help businesses to make better decisions, faster and more efficiently. This particular partnership is enabling customers to save millions in security alerts and reconciliation management.
The insurance industry has also been cautious about adopting these technologies, but there is increasing awareness of the areas in which AI can make an immediate impact to the business. We see increasing adoption by insurers across different technologies, including robotic process automation (RPA), chatbots and personal/virtual assistants, machine learning, deep learning and natural language processing (NLP).
These technologies are helping insurers learn more about gaps in customer needs, in addition to cutting the costs to the customer and servicing their personal needs and requirements better than ever before. For example, Mindtree’s own conversational chatbot, MACAW, helps to provide quotes for life insurance products using Skype messenger and we have also developed a highly advanced ‘sales bot’ for use in the automobile insurance industry.
We’re also exploring the use of deep learning-driven computer vision algorithms, from areas like ‘reading’ forms with combinations of printed and handwritten text for faster forms processing, to assessing and rating automobile damages automatically based on submitted images for faster claims processing.
Machine learning models for fraud detection have of course been in operation for quite a few years; now they are also incorporating the ability to ingest unstructured data such as social media feeds to create more accurate predictive models.
As we’ve seen, the use of AI technologies is a reality today across different industries and enterprises. It is helping companies predict better, make better and faster decisions, serve their customers better with more personalised products and services, make routine processes faster and more efficient and unlock value in ways that were not possible before. It’s time to start using these in your business as well.
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