Consumers expect it to be easy to do business online. Too often this is not the case, because companies have blind spots related to customer experiences, specifically where and with what customers struggle. When customers meet friction online, they get frustrated and abandon the site. Or if they are the really determined 1 percent, they reach out by emailing, chatting or calling. Make no mistake, no customer wants to contact a business.

The President and Chief Executive Officer of NEC Corporation India, Aalok Kumar, has recalled the significant contribution which the company has made with biometrics and other technologies on India's path to digital transformation in the last 70 years of the company's existence. Kumar spoke to Outlook Magazine ahead of the celebration of the 75th anniversary of India's independence celebrated on August 15. He highlighted how emerging technologies will help in shaping the future of the country, emphasizing the role of artificial intelligence-based technologies. Kumar said since 1956, NEC India has carried out projects aimed at connecting India to the global digital system. He explained that the Aadhaar biometric ID cards which Indians use today as proof of ID is built on their company's technology, which also enables multimodal biometric authentication for the Unique Identification Authority of India (UIDAI).

The banking sector's digital transformation journey has come a long way over the past five years. Today, technologies like machine learning (ML) and artificial intelligence (AI) are becoming much more commonplace in banks' digital strategies. Until the arrival of challenger banks like Monzo and Starling Bank a little over five years ago, who showed the benefits that taking a digital-first approach could bring, traditional banks failed to adopt the digital transformation at the same speed as other sectors. While the banking sector has come a long way in its digital journey in recent years, the slow pace of adoption initially has had a knock-on effect on the sector, with other industries now far more advanced in their digital approach. The industry was an early adopter of nascent technologies and as a result, it is now using ML to help with early detection of diseases like cancer. We conducted our own research into the banking industry's digital journey, to see where technologies like AI and ML were being used and, crucially, where they were not.

While healthcare organizations are on their digital journey to provide accessible, affordable and quality healthcare services, the COVID-19 pandemic aggravates the existing challenges faced by the sector. In addition to low doctor patient ratio and inadequate healthcare infrastructure, the pandemic resulted in shortage of beds, ventilators, insufficient testing capacity, resources, biosafety measures and a surge in patient contacts and queries, deepening the woes of the sector. As the pandemic redefines the new normal, healthcare organizations are accelerating their digital transformation journeys to be able to address the need for increasing tele consultations, remote diagnostics, customer support chatbots and wearable patient care. Here are my 10 picks for AI use cases that can be prove to be extremely useful (specifically amid the pandemic) and help organizations across the healthcare value chain advance through their digital journeys. Drug development – Healthcare organizations, specially pharma and life sciences players along with research centres are now heavily using AI to accelerate the drug discovery process which becomes even more critical in case of the COVID-19 vaccine Disease Simulation – AI is also being utilized to replicate the behaviour of disease causing microbes and organizations are seeing benefit in analysing it to help in coming up with possible cure of diseases Population health Insights – Use of AI to understand drug prescription patterns and propensity of diseases or comorbidities in case of COVID-19, predict drug demand and estimate potential market to ensure availability of required medicines Medical Image Analysis – AI-powered solutions for assisted medical imaging analysis tools for pathology, Radiology, radiotherapy, etc. and very useful amidst the pandemic Smart POS for pharma retail – An integrated AI and cloud based POS & billing solution for billing, payment, and inventory management, intelligent reporting, in-store marketing, and customer management for maintaining supply of required medicines Telemedicine – AI-powered analysis of patient symptoms remotely to deliver accurate prognosis post assessment of patients can assist doctors in making the diagnosis quicker and accurate Prognosis Assistant – AI-powered cognitive analysis to help in treatment selection, to recommend first actions and prognostic prediction. It also store patients’ medical records and share securely with doctors that helps in getting the correct diagnostic path Hospital Patient Flow – AI to determine the length of stay of patients and aid in discharge process that will also help in efficient management of hospital beds specially amid the pandemic Smart wearable sensors – Use of AI to link natural language and sensor data to identify potential health issues through changes in activity, communication and sleep patterns as tracked passively from handheld devices Patient Assistance Chatbot – Personal medical assistant app providing automatic answers to conversations, scheduling appointments, diagnosis & treatment, medical questions answering, medical image recognition, personalized medicine. NASSCOM Research, LHIF along with EY released a report titled “Unravelling AI for Healthcare in India” focusing on AI opportunities in the healthcare space. The report provides a unique periodic table of 150+ AI use cases across the healthcare value chain. The use cases identified in this article are also a part of the report. The report also highlights best practices across healthcare organizations that have implemented these use cases.

The advent of next generation technologies and the growing movement to be'Digital Ready' has resulted in rapid adoption of latest technologies in the business landscape of several organizations. The IT constitution of the organization needs to be in sync with this motion so that a holistic approach towards technology changes can be enabled. DRYiCE has carved out sate of art software products which ensure that your IT Ops is in sync with your technology strategy. Our exclusive products and platforms help enterprises operate in a leaner, faster, and cost-efficient manner while ensuring the achievement of business outcomes. We are sponsoring the Gartner IOCS Conference in Las Vegas at platinum level this year.

What are some of the key processes in which you are using AI? At PNB MetLife, technology enables us to align to two of our core values – 'Make Things Easier' and'Put Customer First'. Our strategy is structured around the concept of 3Ds – Digitise, Data and Disrupt. We digitise our day to day processes, which enables us in seamless customer delivery; we mine data and draw insights to mark predictable behaviour of the customers, thereby paving us the way to be future ready; we believe that the digital landscape is constantly evolving and hence we disrupt to keep our digital journey ongoing. Digital transformation had been a challenge for Indian companies for various reasons.

Summary: If you are guiding your company's digital journey, to what extent should you be advising them to adopt deep learning AI methods versus traditional and mature machine learning techniques. By now everyone is at least familiar with using AI/ML as a required cornerstone of company strategy. Frequently this is referred to as'digitization' or the'digital journey'. There's plenty of data showing that early adopters who have gone all-in on this approach are already pulling ahead of competitors both in share and bottom line results. There's also mounting evidence that even though most companies are now aware of this need, either their planning or their execution has been half-hearted.

Summary: Even if you're not big enough to have a full blown data science group that shouldn't hold you back from benefiting from AI. The market has evolved so that there are now industry and process specific vertical applications available from 3rd party AI vendors that you can implement. There are just a few things to look out for. Now that we are squarely in the midst of the exploitation phase of AI, pretty much everything you read will exhort you to hire a bunch of data scientists and get busy. This is not to make light of the top level commitment and organizational effort that's necessary to establish an Advanced Analytics and AI Center of Excellence in your company.

Like most businesses today, your company is probably looking at the possible cost and productivity improvements achievable through digital technologies such as Robotic Process Automation (RPA) and analytics. If so, it's important to understand that digital transformation is a journey of very deep and broad, company-wide change. Through our Pinnacle Model research on digital journeys, we at Everest Group assessed the impact on enterprises implementing RPA. Our study finds that, compared to other enterprises, Pinnacle Enterprises (companies that achieve superior business outcomes in digital journeys) achieve 4X the ROI compared to other enterprises implementing RPA, higher improvement in operational metrics and higher impact in strategic areas. What makes the difference in RPA outcomes for Pinnacle Enterprises?

You want to start an AI project – but what processes do you need to bear in mind, how do you manage the data, and what do you need to look at when it comes to team composition and testing? In this extract from Embracing the Power of AI, Javier Minhondo, Juan José López Murphy, Haldo Spontón, Martín Migoya, and Guibert Englebienne outline how to get through these crucial initial stages. Getting a grasp of the business needs is crucial, as is understanding the data sources. Are we thinking the solution centers on user needs or are we putting technology first? Going back to the key aspects discussed in Chapter 6 (see page 73), successful AI products must be driven and designed to help people access and process information, and facilitate decision-making.