From Tradition to Innovation: Industry Transformation in India

No ratings yet.

No ratings yet.

India is undergoing a remarkable transformation across various industries, driven by rapid technological advancements, evolving consumer preferences, and a dynamic economic landscape. From the integration of new-age technologies like GenAI to the adoption of sustainable practices, industries in India are redefining their operations and strategies to stay competitive and relevant.

Here are some organisations that are leading the way. 

Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India
Industry-Transformation-India-1
Industry-Transformation-India-2
Industry-Transformation-India-3
Industry-Transformation-India-4
Industry-Transformation-India-5
Industry-Transformation-India-6
Industry-Transformation-India-7
Industry-Transformation-India-8
previous arrowprevious arrow
next arrownext arrow
Industry-Transformation-India-1
Industry-Transformation-India-2
Industry-Transformation-India-3
Industry-Transformation-India-4
Industry-Transformation-India-5
Industry-Transformation-India-6
Industry-Transformation-India-7
Industry-Transformation-India-8
previous arrow
next arrow
Shadow

Download ‘From Tradition to Innovation: Industry Transformation in India’ as a PDF

Redefining Customer Experience in the Financial Sector

Financial inclusion. India’s largest bank, the State Bank of India, is leading financial inclusion with its YONO app, to enhance accessibility. Initial offerings include five core banking services: cash withdrawals, cash deposits, fund transfers, balance inquiries, and mini statements, with plans to include account opening and social security scheme enrollments.

Customer Experience. ICICI Bank leverages RPA to streamline repetitive tasks, enhancing customer service with its virtual assistant, iPal, for handling queries and transactions. HDFC Bank customer preference insights to offer tailored financial solutions, while Axis Bank embraces a cloud-first strategy to digitise its platform and improve customer interfaces.

Indian banks are also collaborating with fintechs to harness new technologies for better customer experiences. YES Bank has partnered with Paisabazaar to simplify loan applications, and Canara HSBC Life Insurance has teamed up with Artivatic.AI to enhance its insurance processes via an AI-driven platform.

Improving Healthcare Access

Indian healthcare organisations are harnessing technology to enhance efficiency, improve patient experiences, and enable remote care.

Apollo Hospitals has launched an automated patient monitoring system that alerts experts to health deteriorations, enabling timely interventions through remote monitoring. Manipal Hospitals’ video consultation app reduces emergency department pressure by providing medical advice, lab report access, bill payments, appointment bookings, and home healthcare requests, as well as home medication delivery and Fitbit monitoring. Omni Hospitals has also implemented AI-based telemedicine for enhanced patient engagement and remote monitoring.

The government is also driving the improvement of healthcare access. eSanjeevani is the world’s largest government-owned telemedicine system, with the capacity to handle up to a million patients a day.

Driving Retail Agility & Consumer Engagement

India’s Retail sector, the fourth largest globally, contributes over 10% of the nation’s GDP. To stay competitive and meet evolving consumer demands, Indian retailers are rapidly adopting digital technologies, from eCommerce platforms to AI.

Omnichannel Strategies. Reliance Retail integrates physical stores with digital platforms like JioMart to boost sales and customer engagement. Tata CLiQ’s “phygital” approach merges online and offline shopping for greater convenience while Shoppers Stop uses RFID and data analytics for improved in-store experiences, online shopping, and targeted marketing.

Retail AI. Flipkart’s AI-powered shopping assistant, Flippi uses ML for conversational product discovery and intuitive guidance. BigBasket employs IoT-led AI to optimise supply chain and improve product quality.

Reshaping the Automotive Landscape

Tech innovation, from AI/ML to connected vehicle technologies, is revolutionising the Automotive sector. This shift towards software-defined vehicles and predictive supply chain management underscores the industry’s commitment to efficiency, transparency, safety, and environmental sustainability.

Maruti Suzuki’s multi-pronged approach includes collaborating with over 60 startups through its MAIL program and engaging Accenture to drive tech change. Maruti has digitised 24 out of 26 customer touchpoints, tracking every interaction to enhance customer service. In the Auto OEM space, they are shifting to software-defined vehicles and operating models.

Tata Motors is leveraging cloud, AI/ML, and IoT to enhancing efficiency, improving safety, and driving sustainability across its operations. Key initiatives include connected vehicles, automated driving, dealer management, cybersecurity, electric powertrains, sustainability, and supply chain optimisation.

Streamlining India’s Logistics Sector

India’s logistics industry is on the cusp of a digital revolution as it embraces cutting-edge technologies to streamline processes and reduce environmental impact.

Automation and Predictive Analytics. Automation is transforming warehousing operations in India, with DHL India automating sortation centres to handle 6,000 shipments per hour. Predictive analytics is reshaping logistics decision-making, with Delhivery optimising delivery routes to ensure timely service.

Sustainable Practices. The logistics sector contributes one-third of global carbon emissions. To combat this, Amazon India will convert its delivery fleet to 100% EVs by 2030 to reduce emissions and fuel costs. Blue Energy Motors is also producing 10,000 heavy-duty LNG trucks annually for zero-emission logistics.

The Future of Industries
0
Expanding AI Applications: From Generative AI to Business Transformation

5/5 (3)

5/5 (3)

Generative AI has stolen the limelight in 2023 from nearly every other technology – and for good reason. The advances made by Generative AI providers have been incredible, with many human “thinking” processes now in line to be automated.  

But before we had Generative AI, there was the run-of-the-mill “traditional AI”. However, despite the traditional tag, these capabilities have a long way to run within your organisation. In fact, they are often easier to implement, have less risk (and more predictability) and are easier to generate business cases for. Traditional AI systems are often already embedded in many applications, systems, and processes, and can easily be purchased as-a-service from many providers.  

Traditional vs Generative AI

Unlocking the Potential of AI Across Industries 

Many organisations around the world are exploring AI solutions today, and the opportunities for improvement are significant: 

  • Manufacturers are designing, developing and testing in digital environments, relying on AI to predict product responses to stress and environments. In the future, Generative AI will be called upon to suggest improvements. 
  • Retailers are using AI to monitor customer behaviours and predict next steps. Algorithms are being used to drive the best outcome for the customer and the retailer, based on previous behaviours and trained outcomes. 
  • Transport and logistics businesses are using AI to minimise fuel usage and driver expenses while maximising delivery loads. Smart route planning and scheduling is ensuring timely deliveries while reducing costs and saving on vehicle maintenance. 
  • Warehouses are enhancing the safety of their environments and efficiently moving goods with AI. Through a combination of video analytics, connected IoT devices, and logistical software, they are maximising the potential of their limited space. 
  • Public infrastructure providers (such as shopping centres, public transport providers etc) are using AI to monitor public safety. Video analytics and sensors is helping safety and security teams take public safety beyond traditional human monitoring. 

AI Impacts Multiple Roles 

Even within the organisation, different lines of business expect different outcomes for AI implementations. 

  • IT teams are monitoring infrastructure, applications, and transactions – to better understand root-cause analysis and predict upcoming failures – using AI. In fact, AIOps, one of the fastest-growing areas of AI, yields substantial productivity gains for tech teams and boosts reliability for both customers and employees. 
  • Finance teams are leveraging AI to understand customer payment patterns and automate the issuance of invoices and reminders, a capability increasingly being integrated into modern finance systems. 
  • Sales teams are using AI to discover the best prospects to target and what offers they are most likely to respond to.  
  • Contact centres are monitoring calls, automating suggestions, summarising records, and scheduling follow-up actions through conversational AI. This is allowing to get agents up to speed in a shorter period, ensuring greater customer satisfaction and increased brand loyalty. 

Transitioning from Low-Risk to AI-Infused Growth 

These are just a tiny selection of the opportunities for AI. And few of these need testing or business cases – many of these capabilities are available out-of-the-box or out of the cloud. They don’t need deep analysis by risk, legal, or cybersecurity teams. They just need a champion to make the call and switch them on.  

One potential downside of Generative AI is that it is drawing unwarranted attention to well-established, low-risk AI applications. Many of these do not require much time from data scientists – and if they do, the challenge is often finding the data and creating the algorithm. Humans can typically understand the logic and rules that the models create – unlike Generative AI, where the outcome cannot be reverse-engineered. 

The opportunity today is to take advantage of the attention that LLMs and other Generative AI engines are getting to incorporate AI into every conceivable aspect of a business. When organisations understand the opportunities for productivity improvements, speed enhancement, better customer outcomes and improved business performance, the spend on AI capabilities will skyrocket. Ecosystm estimates that for most organisations, AI spend will be less than 5% of their total tech spend in 2024 – but it is likely to grow to over 20% within the next 4-5 years. 

AI Research and Reports
0