But what does “impact” actually mean? Many people use the term in a generic sense to describe some positive effect of a business or organisation. However, in the world of “impact investing”, impact has a specific meaning.
Impact is the ultimate large-scale contribution of a business, company or country to society including the environment.
This impact can be both positive and negative. It is fair to say that in the process of producing goods and services worldwide, positive and negative impacts are created simultaneously. The key question is whether the positive outweighs the negative.
#2 The Impact is Social or Environmental
As for a business, company, or country’s contribution to society, the UN Sustainable Development Goals are a solid framework are a solid framework for orientation. These are the pressing problems that once improved will lead to a more balanced and sustainable future.
Any company of any size and from any industry can easily identify which of the SDGs their products and services support.
By using references to certain SDGs organisations can then communicate their vision and mission more clearly to investors but also other relevant stakeholders such as governments, communities, suppliers, and consumers.
#3 The Impact is Long-Term
The “ultimate” aspect of impact refers to the fact that impact is not about immediate outputs or outcomes.
Impact is the long-term consequence and systemic change due to a continuous use of an organisation’s products and services.
If we take the example of a fintech solution that promotes financial literacy, transparency, or inclusive access to investing, the impact of that solution is not that people benefit from easier or faster financial transactions. Rather, it’s about creating new financial opportunities for a broader segment of the world population, potentially leading to greater economic empowerment for underserved groups – aligning with SDG 8 (Decent Work and Economic Growth) and SDG 5 (Gender Equality).
#4 The Impact is Scalable
The “large-scale” aspect of impact is critical for impact venture funds, as they seek to invest in scalable businesses that can amplify positive outcomes. Given the urgency of global challenges, there is no time or resources to spare on small-scale solutions. The geographic location of a startup or its initial focus on a specific region is irrelevant – what matters is its potential to grow and address pressing global issues efficiently.
If a product, service, or solution is sufficiently generic and easily scalable to reach a broader audience and various markets, the potential impact of that business will be appealing to impact venture funds.
#5 The Impact is Measurable
It is easy for organisations to remain vague or qualitative in their statements about impact, particularly when discussing the positive and charitable aspects of their actions.
If organisations are serious about creating change, they need to treat impact as an equal measure to profit.As Peter Drucker famously said, “If you can’t measure it, you can’t manage it”.
In the impact realm, deriving meaningful KPIs can be complex. Collaborating with an impact venture fund not only sets the expectations but also provides guidance to establish a transparent framework of KPIs to measure a business’s impact.
Ecosystm Opinion
Many believe only social businesses qualify for impact venture funding. In reality, any (tech) company solving societal or environmental issues is inherently impact-oriented. The key is awareness, measurement, and partnering with the right people.
Check out the websites and portfolios of impact venture funds – you’ll be surprised by the diverse areas and industries they support. Your startup might be the perfect match!
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 Bankleverages RPA to streamline repetitive tasks, enhancing customer service with its virtual assistant, iPal, for handling queries and transactions. HDFC Bankcustomer preference insights to offer tailored financial solutions, while Axis Bankembraces 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 Insurancehas 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 Hospitalshas 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 Hospitalshas 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 Retailintegrates 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’smulti-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 Motorsis 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 operationsin 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 Motorsis also producing 10,000 heavy-duty LNG trucks annually for zero-emission logistics.
Fuelling AI Innovation: India’s Strategic Investment
Earlier this year, the government allocated USD 1.3 billion for theIndia AI Mission, solidifying its commitment to AI. This comprehensive program is designed to catalyse the AI innovation ecosystem within the country. At the heart of this ecosystem’s development lies the expansion of compute infrastructure, a critical resource for AI startups. By providing access to powerful computing resources, the India AI Mission is empowering startups to scale their solutions and compete on a global level.
Beyond infrastructure, the initiative focuses on fostering collaborations between academia, industry, and startups to drive R&D. By creating a supportive environment that promotes knowledge sharing and resource accessibility, the India AI Mission aims to position India as a leader in the AI landscape.
A Spotlight on Indian Startups
Driving Industry Innovation
Healthcare.India’s vibrant AI startup ecosystem is driving innovation in healthcare, with companies leveraging AI to address critical challenges and improve patient outcomes.
Cancer-Focused AI Startups. Several startups are revolutionising cancer care with AI-driven innovations. Niramai, globally recognised for its innovation, uses AI and thermal imaging for early breast cancer detection, particularly effective in younger women and dense breast tissue. Onward Assist provides predictive analytics for oncology, helping oncologists manage patient data and improve the accuracy of cancer care decisions. Similarly, Atom360 focuses on oral cancer screening with an AI-powered app that offers quick, affordable access to critical information, enhancing oral healthcare in underserved areas.
AI-Driven Diagnostic Solutions. AI is significantly advancing diagnostics, enhancing accuracy, and reducing misdiagnosis. SigTuple develops AI-driven diagnostic solutions for medical imaging and pathology, improving accuracy and efficiency in disease detection. Endimension Technology, incubated at IIT Bombay, develops algorithms for detecting abnormalities in medical scans, aiming to reduce misdiagnosis and radiologist workload. Tricog Health delivers AI solutions for rapid heart attack diagnosis, reducing diagnosis time and improving outcomes, especially in underserved regions.
Financial Services. Fintechs have been at the forefront of AI-led innovations, offering innovative solutions for insurance, lending, and microfinance. Artivatic uses AI to transform traditional insurance systems into digital, personalised offerings, making coverage more accessible and affordable for a broader range of consumers. ZestMoney leverages AI for digital lending, providing credit to individuals without a credit history through easy EMI plans, and enhancing financial access. Meanwhile, mPokket offers instant micro-loans to students and young professionals, addressing short-term financial needs with flexible loan options and minimal documentation.
Other Industries. Beyond healthcare and financial services, AI startups are driving innovation across various industries, tackling critical challenges. Entropik uses AI to analyse human emotions and behaviour, helping businesses gain deeper insights into consumer preferences for market research and optimising user experiences. In agriculture, Intello Labs applies AI and computer vision to assess the quality of fresh produce, reducing food waste and improving supply chain efficiency. Similarly, AgNext enhances food value chains by offering AI-driven, real-time quality assessments through its SaaS platform, promoting safety and transparency in agribusiness.
Transforming Businesses
Technology for Security & Fraud. AI startups are offering innovative solutions tailored to organisations’ needs. SpoofSense combats deepfakes and identity fraud with advanced facial liveness detection, ensuring secure user verification by distinguishing between real users and spoofed images. Eagle Eye Networks provides cloud-based video surveillance solutions, using AI to offer real-time monitoring and analytics. In the e-commerce space, ThirdWatch uses AI to detect and prevent fraud in real-time by analysing user behaviour and transaction patterns, reducing financial losses for online retailers.
Tech Development. AI startups are empowering organisations to accelerate innovation and enhance productivity. Haptik helps businesses build intelligent virtual assistants, powering chatbots and voice bots across industries to improve customer engagement. DhiWise automates the development process, enabling faster app creation by converting designs into code. Additionally, Fluid AI provides advanced AI solutions like predictive analytics and natural language processing for sectors like finance, retail, and healthcare. Mihup enhances contact centre performance with its conversation intelligence platform, while Yellow.ai enables enterprises to automate customer engagement through its GenAI-powered platform, creating seamless and scalable customer service experiences.
Empowering People
AI startups are empowering individuals by providing personalised services that enhance learning, creativity, and financial management. SuperKalam and ZuAI offer students tailored learning experiences, using AI to create interactive lessons and assessments that adapt to individual learning styles, improving student engagement and outcomes. For creative professionals, Mugafi combines AI with human mentoring to assist writers in generating ideas and developing scripts, enabling them to create intellectual property with greater efficiency. Wright Research empowers individuals to make informed financial decisions through AI-powered investment advice, while Vahan simplifies job searches for blue-collar workers by using AI to match candidates with suitable employment opportunities via WhatsApp.
Promoting ESG
AI startups are driving meaningful change by optimising processes and creating economic opportunities. Ossus Biorenewables enhances biofuel production through AI, reducing waste and increasing efficiency in renewable energy generation, while Ishitva Robotic Systems promotes sustainability by automating waste sorting and recycling, contributing to a more efficient and circular economy. Karya connects rural workers with digital tasks, offering fair wages and skills development by matching them to tasks suited to their abilities using machine learning. In agriculture, KissanAI helps farmers improve crop yields and manage resources effectively through personalised, data-driven recommendations. ElasticRun improves last-mile delivery logistics in rural areas, enabling businesses to reach underserved markets.
Conclusion
Nvidia CEO Jensen Huang noted India’s potential to become the “largest exporter of AI,” signalling vast global opportunities. India’s AI startups are at the forefront of innovation but face hurdles such as fierce competition for skilled talent, navigating complex regulations, and securing funding. With strategic focus on these challenges and the backing of initiatives like Digital India and Startup India, India’s AI ecosystem can seize emerging market opportunities, accelerate tech advancements, and make a substantial impact on the global AI landscape.
Presenceless Layer.Aadhaar enables remote authentication, providing a digital ID that requires only a 12-digit number and a fingerprint or iris scan, eliminating the need for physical documents. It prevents duplicate and fake identities.
Paperless Layer.Reliance on digital records, using Aadhaar eKYC, eSign, and Digital Locker. It enables secure digital storage and retrieval, creating a paperless system for verifying and accessing documents anytime, on any device.
Cashless Layer. Led by NPCI, this aims to universalise digital payments. UPI enables instant, secure money transfers between bank accounts using a simple Virtual Payment Address (VPA), moving transactions into the digital age for transparency and ease of use.
Consent Layer. Enables secure, user-controlled data sharing through electronic consent, allowing data to flow freely. The Account Aggregator ecosystem benefits most, with AA acting as a thin data aggregation layer between Financial Information Providers (FIPs) and Financial Information Users (FIUs).
The Impact of the India Stack
The India Stack has played a pivotal role in the country’s rapid digitalisation:
Financial Inclusion.Aadhaar-enabled payment systems (AePS) and UPI have significantly expanded financial access, increasing inclusion from 25% in 2008 to 80% in 2024, particularly benefiting rural and underserved communities.
Boost to Digital Payments.The India Stack has fuelled exponential growth in digital payments, with UPI processing 10 billion monthly transactions. This has driven the rise of digital wallets, fintech platforms, and digitisation of small businesses.
Better Government Services. Aadhaar authentication has improved the delivery of government schemes like Direct Benefit Transfers (DBTs), Public Distribution System (PDS), and pensions, ensuring transparency and reducing leakages.
The India Stack: A Catalyst for Startup Success
The India Stack is fuelling startup innovation by providing a robust digital infrastructure. It enables entrepreneurs to build services like digital payments, eCommerce, and financial solutions for underserved populations. Platforms such as Aadhaar and UPI have paved the way for businesses to offer secure, seamless transactions, allowing startups like Paytm and BharatPe to thrive. These innovations are driving financial inclusion, empowering rural entrepreneurs, and creating opportunities in sectors like lending and healthtech, supported by global and domestic investments.
While India Stack has achieved significant success, there is still room for improvement. Strengthening data privacy and security is crucial as personal data collection continues to expand. The Digital Personal Data Protection Act aims to address these issues, but balancing innovation with privacy protection remains a challenge.
Bridging the digital divide by expanding Internet access and improving digital literacy, especially for rural and older populations, is key to ensuring that everyone can benefit from the India Stack’s advantages.
Data isn’t just a byproduct anymore; it’s the lifeblood of modern businesses, fuelling informed decisions and strategic growth. But with vast amounts of data, the challenge isn’t just managing it; it’s building trust. AI, once a beacon of hope, is now at risk without a reliable data foundation. Ecosystm research reveals that a staggering 66% of Indian tech leaders doubt their organisation’s data quality, and the problem of data silos is exacerbating this trust crisis.
At the Leaders Roundtable in Mumbai, I had the opportunity to moderate a discussion among data and digital leaders on the critical components of building trust in data and leveraging it to drive business value. The consensus was that building trust requires a comprehensive strategy that addresses the complexities of data management and positions the organisation for future success. Here are the key strategies that are essential for achieving these goals.
1. Adopting a Unified Data Approach
Organisations are facing a growing wave of complex workloads and business initiatives. To manage this expansion, IT teams are turning to multi-cloud, SaaS, and hybrid environments. However, this diverse landscape introduces new challenges, such as data silos, security vulnerabilities, and difficulties in ensuring interoperability between systems.
A unified data strategy is crucial to overcome these challenges. By ensuring platform consistency, robust security, and seamless data integration, organisations can simplify data management, enhance security, and align with business goals – driving informed decisions, innovation, and long-term success.
Real-time data integration is essential for timely data availability, enabling organisations to make data-driven decisions quickly and effectively. By integrating data from various sources in real-time, businesses can gain valuable insights into their operations, identify trends, and respond to changing market conditions.
Organisations that are able to integrate their IT and operational technology (OT) systems find their data accuracy increasing. By combining IT’s digital data management expertise with OT’s real-time operational insights, organisations can ensure more accurate, timely, and actionable data. This integration enables continuous monitoring and analysis of operational data, leading to faster identification of errors, more precise decision-making, and optimised processes.
2. Enhancing Data Quality with Automation and Collaboration
As the volume and complexity of data continue to grow, ensuring high data quality is essential for organisations to make accurate decisions and to drive trust in data-driven solutions. Automated data quality tools are useful for cleansing and standardising data to eliminate errors and inconsistencies.
As mentioned earlier, integrating IT and OT systems can help organisations improve operational efficiency and resilience. By leveraging data-driven insights, businesses can identify bottlenecks, optimise workflows, and proactively address potential issues before they escalate. This can lead to cost savings, increased productivity, and improved customer satisfaction.
However, while automation technologies can help, organisations must also invest in training employees in data management, data visualisation, and data governance.
3. Modernising Data Infrastructure for Agility and Innovation
In today’s fast-paced business landscape, agility is paramount. Modernising data infrastructure is essential to remain competitive – the right digital infrastructure focuses on optimising costs, boosting capacity and agility, and maximising data leverage, all while safeguarding the organisation from cyber threats. This involves migrating data lakes and warehouses to cloud platforms and adopting advanced analytics tools. However, modernisation efforts must be aligned with specific business goals, such as enhancing customer experiences, optimising operations, or driving innovation. A well-modernised data environment not only improves agility but also lays the foundation for future innovations.
Technology leaders must assess whether their data architecture supports the organisation’s evolving data requirements, considering factors such as data flows, necessary management systems, processing operations, and AI applications. The ideal data architecture should be tailored to the organisation’s specific needs, considering current and future data demands, available skills, costs, and scalability.
4. Strengthening Data Governance with a Structured Approach
Data governance is crucial for establishing trust in data, and providing a framework to manage its quality, integrity, and security throughout its lifecycle. By setting clear policies and processes, organisations can build confidence in their data, support informed decision-making, and foster stakeholder trust.
A key component of data governance is data lineage – the ability to trace the history and transformation of data from its source to its final use. Understanding this journey helps organisations verify data accuracy and integrity, ensure compliance with regulatory requirements and internal policies, improve data quality by proactively addressing issues, and enhance decision-making through context and transparency.
A tiered data governance structure, with strategic oversight at the executive level and operational tasks managed by dedicated data governance councils, ensures that data governance aligns with broader organisational goals and is implemented effectively.
Are You Ready for the Future of AI?
The ultimate goal of your data management and discovery mechanisms is to ensure that you are advancing at pace with the industry. The analytics landscape is undergoing a profound transformation, promising to revolutionise how organisations interact with data. A key innovation, the data fabric, is enabling organisations to analyse unstructured data, where the true value often lies, resulting in cleaner and more reliable data models.
GenAI has emerged as another game-changer, empowering employees across the organisation to become citizen data scientists. This democratisation of data analytics allows for a broader range of insights and fosters a more data-driven culture. Organisations can leverage GenAI to automate tasks, generate new ideas, and uncover hidden patterns in their data.
The shift from traditional dashboards to real-time conversational tools is also reshaping how data insights are delivered and acted upon. These tools enable users to ask questions in natural language, receiving immediate and relevant answers based on the underlying data. This conversational approach makes data more accessible and actionable, empowering employees to make data-driven decisions at all levels of the organisation.
To fully capitalise on these advancements, organisations need to reassess their AI/ML strategies. By ensuring that their tech initiatives align with their broader business objectives and deliver tangible returns on investment, organisations can unlock the full potential of data-driven insights and gain a competitive edge. It is equally important to build trust in AI initiatives, through a strong data foundation. This involves ensuring data quality, accuracy, and consistency, as well as implementing robust data governance practices. A solid data foundation provides the necessary groundwork for AI and GenAI models to deliver reliable and valuable insights.
