ARTIFICIAL INTELLIGENCE LANDSCAPE



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ARTIFICIAL INTELLIGENCE LANDSCAPE

Thought Leadership Article

Wikipedia defines Artificial intelligence (AI), as an intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals. It involves four approaches- thinking humanly and rationally, acting humanly and rationally. AI can automate iterative tasks, Real-world modelling, quantum and cloud computing and perform efficient statistical calculations. Key AI trends for 2021 such as RPA, AI-enabled chatbots offering personalized services leveraging NLP and ML will increase, AI-powered chips offering detailed predictive analytics aids in cybersecurity early detection and prevention as digital data exposes further.

Source: Accenture

MARKET TRENDS

According to research firm, IDC, India’s AI spending is likely to grow from USD 300.7 Mn in 2019 to USD 880.5Mn in 2023 at a CAGR of 30.8% as enterprises are developing AI strategies to explore new businesses. Cloud-enabled AI algorithms will cater to industry-specific tech solutions like Analytics Products, Computer Vision, Internet of Things (IoT)/ Logistics, Robotics, Blockchain and Natural Language Processing. BFSI and manufacturing sector spend 37% of the total AI spending in 2019 across its different use cases.

Key growth drivers of Indian AI market are rising adoption of new technologies to improve R&D by industries, such as retail, defense, oil & gas, and manufacturing; development in Artificial Neural Networks to enhance decision-making, problem-solving, cost-competitive accessibility to historical data that contribute more to GDP. Government initiatives like Aadhar Enabled Payment System, National Mission in Education through ICT, Digital India are propelling AI market growth.

Source- Statista, AI market share by industry in India, 2020

AI MARKET IN INDIA BY END-USER EXPECTATIONS

In realizing PM Modi’s bold vision to make India a $5 trillion economy by 2024–25 while ensuring sustainable and inclusive development, will require Data and AI to increase investment, consumption and exports across major sectors such as agriculture, tourism, energy, logistics and financial services. According to PwC’s survey report 2018, 71% respondents believe that AI will help humans solve complex problems and live richer lives; 58–74% said that AI will aid economic growth, cyber security & global health; 83% business leaders think that AI advisors at work will be more or equally fair. Though for personal health check-ups (77%) and education (61%), respondents prefer involvement of human experts alongside AI run customer service.

End users expects real-time monitoring of Healthcare Patient Data & Risk Analysis, Lifestyle Management & Monitoring, Precision Medicine, Inpatient Care & Hospital Management, Medical Imaging & Diagnostics, Drug Discovery & Research, Virtual Assistant and Wearables. In Manufacturing sector, AI can transform Material Movement, Predictive Maintenance and Machinery Inspection, Production Planning and improve Quality Control. In Agriculture market, AI is leveraging data for Precision Farming, Livestock Monitoring, Drone Analytics, Production planning using soil mapping and crop prices, Crop failure prediction to optimize food supply planning, determine subsidies, and protect farmer income.

Source: Ruling party Government Manifesto, Government of India Press Information Bureau, Role of Data and AI in realizing the PM’s vision for India by 2025

India’s “AI for All” strategy focuses on AI-based solutions across agriculture support through (Jal Shakti Abhiyan) water management, crop insurance, image recognition, automated intelligent monitoring of irrigation systems, vernacular language support, weather sensing technology to give farm level advisories developed by ICRISAT, which led to an increase in yield from 10–30% for farmers. Moreover, AI is contributing to COVID-19 response with economic recovery through workforce planning, Predictive logistics planning processes, real time Financial reporting, cash flow and liquidity, digital sales interface, digitization of operations to credit business loans to SMEs and farmers. In Retail segment, Predictive analytics is targeting personalized campaigns using customer data and aware of counterfeit products via blockchain-enabled tracking, additionally AI offers Product Recommendation, Virtual Assistant, Visual Search, Price Optimization, Payment Services Management, Supply Chain Management and Demand Planning to MSMEs. Defense industry is preparing AI use cases across Warfare Platform increasing Cyber Security, Target Recognition, Simulation & Training, Threat Monitoring & Situational Awareness and battlefield healthcare.

Source: India’s Trillion Dollar Digital Opportunity, Feb 2019 (MeitY); Potential contribution of Data and AI to India’s GDP by 2025

KEY VERTICALS

Source- imarc, AI market key verticals

The major surge in adoption of AI software across industries is due to its advanced information capacity, high computing power, parallel processing capacities. Based on technology, AI market is segmented into natural language processing (NLP), computer vision and machine learning. Industries such as healthcare, automotive, BFSI, and education are rapidly implementing ML technology in R&D that involves hypothesis generation, clustering, filtering, visualization and navigation.

Based on end-user, the AI market comprises of manufacturing, healthcare, retail, automotive, security, agriculture, marketing, law, fintech, construction, defense, supply chain, aerospace, food & beverage, building automation, gaming, telecommunication, media & entertainment, and oil & gas. Aster DM, a healthcare unit in India is connecting hospitals by providing AI-based decision support systems for the workers, playing a significant role in AI market growth in healthcare segment.

KEY USE CASES

AI in Telecom

Telecom sector with a market share of 2.2% contributes $138 Mn to the AI market and includes MNCs such as Verizon, Reliance Jio Infocomm, Airtel, and Tata Communications that develop IoT, 5G connectivity solutions etc. AI is adopted by the Telecom firms across the Telecom value-chain and various use cases:

  • Telecom Networks: Collaboration on AI in Core Networks with Network Equipment firms — Ericsson and Nokia
  • Edge Computing: Telecom firms are collaborating on AI with MS (Azure) and AWS for Mobile Edge Computing and Network Virtualization
  • Connectivity Solutions: Building Connected Cars, Smart Devices, Smart Homes, Private Networks, IoT Platforms, and Smart Cities
  • Consumer Plans and Customer Services: AI can make informed decisions of best plans for consumers, and provide quick response and personalized experience through SMS, App, and Push Notifications

AI in Energy

It includes energy system modelling and forecasting to reduce unpredictability and enhance power balancing efficiency. In renewable energy systems, AI can allow storage of energy through intelligent grids by smart meters, and also improve the reliability and affordability of photovoltaic energy.

AI in Healthcare

Source- PWC, “No longer science fiction, AI and robotics are transforming healthcare”

ROLE OF SECURITY IN AI

According to Cybersecurity Ventures, the cost of cybercrime is projected to reach $6 trillion annually by 2021, up from $3 trillion in 2015. Gartner reports that global information security market is projected to grow at a five-year CAGR of 8.5% to reach $170.4 billion in 2022. In 2019, Accenture research survey mentioned that 68% of business leaders felt cybersecurity risks are growing.

AI in security can identity and execute Risk and Compliance Management, Encryption, Antivirus/Antimalware and aid in Intrusion Detection/Prevention Systems. AI through machine learning and deep learning techniques is trained to analyze billions of data from both structured and unstructured sources and hence “understand” cybersecurity threats and risk. By interpreting threats, such as malicious files, suspicious IP addresses within seconds or minutes, security analysts can respond to threats up to 60x faster.

AI can prevent cyberattacks but in reality, AI is a double-edged sword and 23% respondents reported loss of privacy issue in AI based customer service as per Statista report, 2018.

Source- Statista, Key concerns associated with artificial intelligence (AI) based customer service in India, 2018

VENDORS LANDSCAPE

India, 2nd largest exporter of ICT services, with 4.4 Mn employees comprising of 500,000 in AI/ML. The demand for setting up big data and AI CoEs in India is rising because of COVID-19 led distancing and digitization. NASSCOM in 2018 indicated that 1,200 new advanced technology start-ups have ventured with data analytics as the most significant contributor. AI Services market is currently dominated by Big 4 and Accenture with revenues (>$100 Mn), mid-sized AI firms, and boutique vendors like BRIDGEi2i, Cartesian Consulting, Tech Mahindra, Virtusa, Mu Sigma, Fractal Analytics, NTT Data, KPMG, Capgemini, Cognizant, NEC drawing revenues ($20 — $100 Mn).

AI-as-a-Service will be a preferred delivery model that enables rapid, cost-saving onboarding of AI cognitive capabilities and accelerators without having to worry about the underlying AI hardware/infra components. Another example of AIaaS is when providers offer several Deep Learning and Machine Learning algorithms through a tie-up with AWS Machine Learning Marketplace.

AI-as-a-Solution are custom-built boutique vendors that deliver production-level AI solutions deployed on-premise or on cloud infrastructure and involve industry domain expertise, follows iterative agile methodology to deliver business value.

AI-as-a-Product- when AI software is customized as needs of an enterprise, e.g.- BRIDGEi2i’s sales enablement product BRIDGEFunnel which leverages proprietary accelerators WatchtowerTM & RecommenderTM to offer deep insights with real-time alerts.

The way forward for AI consultancies is to differentiate in terms of sizeable AI workforce, best-in-class solutions with domain expertise, across multiple sectors and geographies.

REFERENCES

Nasscom, NITI, PwC, Invest India, Accenture insights

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