Viswanath Ramaswamy, vice-president, Technology, IBM Technology Sales, India/South Asia
By Srinath Srinivasan
It is an accepted fact that the pandemic has accelerated the adoption of technology and, in particular, AI. According to IBM, reason behind this rapid adoption are the advancements in the technology which made it accessible, business needs and the change in business needs induced by the pandemic particularly.
“We are seeing focus on AI in every conversation with our clients; be it in BFSI, telecom, retail, manufacturing, consumer goods, auto, etc. The pandemic has forced enterprises to innovate,” says Viswanath Ramaswamy, vice-president, Technology, IBM Technology Sales, India/South Asia. According to IBM’s Global AI adoption Index 2021, over half (53%) of Indian IT professionals report their companies have accelerated rollout of AI due to the Covid-19 pandemic. Around 43% Indian IT professionals are most likely to say that the pandemic has increased their focus on security and threats.
The bigger picture is a growing market for advancements such as Natural Language Processing (NLP), automation and trust and security. “Most large enterprises are global and must operate in numerous languages. Language varies from country to country. As a result, enterprise NLP solutions must work in many languages and ideally without the need to undergo retraining for every language individually,” says Ramaswamy.
IBM Watson Discovery, which supports 10 languages including Hindi, can understand the meaning of Hindi text written in Devanagari script and extract useful information from it such as business, keywords, named entities, relationships, perform sentiment analysis. IBM Research India collaborated with IIT Bombay to lead this effort.
Trust allows organisations to understand and explain recommendations and outcomes and manage AI-led decisions in their business, which can be critical for regulatory requirements, while maintaining the full ownership and protection of data and insights. Some of the tools from IBM can help businesses monitor and mitigate bias. “We are helping financial services organisations build a trusted architecture based on data and AI solutions as the foundation for both end-to-end digitisation of core operations and the deployment of new digital services,” says Ramaswamy.
When it comes to automation, AI is used to simplify IT operations management and accelerate and automate problem resolution in complex modern IT environments. “Bharti Airtel has been working with us to integrate end-to-end advanced automation and plans to embed AI capabilities in the future as a core part of its network transformation. In this first phase, IBM and Airtel have co-developed a ‘single-click’ automated hybrid cloud design and deployment capability and ‘light touch’ operations,” says Ramaswamy. This enables Airtel to rapidly improve network connectivity and accelerate its continued core network transformation. As a result, Airtel will be able to scale to meet increased customer demand, onboard new partners more quickly, and speed the launch of innovative cloud-based services.
While AI has become more accessible than ever, the Global AI Adoption Index 2021 also found that lack of AI skills and increasing data complexity are cited as top challenges to adoption. It is a challenge to unify complex, siloed data across decentralised IT infrastructures, ensuring security and compliance of the data and technology, to build trust in AI systems and outcomes, and to develop a clear strategy with the appropriate skills and cross-functional teams to scale and support AI to meet business needs. “Let me provide some perspective here, AI requires machine learning; machine learning requires analytics; analytics requires the right data and information architecture (IA). In other words, there is no AI without IA . These capabilities form the solid rungs of what we call the AI Ladder – the increasing levels of analytic sophistication that lead to and buttress a thriving AI environment,” he explains.
Hence, it becomes a necessity to have the right architecture, capabilities and approach for businesses to overcome data complexity challenges. To tackle skilling challenges, with respect to India, IBM has collaborated with Central Board of Secondary Education (CBSE) to develop a curriculum on Artificial Intelligence, to be introduced as an elective subject for classes IX to XII. The pilot project was launched as part of the CBSE SEWA programme last year with the aim of reaching 200 schools across 13 states in India.
“We have covered 160 schools and over 12,000 students have benefitted from the programme,” says Ramaswamy. IBM has also collaborated with National Skill Development Corporation (NSDC) to offer ‘Open P-TECH’, a free digital education platform to users via NSDC’s eSkill India portal. “There has been over 2700 course completions and 400 hours of learning registered on the platform. Blockchain, Cybersecurity and AI are the most popular courses among learners—in sync with the demand for new collar job roles,” informs Ramaswamy.
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