Naveen Kamat is the Executive Director for GTS Data and AI Services at IBM. He is a seasoned executive, engineering leader, mentor, coach, who is actively involved in driving breakthrough innovation and works towards fostering industry-academia partnerships. As an experienced global leader in AI, Naveen Kamat is a proponent for more up-skilling and cross-skilling initiatives in AI for country’s workforce to leverage the economic and technological benefit that AI technologies bring in the coming decades. Naveen shared his thoughts on AI skilling and why it is the need of the hour with INDIAai. 

What is IBM’s approach to AI?

We believe AI is a great way for companies to bring in a whole new level of predictability, automation, and optimization to their business or IT processes. We have enabled and collaborated with several enterprises to drive breakthrough outcomes and reshaped their businesses on the basis of a strong AI foundation. 

For example, Indian Council of Medical Research (ICMR) collaborated with IBM to implement Watson Assistant on its portal to respond to specific queries of front line staff and data entry operators from various testing and diagnostic facilities across the country on COVID-19. (The queries could be related to nature and process of data to be captured by test labs, how to record inventory of test kits & reagents, the process of reporting to various Government agencies, and references to the latest guidance, in addition to responding to queries on COVID-19 in general.) Parle is working with IBM to create an “intelligent supply chain" by leveraging IBM Watson AI solution to predict demand, reduce time-to-market, and right-size its inventory across the supply chain. IFFCO Tokio General Insurance collaborated with IBM to automate the claim assessment process using an AI-based Claim Damage Assessment Tool (CDAT). CDAT leverages Cognitive Image Analytics to assess the type and extent of damage incurred to the vehicle to facilitate the claims process. Within a few minutes, the assessment and the cost are given to the customer, accepting which the customer gets paid in 15 minutes. The solution helped IFFCO Tokio reduce the claim response time by 30% and achieve cost optimization.

An essential ingredient for the success of AI projects is the availability of high-quality data in a secure and timely manner. On many occasions, we have seen that there are so many different data silos and redundant data pipelines that have built up over decades of distributed operations within an enterprise. Collecting, organizing, analyzing data through an optimized, secure and scalable information architecture becomes vital for the longer-term viability and success of AI projects. The AI Ladder, developed by IBM provides organizations with an understanding of where they are in their AI journey as well as a framework for helping them determine where they need to focus. It is a guiding principle for organizations to transform their business by providing four key areas to consider: how they collect data, organize data, analyze data, and then ultimately infuse AI into their organization.

More importantly, at IBM, we also believe that we have to operate with a great deal of responsibility when it comes to managing Data & AI for our clients and has pioneered products and services around Trusted AI. With Trusted AI, we are looking at various aspects such as data privacy, model bias, data lineage, model explainability. A large part of realizing outcomes with AI projects is also related to how these insights get integrated within the workflows for the enterprise as part of their DevSecOps cycle. Each enterprise could be at a different level of maturity in terms of AI adoption and organizational readiness - both in terms of technology as well as their own people enablement and process engineering. And so a big part of our engagement with clients is around consulting for Data & AI strategy, helping them with the data management products and services besides building enterprise-scale AI solutions that are fit for purpose and logically embedded into their business processes.

How AI skilling is going to be crucial for India?

A lot of challenges are unique to India in the Data and AI space - given the scale and the massive digital footprint - and the evolution of Aadhaar, UPI, and governmental initiatives towards building digital ecosystems for governance. AI can be a game-changer in solving some of the developmental challenges - be it helping farmers with improving crop yields or building a new level of observability and transparency into public distribution systems. India thus becomes a crucible for innovation and best practices that can be leveraged globally. Also, India has a demographic advantage and a strong base of foundational STEM skills. However, according to the International Labour Organisation (ILO) India is staring at a 29 million skill-deficit by 2030. As the industry sees a shift towards full-stack technology-based roles students will require deep technical skills as well as broad domain knowledge. It’s important for industry, government, and academia to work in conjunction to build a robust skill ecosystem to truly achieve the vision of a skilled India and Digital India.

One unique aspect of picking up AI skills is that one does not necessarily have to come from an engineering background. Anyone with a strong grounding in math and statistics and with a logical thought process can foray into the realm of AI. Programming languages such as Python and R are relatively easy to learn and come up with a lot of pre-built routines and functions that make the application of AI easier. Likewise, there are a lot of options when it comes to visualization tools. So we see people working in varied disciplines and in varied roles (in the healthcare, retail or financial domain) picking up AI skills and that is a very welcome development because the use and adoption of AI is also going to be pervasive across the industry sectors.

How can India ensure a future robust AI-ready workforce?

There is a tremendous level of interest and momentum even at an undergraduate level to pick up skills around AI - as the youth, in general, have come to realize that there are exciting careers to be made by investing in AI skills. It's very important though to recognize that a 'future robust AI-ready workforce' will mean that there is skilling not only around data science and data engineering - but related disciplines such as full-stack development, cloud-native environments (Kubernetes and container orchestration), UI/UX design. And above all, SME and architectural skills that can bring AI to be integrated within the existing or new business processes within a particular domain to have automated and intelligent workflows.

 I would strongly encourage institutions or edtechs imparting AI education or any individual undertaking skilling oneself to look at education in a real industry or social context. There have to be opportunities to apply AI skills for a real-world problem - because every step of the way - from data collection to data munging to feature selection - all the way up to building a model and deploying it for a desired and repeatable outcome - is a very significant learning process by itself. It's very encouraging to see a lot of institutes offering high-quality education programs around AI and Analytics both at a graduate and postgraduate level but also in the form of executive programs for working professionals. A large number of these programs offer industry internships or Capstone projects - as a way of offering an opportunity to apply the AI skills in a real-world context - and this can be incredibly valuable as part of the learning process.

What is IBMs process of cross-skilling?

There has been a major thrust around how we re-imagine our products and services in this Cognitive era. In the first half of 2020, we saw employees in I/SA clocking 4.3 Million Hours, earning over 1 Lakh Badges on key topics including Cognitive practitioner, enterprise design thinking, and automation essentials on our Think Academy digital platform, IBM’s learning program. IBMer learning hours witnessed a 39% increase in comparison with the same period last year (H1 2020 vs H1 2019).

For example, in IT Services, we believe that as workloads shift increasingly towards cloud-enabled and cloud-native environments, traditional service management paradigms will make way for newer ways of managing IT estates of our clients through concepts such Site Reliability Engineering (SRE paradigm) where automation and AI will be the key differentiator. And hence we are focussed on reskilling and upskilling our services teams with skills in the area of automation, AI techniques, and concepts. We are seeing a marked shift in the skill and talent base of our existing teams as well as the talent that we are bringing into IBM. We have also launched badging / certification programs internally for folks wanting to pursue their career paths in data science or AI - so that can be an independent track by itself - towards reaching the ultimate levels of technical excellence and accomplishment within IBM.

What are the skilling initiatives from IBM on AI?

IBM has a massive, in-house corpus of learning resources and programs around AI, besides a very large number of projects that we are working on across the various industry sectors. We have also tied up with MOOC learning providers such as Udemy and there are a large number of learning programs available through these partnerships for our internal teams that are looking to learn AI concepts & techniques. 

IBM is also playing a pivotal role in evolving the AI skills landscape in India through a slew of initiatives. For this, IBM has made investments in creating the future of Indian skills through IBM’s 'Stems for Girls' initiative, where the company is teaching 78,000 girls across India to build "new collar skills" that includes coding and building AI models. In collaboration with CBSE we are integrating Artificial Intelligence (AI) in the high school curriculum (Grade XI & XII) for the current academic year (2020 –2021), in approximately 200 schools across 13 states in India. The IBM AI curriculum is structured around a course framework for students consisting of base strands of knowledge (basics, history, applications), skills (design thinking, computational thinking, data fluency, critical thinking), and values (ethical decision making, bias) in AI. It is further made robust with problem-based learning outcomes and assessment methods for teachers, to build foundational skills of AI in students making them not just consumers of AI, but creators as well. We recently announced our collaboration with NSDC to offer ‘Open P-TECH’, a free digital education platform, focused on emerging technologies, such as AI and professional development skills. As a part of the collaboration, IBM will curate online courses from Open P-TECH platform and offer it to users via NSDC’s eSkill India portal to empower Indian youth on various skills to succeed in future careers. 

We are also working through various collaboration programs with many different Universities as part of our University outreach in terms of resources, grants, internships, faculty training, curriculum, and content curation.

IBM is committed to embedding Good Tech in everything that we do and leveraging the power of technologies like ‘AI in education’ and ‘AI for education’. We look forward to a continued partnership with the government, industry, developers, and universities to bring artificial intelligence together with hybrid cloud solutions and services to have a profound impact on every sector of society.