Building a digitally intelligent India

India has commenced its transformational journey from being a Digital India to a Digitally Intelligent Nation. The emerging technology landscape, coupled with innovative practices for new business and governance models is paving the way for emerging concepts around Intelligent Nations. There is a dynamic shift in approaches adopted by developing nations to ensure competitive advantage.

The approaches that are emerging highlight significant changes including:

• A shift toward a predictive analysis and proactive methods has surpassed reactive measures.
• Modified citizen interface by inculcating data-defining processes rather than relying on processes consuming data alone.
• Furthermore, ensuring a policy and planning framework to create value through trustworthy use of emerging technologies has become the top priority for intelligent nations.
• There is a need for creating an ecosystem for intellectual property rights to take the front-runner advantage from the deployment of emerging technology systems.
• Leading through product and services developments in emerging technologies is imperative for both enterprises and government.

An intelligent nation is one that consists of intelligent enterprises and data-driven governments, building upon the promise of digital transformation by applying data-driven intelligence to drive actions and decisions based on superior insights focusing on strategies where the most public good can be impactfully achieved. The idea behind the concept of intelligent nations is to improve wellbeing, economic prosperity, quality of life, and public security. The key differentiation in intelligent enterprises (whether government or non-government) is the acceptance of machines as co-workers. There is a gradual shift in repetitive tasks being undertaken by machines with organizations focusing primarily on the execution of critical tasks. Rapid automation techniques and machine learning have escalated the potential and proportion of high value-added tasks.

From defining the facets of intelligent nations to bringing the concept into reality, both strategically and operationally, we have come a long way. Collaborative practices adopted by multiple stakeholder groups have led to the realization of various achievements. We need to give ourselves credit in terms of the unique initiatives being driven, for example, along with having the largest digital-literacy program, we are creating a vast rural broadband network as well as a network of digital services known as CSCs or common service centers. We have successfully created the world’s largest digital identification platform Aadhaar. There are various other programs that are pioneered by India like having the only digital vault for citizens, known as Digilocker, and the largest direct-benefit transfer systems. We are the facilitators of the world’s biggest citizen-engagement platform MyGov. In fact, we have already started using terms like real-time governance or RTGS. Establishment of the largest e-market place for government GeM and the accreditation of private cloud service providers are yet other milestones toward creating a flexible program management. We have made reasonable progress in creating the foundations of the regulatory ecosystem for adoption of emerging technologies. Our models and their complexities can be used as a benchmark and we surely are on a journey in achieving excellence.

Going forward, there is a need to integrate emergent technologies like artificial intelligence, blockchain, and Internet of Things under a national program. In order to achieve that, we need to replace the siloed interfaced policy prescriptions around various domains to an integrated data-centric policy prescription. From domain-led policies like startups, drones, e-commerce, and the like, emerging technologies would need to get integrated into all policies as a horizontal line of action. An overarching structure to do a data review of all policy prescriptions is the need of the hour. From an interfaced structure, we should move to an integrated structure. The developments should not be the domain of a ministry or of a government department alone. There should be a multi- or cross-sectoral task force to work on the constant regulation of developments. Moreover, formulation of a National Artificial Intelligence policy is of prime importance. While artificial intelligence might be a horizontal discipline, a structured push through a well-defined AI policy should be implemented with the Ministry of Electronics and IT, Science and Technology, or Commerce and Industry taking the lead. This will bring in a unification of direction to currently separately driven initiatives by the ministries.

The policy landscape may require attention to the availability of training data and creation of data bank and cross-sectoral availability of structured data sets for analysis and learning. A central ministry is required to work as the nodal agency of the same. A multi-stakeholder dialogue needs to be created to ensure a platform with multi-stakeholder representation with programmatically planned execution. The German Industry 4.0 Platform serves as a very good reference for the same. Promoting research and innovation is another key requirement. While much of the AI technology framework has been already established, more basic and applied research needs to be conducted to realize the vision of the intelligent enterprise. A network of industry and universities to address some of the most pressing challenges will be helpful. Artificial models must become more robust, accurate, and credible. Interpretability and traceability of algorithms should be improved so that users can understand results. The collaboration benefits research partners, who get funding, business data, and industry problems to work on, while the additional pool of expertise and machine-learning models enables industry to advance its AI product portfolio. There is a requirement for work organization and redesign as technology is constantly transforming workforce. Greater use of robotics and automation is bound to reduce a great number of jobs in assembly and repetitive operations. However, this will be counterbalanced by new jobs in IT and data science, with primary focus on critical tasks. Education systems should seek to provide broader skill-sets to close impending gap. Skilling and re-skilling are required as jobs in the AI era will seek a radically different skill set and competence profile. Skill development policy should be enforced to regulate skilling and re-skilling. Revision of secondary school and university curriculums to inculcate interest toward AI and robotics should be encouraged and industry participation in academic curriculum design for AI/robotics courses should be carried out. Enhanced collaboration with other countries for knowledge exchange for R&D around AI and robotics and making quality training data available in the form of shared public data sets is bound to take the initiative to next level. Implementation of a regulatory framework is the need of the hour. Adoption of smart technologies will require a supporting legal and regulatory environment to ensure protection of data, effective handling of liability issues, privacy concerns, and the like. The data-privacy frameworks in this direction are the initial welcome steps.

Another key requirement for an integrated national program is ensuring safety and cyber security. It is important to ensure that cyber-controlled systems do not become a risk for safety of people or environment. Cybersecurity is the digital glue that keeps IoT, smart cities, and our world of converged machines, sensors, applications, and algorithms. This calls for integration of safety and cyber-security standards. We need to focus on the evolving discipline of data protection, where everyone is learning to cope with fast-changing and complex requirements. Furthermore, ensuring realistic standards and smooth inter-operability functions is important. Emerging technologies will lead to inter-company integration through value networks. This will only be possible when we have a single common set of standards. With systems growing complex, there will be a need to equip workforce with tools and techniques for development of models for complex production systems. It is also important to generate citizen awareness as it often becomes a critical issue while working with rural citizens and SMEs.

We have entered a new renaissance of accelerated technological development that is exponentially transforming our civilization. Given the above as a strategic roadmap, the realization of the dream of a Digitally Intelligent India to lead and leapfrog the next wave of technology may require the collective stakeholder execution of the integrated program. The real imperative is for planning and systematic integration in resonance with catalyzing innovation.

We must strive to work in unison for creating intelligent nations.