Need to develop AI, ML expertise & empower individuals

India’s UPI has seen unprecedented growth, cementing its position as a global leader in digital payments. As per Worldline’s India Digital Payments Report, UPI transactions skyrocketed from 8.03 billion in January 2023 to an astounding 13.9 billion by June 2024, with the total transaction value surging from USD 154.60 billion to USD 239.04 billion. UPI has not only revolutionized digital payments in India but also garnered global attention as a model for modern payment systems, steering the country towards a cashless economy.

Similarly, Artificial Intelligence (AI) holds transformative potential, revolutionizing operational efficiency, customer experience, innovation, predictive capabilities, business decision-making, and cybersecurity. As organizations across industries look to seriously adopt AI for sustained growth and success, the need to understand and harness AI/ML has never been more critical. Academia, industry, and government must now collaborate to develop a robust AI/ML framework, ensuring that the necessary skills are cultivated to navigate this new era of technological advancement. It is important to recognize that these technologies are not only for data scientists but for all individuals.

The Growing Impact of AI/ML and the Challenges

AI and machine learning are disruptive technologies, revolutionizing business operations by automating processes, enhancing decision-making through data analysis, and personalizing customer experiences, ultimately driving efficiency and innovation.

They improve customer engagement, predict trends, and boost competitiveness. In BFSI, AI automates tasks, enhances customer service, and speeds up fraud detection. Manufacturing uses AI to optimize production and improve quality, while retailers leverage it for better customer service and inventory management. In healthcare, AI enables more accurate diagnoses and personalized treatments.

However, the rapid growth of AI/ML has revealed a critical skills gap, with a shortage of professionals able to fully utilize these technologies. As the future of work relies on AI/ML expertise, individuals must acquire these skills, or economies risk falling behind globally.

Tailored Learning Paths for All For undergraduate students

Today’s students are the future workforce, and as AI/ML becomes increasingly prevalent, students in fields such as engineering, business, medicine, and even the arts must understand these technologies to stay competitive.

Integrating AI/ML education into undergraduate, master’s, and research programs is essential, offering both standalone courses and interdisciplinary modules. These programs should teach in-depth technical skills, theoretical foundations, and real-world applications, helping students understand how AI/ML solves current industry challenges.

A well-structured curriculum along with practical knowledge of algorithms and coding, is crucial. To equip students for a future where AI/ML is central, foundational courses on AI/ML basics, ethical implications, and applications should be mandatory for all undergraduates, regardless of their major.

Universities should prioritize hands-on, project-based learning, allowing students to apply AI/ML tools to real-world challenges. This could involve partnerships with industry or research projects where students develop models, analyze data, and derive actionable insights. By promoting a practical, interdisciplinary approach, students will be fully prepared to thrive in an AI-driven future.

For professionals

As AI and machine learning become integral to modern industries, professionals must learn to work effectively with these technologies to remain competitive. AI/ML enhances productivity, drives innovation, and opens new career opportunities, but without a solid understanding of how to apply them, professionals may slow their advancement.

For professionals who manage multiple stakeholders and are responsible for implementing AI/ML-driven initiatives, it’s essential to focus on the strategic applications and implications of these technologies. Training programs should cover a high-level understanding of AI/ML, including model deployment, system integration, associated risks, and popular tools. This knowledge is crucial for ensuring the successful execution of medium- to long-term projects that leverage AI/ML.

Given the constraints many professionals face, such as balancing work and personal commitments, full-time studies may not be feasible. Online courses and boot camps provide flexible alternatives, enabling professionals to upskill without disrupting their careers. Additionally, employers play a key role in promoting AI/ML literacy by offering tailored training programs, ensuring their workforce is equipped to harness these technologies effectively. By investing in continuous learning, both professionals and organizations can stay at the forefront of innovation in an AI-driven world.

For strategists and decision-makers

Business leaders, executives, and policy-makers must also possess a working knowledge of AI/ML. While they may not need to code or develop models themselves, they must understand the capabilities, limitations, and ethical considerations of AI/ML technologies to make informed decisions. Their ability to guide strategic initiatives, allocate resources, and ensure responsible AI implementation depends on their understanding of these technologies. A lack of AI literacy at the decision-making level can lead to misguided investments, poor regulatory frameworks, or the misuse of AI in ways that harm society.

A carefully curated awareness program of short duration can be designed and conducted for strategists and decision-makers. the focus areas are high-level understanding, strategic application, implications of AI/ML, use cases, best practices, impact analysis, ROI, Risks, compliance, and more. Workshops and seminars focusing on the business and ethical implications of AI/ML, AI governance, and data privacy can help executives and policy-makers stay relevant. Decision-makers should also consider forming AI/ML advisory boards within their organizations. These boards, consisting of AI experts and ethicists, can help guide organizations in navigating the complex landscape of AI/ML deployment.

(The author is Information Technology Technical Consultant, Astrikos.ai)