From Classroom to Boardroom: Transforming Finance Talent with AI

Dr. Suresh Ramanathan, Dean & Principal of Great Lakes Institute of Management, Chennai, explores the transformative role of artificial intelligence in reshaping the finance industry and its workforce. With AI deeply integrated into asset management, risk mitigation, customer service, and investment analysis, the next critical step lies in equipping finance professionals with the skills to navigate this AI-driven paradigm.

Business schools worldwide, including Great Lakes, are pioneering this shift by embedding AI across curricula, pedagogy, and experiential learning. The focus is on cultivating finance professionals who can leverage AI for strategic decision-making, robust risk management, and ethical compliance, ensuring a talent pool that meets the evolving demands of the finance industry.

Dr. Ramanathan emphasizes the importance of academic-industry collaboration in bridging the gap, ensuring that future leaders can harness AI’s potential responsibly while driving innovation in a competitive landscape.

As financial services continue to transform at a breakneck pace, artificial intelligence stands as a pivotal force reshaping the finance industry. This is not just a passing trend; it’s a fundamental shift. AI is already central to asset management, risk assessment, fraud detection, customer service, and investment analysis. The next frontier, however, is equipping the finance workforce with the skills and competencies required to navigate this AI-powered landscape. Several business schools across the globe and in India are reimagining financial education to integrate AI across curriculum, pedagogy, and experiential learning, aiming to develop finance professionals who can leverage AI in meaningful ways.

For corporate leaders invested in upskilling and hiring talent, the impact of AI on finance in education is profound, and we see three critical dimensions in which it will shape the future workforce.

AI Skills in Financial Decision-Making

One of the most compelling applications of AI in finance is in enhancing decision-making. AI tools enable finance professionals to process massive datasets in real time, generating insights that allow for rapid and accurate financial forecasts, credit scoring, and investment decisions. However, AI’s role goes beyond speed and precision, it’s also about transforming data into actionable insights.

In our financial education programs, we emphasize skills in AI-driven data interpretation and strategic thinking. It’s not enough to understand AI algorithms; students must learn how to translate AI outputs into decisions that align with broader business goals. Case-based learning and real-world projects help bridge this gap. For example, students might use machine learning algorithms to analyze market trends and customer spending behaviors, practicing how to deploy these insights in real-world financial decisions.

For corporations, this means future finance professionals will come to you not only equipped with technical skills but also with a strategic mindset on how to apply AI-driven insights to achieve outcomes. AI literacy, paired with critical financial judgment, will become the baseline.

AI-Powered Risk Management Skills

Risk assessment and mitigation have always been fundamental in finance, and AI is reshaping these areas. Today’s AI systems can analyze multiple data sources including non-traditional ones like social media sentiment and real-time transaction data to detect and mitigate potential risks well before they materialize. This has transformed areas such as credit risk, operational risk, and compliance.

At Great Lakes, we will be training students to use AI tools for robust risk management frameworks. For instance, we are working on incorporating AI-based risk simulation models into the curriculum, where students analyze credit risk with predictive models and evaluate portfolio risks using Monte Carlo simulations powered by AI. The curriculum is being designed so that students don’t just learn to operate these tools but understand the underlying assumptions, limitations, and ethical implications, which are equally crucial.

From a corporate perspective, hiring finance professionals trained in AI-driven risk management means bringing in talent who can not only enhance risk detection but also provide a nuanced perspective on risk governance. This is invaluable in a regulatory landscape where compliance costs are rising, and regulations are rapidly evolving.

Ethical Implications and Responsible AI in Finance

AI’s expansion in finance also brings forward a series of ethical and regulatory considerations. Financial leaders are keenly aware of the consequences of biased AI models, data privacy issues, and the importance of explainable AI in building trust. With the industry’s emphasis on responsible AI, financial education must go beyond teaching the mechanics of AI and address these ethical implications head-on. By introducing courses on data ethics and compliance, a b-school can ensure that graduates are equipped to make principled decisions and recognize the regulatory impacts of their AI implementations.

For corporates, this means the next generation of finance professionals will not only have the technical acumen to build and implement AI solutions but will also be mindful of ethical considerations, ensuring compliance and fairness. This aligns with the growing emphasis on ESG (Environmental, Social, and Governance) principles in finance, where ethical AI is increasingly part of the “social” and “governance” aspects.

Embracing the Future: Bridging Academia and Industry

The future of finance belongs to those who can navigate the synergy of human expertise and AI-driven intelligence. Business schools play a vital role in developing talent capable of meeting industry demands and addressing its most pressing challenges. But the collaboration does not end with curriculum updates. We work closely with industry partners to ensure our programs stay relevant and offer students exposure to the latest AI tools, case studies, and industry insights. Corporate leaders can greatly benefit from strengthening ties with educational institutions that prioritize AI in finance. By participating in curriculum co-design, guest lectures, and capstone project evaluations, you can directly influence how future finance professionals are trained. This collaboration allows you to develop a talent pipeline that is AI-ready and aligns with your organization’s needs.

AI’s role in financial education is as much about developing technical expertise as it is about nurturing a forward-looking mindset. Business schools should be committed to shaping finance professionals who not only understand AI but can use it responsibly and strategically. As AI continues to evolve, the real differentiator for finance leaders will be those who can harness its full potential while adhering to ethical standards. For the corporate world, partnering with AI-focused educational programs is not just a forward-thinking strategy; it’s essential for staying competitive in a rapidly transforming financial landscape.

Read More:

• UGC Draft Regulations 2025: Holistic Faculty Recruitment, Multidisciplinary Flexibility, and Revamped VC Selection
• UGC Invites Feedback on Draft Guidelines for Skill-Based Courses and Micro-Credentials in Higher Education