Nepal's AI Moment: Why Playing It Safe Is the Riskiest Strategy

Nepal Rastra Bank's new AI guidelines represent a historic opportunity, and a critical test of whether Nepal will lead or lag in the digital economy revolution.

In December 2025, Nepal Rastra Bank released comprehensive AI guidelines for financial institutions, marking Nepal's entry into the global conversation about artificial intelligence governance. The document demonstrates technical sophistication, aligns with international standards, and shows genuine concern for consumer protection. It should be celebrated as an important first step. But if Nepal's ambition is merely to have guidelines rather than to build an AI-powered economy, we risk winning the battle for regulatory compliance while losing the war for economic competitiveness.

The guidelines reflect a fundamental tension playing out worldwide: how do we harness AI's transformative potential while managing its risks? International frameworks, from the UN's recent model policy on responsible AI [1] to the U.S. federal government's innovation-focused memorandum [2], show different answers to this question. Nepal has chosen the cautious path. The question is whether caution serves our national interest, or whether it simply ensures we arrive safely at irrelevance.

The Paradox of Safety

Nepal's guidelines are comprehensive in their risk management approach. They mandate board-level oversight, require bias testing, protect consumer privacy, and establish clear accountability chains. These provisions mirror best practices from established economies. On paper, Nepal's framework could pass muster in Brussels or Washington. This is no small achievement for a developing economy.

Yet the guidelines contain a revealing omission: nowhere do they articulate how AI will contribute to Nepal's economic development. There are no targets for AI-driven financial inclusion, no vision for AI exports, no strategy for leveraging our remittance economy, which represents roughly 25% of GDP, through AI-optimized services. The framework treats AI purely as an operational risk to be managed, not as an economic opportunity to be seized.

Research from academic institutions worldwide confirms what Nepal's policymakers seem to have missed: AI governance is not a binary choice between innovation and safety. A recent study on AI integration in public administration found that successful AI adoption requires governance frameworks that actively enable innovation while maintaining democratic values and public trust [3]. The key word is "enable." Nepal's guidelines, by contrast, establish hurdles without building ladders.

The Innovation Deficit

Consider what's missing from Nepal's AI framework. There is no regulatory sandbox allowing financial institutions to experiment with AI solutions under relaxed oversight. There are no tax incentives for AI research and development. There is no fast-track approval pathway for low-risk AI applications. There is no shared data infrastructure to help smaller institutions compete with larger banks. There are no public-private partnerships to build AI validation capacity or workforce pipelines.

This matters because while Nepal debates whether to allow AI chatbots, competitors are racing ahead. Singapore's Monetary Authority has run innovation sandboxes for years, attracting billions in fintech investment. India's Unified Payments Interface, powered by AI-driven fraud detection, processes billions of transactions monthly. Even Bangladesh is piloting AI-based alternative credit scoring to expand financial inclusion. Nepal risks being left behind not because we lack talent or capital, but because our policy framework emphasizes restriction over enablement.

The irony is that Nepal possesses unique competitive advantages. Our large diaspora creates natural demand for remittance innovation, a perfect testbed for AI-optimized cross-border payments. Our smaller market size means regulatory changes can be implemented faster than in India or China. Our young, tech-savvy population is adoption-ready. Our strategic location positions us as a potential bridge between South Asian markets. These advantages mean nothing if our regulatory framework tells innovators to look elsewhere.

Learning from Leaders

The contrast with more ambitious regulatory approaches is instructive. The U.S. federal government's recent AI memorandum explicitly directs agencies to "accelerate federal use of AI through innovation, governance, and public trust", note the ordering [2]. Innovation comes first, but not at the expense of governance and trust. This isn't recklessness; it's strategic priority-setting.

International research on AI regulation and economic growth reinforces this approach. Studies examining major technology companies' AI ethics practices find that firms like Google, Microsoft, and IBM have operationalized ethics not through restrictive rules but through integrated development processes, internal review boards, and transparency tools [4]. The lesson: effective governance enables rather than prevents innovation. Successful frameworks align market incentives with ethical outcomes through mechanisms like tax credits for responsible AI, procurement preferences for transparent systems, and technical assistance for smaller players.

The UN's framework for responsible AI in international organizations offers another model [1]. While emphasizing risk-based approaches and rigorous assessment, it explicitly recognizes AI's potential to advance organizational missions. The framework doesn't just list what AI shouldn't do, it articulates what AI should achieve. Nepal's guidelines would benefit from similar ambition.

The Cost of Caution

What happens if Nepal maintains its current trajectory? The most likely outcome is slow AI adoption concentrated among large commercial banks with resources to navigate complex compliance requirements. Smaller institutions, microfinance organizations, development banks, payment service providers, face prohibitive barriers. This consolidation advantage contradicts Nepal's stated goal of fostering "a competitive and inclusive financial sector."

More broadly, excessive caution creates opportunity costs. Every year Nepal spends perfecting risk frameworks while competitors build AI industries representing lost GDP growth, foregone job creation, and diminished global competitiveness. Research suggests that countries with well-calibrated AI governance can expect 1-3% additional annual GDP growth from AI-enabled financial deepening alone [4]. For Nepal, this could translate to billions in economic value over a decade.

The human cost matters too. Nepal produces talented engineers who increasingly seek opportunities abroad because our domestic market offers limited scope for cutting-edge work. An ambitious AI strategy, complete with sandboxes, innovation funds, and public-private partnerships, could reverse this brain drain, transforming Nepal into a regional AI development hub.

A Path Forward

Nepal doesn't need to abandon the prudent foundations established in the current guidelines. Board oversight, bias mitigation, consumer protection, these principles should remain. But we need to supplement restriction with enablement.

Practically, this means three immediate reforms. First, establish a regulatory sandbox allowing financial institutions to test AI solutions with 1,000-10,000 customers under NRB supervision. Successful pilots get expedited full approval. Second, create a $20 million AI innovation fund (financed through banking sector levies) offering grants to institutions developing AI solutions for financial inclusion, remittance optimization, or MSME lending. Third, launch a national credit bureau upgrade incorporating AI-powered alternative credit scoring using mobile money, utility payments, and other non-traditional data to bring 2 million unbanked Nepalis into formal finance.

These three reforms, sandbox, innovation fund, credit bureau, would cost less than $50 million but could catalyze hundreds of millions in private investment while demonstrating Nepal's commitment to AI-led growth. Industry voices, from technology leaders to financial executives, increasingly argue that AI governance cannot be treated as mere compliance but requires institutional commitment and strategic vision [5]. Nepal's regulators should heed this call.

The Real Risk

Nepal Rastra Bank's AI guidelines represent careful, competent work. They demonstrate that Nepal can match international standards for governance frameworks. But matching standards is not the same as setting them. The real question is whether Nepal aspires to be a rule-taker or a rule-maker in the emerging AI economy.

The choice before us is not between reckless innovation and prudent caution. It's between managed risk-taking that positions Nepal as a competitive AI economy, and risk avoidance that guarantees we become mere consumers of technologies developed elsewhere. Academic research, international frameworks, and successful case studies worldwide point to the same conclusion [1, 2, 3, 4, 5]: the greatest risk in AI governance isn't moving too fast, it's moving too slowly.

Nepal has perhaps 24-36 months before regional competitors establish insurmountable leads in AI finance. Our diaspora capital, strategic location, and young population provide advantages. Our guidelines provide a foundation. What we need now is the courage to build something ambitious on that foundation.

The AI revolution will happen with or without Nepal's participation. The only question is whether we'll be shaping that revolution or swept along by it. Nepal Rastra Bank has given us the rules for a cautious game. Now we need policymakers brave enough to play to win.

The author is an expert AI engineer and an educator.

References

[1] High-level Committee on Management. (2024, June 12). Framework for a model policy on the responsible use of artificial intelligence in UN system organizations. United Nations System Chief Executives Board for Coordination. https://unsceb.org/sites/default/files/2024-11/Framework%20for%20a%20Model%20Policy%20on%20the%20Responsible%20Use%20of%20AI%20in%20UN%20System_0.pdf 

[2] Vought, R. T. (2025, February 3). Memorandum for the heads of executive departments and agencies: M-25-21 accelerating federal use of AI through innovation, governance, and public trust. Office of Management and Budget, Executive Office of the President. https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf 

[3] Gavriluta, A. F., & Tofan, M. (2025). Integrating artificial intelligence into public administration: Challenges and vulnerabilities. Administrative Sciences, 15(4), 1–23. https://doi.org/10.3390/admsci15040149 

[4] Kulothungan, V., Mohan, P. R., & Gupta, D. (2025). AI regulation and capitalist growth: Balancing innovation, ethics, and global governance. In 2025 IEEE 11th Conference on Big Data Security on Cloud (BigDataSecurity) (pp. 39–45). IEEE. https://doi.org/10.1109/BigDataSecurity66063.2025.00020 

[5] Yadav-Ranjan, R. (2025, February 4). AI governance: The CEO's ethical imperative in 2025. Forbes. https://www.forbes.com/sites/committeeof200/2025/02/04/ai-governance-the-ceos-ethical-imperative-in-2025/ 

[6] Nepal Rastra Bank. (2025, December). Artificial Intelligence Guidelines: Banks & Financial Institutions. Banks & Financial Institutions Regulation Department.