Published: 15th April 2026
For many financial institutions, Generative AI (GenAI) is viewed as a high-speed engine for innovation, yet most remain stuck in the ‘pilot’ lane. For Meena Karunanidhi, Lead Solution Architect and People Manager at Bank of Ireland, the challenge isn’t just the technology itself – it’s the complex web of organisational, regulatory, and human factors that determine whether an AI strategy succeeds or stalls.
Through her applied research project for the MSc in Leadership, Innovation and Technology, Meena investigated why adoption remains uneven despite the immense pressure to modernise. Her findings offer a blueprint for ‘Governance by Design’, ensuring that AI initiatives in highly regulated sectors are not only innovative but also trusted and sustainable.
TLDR; While GenAI offers a transformative opportunity for banking, successful adoption requires moving beyond a tech-first mindset. By addressing four critical pillars – Organisational, Regulatory, Technical, and Ethical – financial leaders can bridge the gap between AI ambition and real-world execution.
The Industry Problem: The Urgency of the “GenAI Gap”
The financial services sector is currently caught in a paradox. On one hand, there is an urgent need to exploit AI for operational efficiency and personalised customer experiences to stay competitive. On the other, the industry is anchored by legacy infrastructure, a significant skills shortage, and a ‘wait-and-see’ approach to emerging regulations.
“Implementing advanced technologies isn’t just a technical challenge,” Meena explains. “It’s deeply influenced by organisational dynamics“.
In her role at Bank of Ireland, she observed that recurring patterns – such as cultural resistance and inconsistent governance – frequently hindered the transition from theoretical potential to production-grade reality.
Project in Practice: Bridging the Gap Between Ambition and Execution
To ensure her research wasn’t just another “ivory tower” academic exercise, Meena adopted a rigorous mixed-methods approach that mirrored the complexity of the industry she serves. By combining qualitative interviews with senior practitioners and quantitative surveys across the broader financial sector, she was able to capture a high-resolution image of the current AI landscape.
“I engaged multiple stakeholders, including leaders, architects, compliance specialists and operational teams, ensuring that insights reflected real-world practices, challenges and priorities,” Meena explains.
This wasn’t just about collecting data; it was about triangulation – cross-verifying findings between expert interviews and industry-wide survey responses to uncover the genuine friction points where innovation often grinds to a halt.
The Results: Four Pillars of Resistance
Meena’s research identified four primary categories of barriers that financial institutions must navigate to accelerate adoption:
- Organisational & Financial: High implementation costs and limited leadership buy-in often stall projects before they scale.
- Compliance & Legal: Regulatory uncertainty and strict data privacy requirements create a ‘compliance drag’.
- Technical Debt: Issues like model drift and poor data quality undermine the reliability of AI outputs.
- Ethical & Trust: Public and internal mistrust regarding bias and the lack of ‘explainability’ in AI-driven decisions.
While technical issues like ‘model drift’ and data quality are significant, the research highlighted that the deepest resistance is often cultural. Internal hurdles, such as high implementation costs and a lack of leadership support, frequently stall AI initiatives before they can even reach the production phase. Furthermore, in a highly regulated environment, regulatory uncertainty acts as a heavy anchor, with teams often paralysed by unclear cross-border guidelines and strict data privacy requirements.
Meena notes that public acceptance is the final, often overlooked hurdle: “The public’s acceptance of GenAI depends on effectively addressing ethical and trust-related concerns such as bias, lack of transparency and accountability gaps”.
Strategic Mandates for Financial Leaders
For financial leaders, the ‘so what?’ of Meena’s research is clear: accelerating GenAI adoption requires a shift from ‘Tech-First’ to ‘Governance by Design’. This means designing modular, scalable systems where auditability and model transparency are built-in from the very first discovery phase, rather than retrofitted as an afterthought.
Based on her findings, Meena developed a series of actionable recommendations for leaders looking to move the needle on GenAI:
- Governance by Design: Don’t retrofit compliance. Architects must design modular, scalable systems where data quality and auditability are built-in from the outset.
- Proactive Regulatory Engagement: Instead of waiting for final rules, institutions should participate in regulatory sandboxes or pilot programs to co-create compliance frameworks.
- Incremental, Value-Led Delivery: Balance speed with control by adopting risk-aware deployment strategies that demonstrate ROI early while maintaining human-in-the-loop oversight.
- Fostering a Culture of Experimentation: Secure executive buy-in for upskilling programs that reduce workforce resistance and psychological barriers to AI change.
Ultimately, her impact plan emphasises that innovation cannot happen in a silo; it requires a culture of psychological safety where teams feel confident experimenting within established regulatory guardrails.
A Career Transformed: Moving to Holistic Leadership
For Meena, the Master’s programme was the catalyst for a fundamental shift in her professional mindset. She states that “the programme fundamentally shifted how I approach both solution design and leadership, moving from a primarily technology-driven mindset to a holistic, human-centered approach,” she notes.
By combining over 20 years of IT experience with the specialised knowledge gained from modules like Strategic Management of Technology and Personality and Leadership, Meena has become a bridge between technical design and high-level business strategy. She is already applying these principles at Bank of Ireland, evaluating AI agents across the software development lifecycle to drive efficiency while maintaining the rigor required in a regulated environment.
About Meena Karunanidhi
Meena Karunanidhi is a Lead Solution Architect and People Manager at Bank of Ireland, with over two decades of experience in banking and financial services. She currently leads the Integration Solution Design team, managing architects across Retail, Business, and Open Banking domains. She completed her Applied Research Project as part of the MSc in Leadership, Innovation and Technology with TU Dublin and Technology Ireland ICT Skillnet.
Lead on Innovation and Change
As organisations navigate the complexities of digital transformation, the need for leaders who can balance technical excellence with strategic governance is critical.
MSc in Leadership, Innovation and Technology
