Organizations that are exploring A.I. are moving beyond experimentation, getting creative, and even having fun with it, says Nadine Kawkabani at MFS Investment Management.
(Nadine Kawkabani, vice president, senior director, global distribution business strategy for MFS Investment Management leads the global business strategy and A.I. team at MFS Investment Management for retail and institutional channels. Kawkabani says that achieving success across a range of A.I. use cases is inspiring her to participate in PMCR 2026 and join the “A.I. Implementation Showcase: What’s Actually Working?” session. Organizations that are exploring A.I. are moving beyond experimentation, getting creative, and even having fun with it. A.I. is making the investment operations landscape more cohesive, improving coordination across business, technology, risk, and governance units, enabling a firm to act as one team that shares the success of an A.I. project.)
Professional Background / Expertise
Q: Can you tell us a bit about your role and what your day-to-day looks like at MFS Investment Management?
A: I lead the global business strategy and A.I. team at MFS Investment Management across both retail and institutional channels. My responsibilities span strategy development, business management, and advancing our business intelligence and analytics capabilities — including data science, automation, and generative A.I.
A significant part of my role focuses on building, scaling, and innovating enterprise A.I. solutions, as well as contributing to the firmwide A.I. strategy and roadmap. This includes shaping priorities, governance, and enterprise use-case development beyond distribution. I also oversee strategic academic partnerships that support research collaboration, talent development, and long-term innovation.
Q: What’s a recent project or initiative your team has worked on that has made the biggest impact for your organization?
A: One of our most impactful efforts has been Building Forward, which reflects our intentional approach to A.I. adoption. Rather than pursuing technology for its own sake, we are focused on aligning A.I. with our strategy — using it to augment how we work and scale capabilities thoughtfully.
The emphasis has been on focused, disciplined execution, and ensuring A.I. meaningfully supports our people and business objectives.
Q: What is your dream project?
A: My dream project is delivering end-to-end value creation — something deeply strategic with multiple integrated components. It would bring together data, A.I., human expertise, and operating models in a way that meaningfully transforms how work gets done and how value is delivered across the organization.
Session Insights
Q: What inspired you to participate in PMCR 2026 and speak on “A.I. Implementation Showcase: What’s Actually Working?”
A: What inspired me is seeing real success across a range of A.I. use cases — where organizations are moving beyond experimentation into value realization. People are getting creative, finding efficiencies, and even having fun with it. We’re seeing tangible impact not just in outcomes, but in how teams come together.
Q: What do you think makes this session especially relevant for today’s investment operations landscape?
A: A.I. implementation is no longer about isolated teams or point solutions — it’s about operating as one team. Success requires coordination across business, technology, risk, and governance, with shared ownership of outcomes.
Industry Challenges & Trends
Q: What’s one of the biggest challenges your team or clients are facing right now, and how are you approaching it?
A: One of the biggest challenges is keeping up with the pace of development while maintaining clarity and discipline. This includes establishing the right frameworks for prioritization, measurement, and integration.
Measuring impact — both qualitative and quantitative — across short-term wins and long-term value creation is particularly complex. While there’s excitement around near-term gains, sustained success depends on long-term thinking, strong foundations, and bringing the pieces together coherently.
We’re also continuously thinking about the collective intelligence, be it among either humans or machines or collectively across both.
Q: How do you foresee technology reshaping your area of expertise over the next year or two?
A: We’ll see a broader industry-wide impact as A.I., automation, and analytics mature and become more embedded in everyday workflows. The most important shift will be staying focused on the value proposition — being clear on purpose, outcomes, and remaining authentic to your organization’s voice, rather than chasing every new capability.
Q: Which technology has impressed you? Which has disappointed you?
A: I’ve been impressed by how quickly generative A.I. and agentic approaches are moving from experimentation to practical application.
At the same time, some technologies have been disappointing when adoption outpaces readiness — highlighting that success depends as much on operating models, data quality, and change management as on the technology itself.
The PMCR Experience
Q: What are you most excited about learning at PMCR?
A: I’m most excited about connecting with peers and hearing about their journeys — what’s working, what’s not, and how they’re navigating similar challenges. I’m also interested in gathering feedback on the evolving vendor landscape and learning more about where organizations are on their agentic A.I. journeys.
Q: What do you hope attendees walk away with after hearing your session?
A: I hope attendees walk away feeling that we’re on this journey together. My goal is to spark thoughtful discussion around the future skillsets we’ll need, how we build for that future, and to share ideas, lessons learned, and validation of approaches others may already be considering.
Getting to Know You
Q: What’s one thing people might be surprised to learn about you?
A: I’ve worked across several fields and continents, which has shaped both local and global perspectives in how I approach problems. In addition, I love to travel in my personal life.
I bring an ‘economist mindset’ to A.I. that balances macro and micro thinking, leveraging diverse capabilities to solve complex challenges, and I’m deeply passionate about forward-looking innovation.
That mix of global exposure and systems thinking shapes how I approach A.I. — not as a tool, but as an ecosystem.
Q: What’s the best piece of career advice you’ve ever received?
A: Early in my career, a senior leader encouraged me to consider career paths I hadn’t previously imagined. That experience taught me to stay open to non-linear paths, focus on developing skills I’m passionate about, and seek roles based on learning and impact — rather than titles alone.