How does the adoption of artificial intelligence transform decision-making, value creation, and competitive advantage across financial institutions and investment firms?
Second-year MBA student Alex Notman T’26 set out to explore this question through an independent study, examining how firms are using AI today—and what those patterns suggest about emerging capabilities, organizational challenges, and where AI is likely to carry the financial-services industry next.
As you start this project, what aspects of AI’s impact on financial services are you most eager to dig into?
I am most eager to explore where AI meaningfully improves decision-making in financial services versus where it merely accelerates existing, inefficient processes.
I am particularly interested in how AI affects the speed, consistency, and quality of decisions across areas such as risk assessment, underwriting, liquidity management, investment analysis, and portfolio monitoring.
Beyond value creation, I want to understand how firms actually capture that value, whether through cost advantages, improved returns, scalability, or defensible operating models. This includes examining whether competitive advantage is driven by superior data, proprietary models, organizational integration, or the ability to embed AI into core workflows at scale, as well as why some firms move beyond pilots to realize measurable economic impact while others struggle to operationalize similar capabilities.
Ultimately, this project seeks to clarify the conditions under which AI becomes a transformative source of decision advantage and sustainable value capture, rather than a marginal efficiency gain.
What strengths or perspectives do you feel you bring to this project that will help you analyze how AI is reshaping financial services?
I bring a perspective shaped by experiences across segments of the financial services ecosystem, including insurance brokerage at Marsh, strategy consulting in Oliver Wyman’s Financial Services practice, and growth equity at The Newcastle Network.
At Marsh, I worked within a large, global organization providing insurance brokerage and risk advisory for financial services clients, which exposed me early to the operational complexity of enterprise-scale firms. Core activities such as risk analysis, renewal management, and client reporting relied heavily on legacy technology and manual workflows, highlighting how difficult it can be for large organizations to modernize systems that are deeply embedded in daily operations.
This understanding deepened at Oliver Wyman, where I worked across a range of engagements spanning global banks and other large financial institutions. Through these projects, I observed how organizational scale, regulation, and governance can slow decision-making and make timely, consistent insight generation both complex and resource intensive.
My MBA summer internship at The Newcastle Network provided a contrasting perspective that anchors how I think about AI-driven opportunity. Working within an investment platform that actively embraces technology, advanced analytics, and emerging AI tools exposed me to how faster synthesis of information and deeper data-driven insight can improve sourcing strategies, diligence, investment judgment, and value creation efforts.
I was encouraged to focus not only on what technologies can enable, but on how management decisions, incentives, and organizational readiness determine whether those capabilities translate into real impact.
Viewed through this lens, my prior experience in large financial institutions sharpened my ability to identify where inefficiency, process friction, and decision latency create both risk and opportunity. Experiencing these environments side by side has shaped how I approach this project, allowing me to evaluate AI not only as a technological capability, but as a potential lever for meaningful value creation and capture when applied to the right decisions and processes.
How have Tuck courses, faculty guidance, or prior experiences shaped the way you’re approaching this?
My approach to this project has been shaped by the combination of my professional experience and Tuck’s emphasis on management as a central driver of decision-making and organizational performance. Prior to Tuck, my work exposed me to how governance structures, incentives, and operating models shape outcomes within large financial institutions, while my private equity experience reinforced the importance of execution in translating strategy into value creation.
At Tuck, coursework and faculty guidance have deepened my understanding that the successful adoption of technologies such as AI is fundamentally a management challenge, requiring leadership alignment, clear ownership, appropriate talent, and effective change management rather than simply technical capability.
This perspective was reinforced through my first-year project, in which I self-sourced and led a value creation engagement for a middle-market private equity firm, supporting a portfolio company’s digital transformation by identifying opportunities for operational improvement through technology integration, particularly through the adoption of AI.
I was encouraged to focus not only on what technologies can enable, but on how management decisions, incentives, and organizational readiness determine whether those capabilities translate into real impact—a lens that directly informs how I am approaching this study.
What made an independent study the right format, and how does it build on Tuck’s personalized learning opportunities?
An independent study is the right format for this project because the impact of AI on financial services is evolving too quickly and unevenly to be fully addressed within the structure of a traditional course.
Given my prior experience, I wanted the flexibility to examine AI adoption across multiple segments of the financial services ecosystem while going deeper into investment firms, where decision-making and value creation dynamics are particularly pronounced.
[The independent study] builds on Tuck’s personalized learning model by enabling close faculty engagement and allowing me to tailor the scope, methods, and outputs of the project to my professional background and post-Tuck goals.
The independent study format also allows me to integrate academic research, industry reports, and professional interviews in a way that mirrors how strategic questions are evaluated in practice, while iterating as new insights emerge.
It also builds on Tuck’s personalized learning model by enabling close faculty engagement, particularly with Professors Bill Martin and Brian Melzer, who are advising my study, and allowing me to tailor the scope, methods, and outputs of the project to my professional background and post-Tuck goals. The result will be a practitioner-relevant framework that links AI capabilities to decision outcomes, value creation and capture, and long-term competitive advantage.
You’ll be speaking with practitioners across banking, investing, insurance, and consulting—what kinds of insights or perspectives are you hoping to gather as you develop your framework?
I hope to gain an understanding of how AI is being incorporated into real decision-making processes, rather than how it is framed in theory or discussed at a conceptual level. I am particularly interested in how firms identify and prioritize AI use cases, evaluate economic impact, and navigate constraints related to data quality, legacy infrastructure, regulation, and organizational change.
I also want to understand how leaders determine where AI should automate decisions, where it should augment human judgment, and how responsibility and governance evolve as these systems become embedded in core workflows. These perspectives will be essential in distinguishing genuine value creation from experimentation, and in developing a framework that reflects both the practical realities of AI adoption and the conditions under which it can deliver sustained competitive advantage.
As you look toward your post-Tuck career, how do you hope to apply what you learn in this project to roles at the intersection of AI and financial services?
Post-Tuck, I am interested in roles where I can apply a strong understanding of how AI reshapes decision-making, economics, and competitive advantage within financial services and investing contexts. This includes investing roles in venture capital or private equity, strategy or transformation roles within financial institutions, and operations or strategy roles at AI-enabled or AI-native companies serving the financial services sector.
Building on my background, I want to use the insights from this project to better evaluate how AI affects investing including deal sourcing, diligence, underwriting, and post-investment value creation, as well as how large institutions can integrate AI into core workflows to improve efficiency, risk management, and capital allocation.
At the same time, I am interested in how AI startups translate technical capability into scalable products that meet the operational, regulatory, and governance needs of financial services customers.
Ultimately, this project is intended to position me to contribute at the intersection of AI and financial services, bringing a practical, experience-driven perspective to organizations seeking to move from AI experimentation to durable value creation and capture.
If you're interested in speaking with Alex for the study, he can be reached at alexander.g.notman.tu26@tuck.dartmouth.edu.
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