Why skills taxonomies and architectures are critical to navigating the financial industry’s future
A modern, dynamic approach to skills assessment in the financial industry requires a sound underlying framework and a strategic overlay tied to an organization’s goals. Taxonomies and architectures can help define pathways to success.
Skills taxonomies and architectures have become foundational to talent strategy in the financial industry, supporting firms’ efforts to navigate technological change, regulatory complexity and evolving client expectations.
Skills taxonomies are structured – and often highly detailed – lists of specific abilities or skills. Skills architectures, by contrast, are much higher-level applications of taxonomies that take into account everything from job roles to organizational objectives and strategy.
“We see the taxonomy as a library, and the architecture as being more linked to roles and functions, more of an organizational articulation of how you structure your workforce,” said Claire Tunley, CEO of the UK’s Financial Services Skills Commission (FSSC).
The FSSC produces its own Future Skills Framework that companies can adopt or use as the basis to construct their own. A framework builds on a skills taxonomy by layering onto it a set of proficiency levels and typically includes guiding principles for how an organization will assess those levels in its own staff.
By moving beyond static job descriptions to dynamic skills-based models, financial institutions can better identify gaps, forecast demand, and develop and deploy talent with precision.
According to a 2023 report on skills by the World Economic Forum (WEF) and PwC, taxonomies must be dynamic, customizable, and granular in order to be effective. For practical advice on how to think about and design a skills taxonomy, check out our guide here.
The need for a dynamic approach is especially critical as AI and automation reshape traditional roles, elevating the importance of human-centric skills like critical thinking, collaboration, and ethical judgment.
“We live in a very structured world right now of job architectures, but there also needs to be a fluidity to accommodate new roles that are appearing,” said Ina Gantcheva, Partner in the Human Capital practice at Deloitte. “We are also seeing other transitions, such as strategic thinking skills traditionally associated with higher-level management now being needed at all levels.”
The emergence of AI is not only highlighting the need for human skills to interpret generative outputs or analysis, but also the importance of AI skills themselves for employees responsible for building and training models, or simply those using the models in their jobs.
In an October 2025 report commissioned by Google, PwC formulated an AI skills taxonomy that combined AI-specific concepts like prompt engineering with conventional core and human skills like data literacy and critical thinking that are relevant to AI use and interpretation. A recent post on CFA Institute Enterprising Investor analyzed how an AI taxonomy can help investment firms evolve, particularly in the age of agentic AI.
Equally important is the ability to communicate the methods and results of AI analysis. For example, a report by CFA Institute Research Foundation has advocated more explainable AI in finance, and has also stressed the importance of human oversight and organizational alignment.
Preparation is everything
Skills taxonomies and architectures are most effective if they have been created with an organization’s strategic goals in mind. If a skills structure is not properly aligned, it will be harder to close skills gaps and lead to inefficient recruitment and learning.
And while a skills taxonomy in itself is a way to standardize the language around skills, there needs first to be agreement within an organization on how people will talk about the entire skills landscape and what is meant by certain functions or concepts such as skills, competencies and proficiencies.
This is important because although people often think they know what is meant by many of these terms, there is no common global language or set of definitions to rely on. Some practitioners no longer consider competency as a distinct or useful concept, for instance, even though the term still features in some human resources platforms to mean the application of a skill together with other behaviors and traits to carry out a task – something that today is often termed capability.
Creating a skills inventory that catalogues the skills that employees already have is another essential part of preparation, as it is what will inform the analysis of which skills gaps may exist.
Then comes the taxonomy itself. It will categorize skills according to their high-level nature – such as behavioral or technical – and then through more granular levels.
The Global Skills Taxonomy developed by the World Economic Forum (WEF), for instance, is divided into two broad areas. The first is attitudes, and the second is skills, knowledge and abilities.
Three more levels then break those down into 93 separate skills, spanning human traits such as empathy, persistence or self-control, through to physical or knowledge-based abilities such as cloud computing, project management or dexterity.
The WEF taxonomy aims to find common ground between some of the most frequently referenced skills taxonomies, such as public sector initiatives like the US government’s O*NET, or the European Skills/Competences, Qualifications and Occupations (ESCO) classification, or systems such as Workday in the private sector.
Difficult, but worth it
According to Tunley, it is often not the pace of change that holds organizations back from thinking about skills in a coordinated and structured way. It is instead the effort and complexity involved.
“I think it’s the fact that you have to do a lot of work first,” she said. “You have to come up with a skills taxonomy and an agreement across your whole organization about what’s important.”
The benefits are far-reaching, however. The value of skills taxonomies, frameworks and architectures goes well beyond understanding the skills of existing employees or finding where gaps exist. Designed well, they combine to act as a guide to career paths for employees, revealing where commonalities exist between different functions within an organization. They also help steer employer learning programs by ensuring that they are designed to meet real needs.
And while taxonomies can indeed be fearsomely complex, some practitioners advocate simplicity. Bhushan Sethi, a consultant and also Adjunct Professor at NYU Stern School of Business, favors a taxonomy of no more than 20 skills and then a focus on communicating the relevance and application of those skills to roles.
“The best thing that organizations can do is come up with a simple set of skills and bring that to life, explaining how they apply to different functions,” he said. “Embed them in hiring practices, on-the-job coaching, performance management and succession planning.
“And then make it simple to maintain.”
Discover how experts in the financial industry are creating and managing skills taxonomies and skills development:
Building an effective skills taxonomy: five rules to success
The skills gap challenge: knowing what you have – and what you need
From theory to application: Thinking beyond skills in the financial industry workplace
How AI-powered learning can upskill teams in the investment industry
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