If you’re an actuary today—or thinking about becoming one—you’re stepping into a profession that’s evolving faster than ever. The rise of artificial intelligence (AI) isn’t just changing the tools we use; it’s reshaping the very skills that make actuaries valuable. Gone are the days when crunching numbers in Excel was enough. Now, the most successful actuaries blend deep technical know-how with creativity, communication, and a knack for asking the right questions. This isn’t about replacing human judgment with machines, but about amplifying what we do best by working alongside them. In this article, I’ll walk you through the ten essential skills actuaries need to thrive in the AI era, with real-world examples, practical tips, and a few personal observations from years in the field.

Technical Proficiency and Programming #

Let’s start with the obvious: you can’t ignore technology anymore. Python, R, and SQL aren’t just buzzwords—they’re your new best friends. These languages let you manipulate massive datasets, build predictive models, and automate repetitive tasks. For example, imagine you’re pricing a new insurance product. Instead of manually adjusting rates based on a handful of factors, you can use Python to analyze thousands of customer profiles, spot trends, and even predict which customers might file a claim. That’s not science fiction; it’s what leading firms are doing right now[1][2].

If you’re new to coding, don’t panic. Start small. Pick one language—Python is a great choice—and work through online tutorials. Build a simple model that predicts something fun, like how many cups of coffee your team drinks each week. The key is to get comfortable with the logic of programming, not just the syntax. Over time, you’ll find yourself reaching for code to solve problems you used to tackle by hand.

Data Analysis and Modeling #

Actuaries have always been data experts, but the scale and complexity of today’s data demand a new level of skill. You need to go beyond basic statistics and embrace machine learning techniques. For instance, traditional reserving methods might use historical averages, but machine learning can detect subtle patterns in claims data that humans might miss. This isn’t just about being more accurate; it’s about being faster and more responsive to change[1][3].

A practical tip: Get hands-on with real datasets. Many organizations release anonymized insurance data for research. Download a claims dataset, clean it up, and try building a model that predicts claim severity. Compare your results to traditional methods. You’ll quickly see where machine learning shines—and where human judgment is still essential.

Understanding AI and Machine Learning #

AI isn’t a magic wand, but it is a powerful tool. As an actuary, you don’t need to become a machine learning engineer, but you should understand how these models work, their strengths, and their limitations. For example, a neural network might excel at detecting fraud in insurance claims, but it can also be a “black box”—hard to explain to regulators or customers. That’s where your expertise comes in: you need to bridge the gap between technical complexity and practical, explainable results[3][6].

Start by taking an introductory AI or machine learning course—many are free online. Focus on concepts like supervised vs. unsupervised learning, overfitting, and model interpretability. Then, try applying these concepts to a small work project. Maybe you can use a decision tree to classify policy renewals or a clustering algorithm to segment customers. The goal is to demystify AI, not master every algorithm.

Regulatory Knowledge and ESG Competency #

The world of insurance and finance is governed by a thicket of regulations, and these rules are evolving to keep pace with technology. At the same time, Environmental, Social, and Governance (ESG) factors are becoming critical to risk assessment. For example, an insurer might need to model the impact of climate change on property claims or assess the reputational risk of investing in certain industries. Actuaries who understand these frameworks—and can explain them to stakeholders—are in high demand[1].

Stay informed by following regulatory updates from bodies like the NAIC or EIOPA. Join professional groups focused on ESG. And don’t just read about these topics—try to apply them. If your company is considering a new product, ask how ESG factors might affect its risk profile. Offer to help build a model that quantifies these risks. You’ll not only add value but also position yourself as a forward-thinking professional.

Communication and Presentation Skills #

Here’s a secret: the best technical analysis is useless if no one understands it. Actuaries must translate complex models and results into clear, actionable insights for executives, regulators, and customers. This means writing concise reports, creating engaging presentations, and sometimes, telling a compelling story with data[1][5].

Practice explaining technical concepts to non-experts. Try the “grandparent test”: if you can explain your work to someone with no technical background, you’re on the right track. Use visuals—charts, graphs, even infographics—to make your points clearer. And remember, communication is a two-way street. Listen to your audience’s questions and concerns. Often, their feedback will help you refine your models and assumptions.

Strategic Thinking and Business Acumen #

AI can handle the number-crunching, but it can’t replace human judgment when it comes to strategy. Actuaries need to understand the broader business context—how products are designed, priced, and sold; how markets are changing; and where new opportunities lie. For example, if you’re working in health insurance, you might spot a trend toward telehealth and recommend new products tailored to digital healthcare providers.

To build this skill, get curious about your industry. Read trade journals, attend conferences, and network with colleagues in other departments. Ask questions about how decisions are made and what drives profitability. Over time, you’ll start to see how your technical work fits into the bigger picture—and how you can add more value to your organization.

Leadership and Teamwork #

As you progress in your career, you’ll likely move from individual contributor to team leader. This means not just doing the work, but guiding others, resolving conflicts, and fostering collaboration. The analytical rigor that makes you a great actuary can also make you a great leader—if you’re willing to develop your “soft” skills[5].

Look for opportunities to lead small projects or mentor junior staff. Take a course on management or emotional intelligence. Pay attention to how teams function (or don’t) and think about how you can help everyone do their best work. Remember, leadership isn’t about having all the answers; it’s about creating an environment where everyone can contribute.

Ethical Judgment and Governance #

AI brings incredible opportunities, but also new risks—bias, privacy concerns, and the potential for misuse. Actuaries have a professional responsibility to ensure that models are fair, transparent, and aligned with the public interest. For example, if an AI model used for underwriting inadvertently discriminates against certain groups, it’s your job to spot the problem and fix it[3][6].

Stay informed about ethical guidelines from organizations like the Society of Actuaries or the Casualty Actuarial Society. Participate in discussions about AI ethics within your company. When building models, always ask: Who could this harm? How can we mitigate those risks? By taking ethics seriously, you’ll not only protect your organization but also uphold the integrity of the profession.

Continuous Learning and Adaptability #

The only constant in the AI era is change. New tools, techniques, and regulations emerge all the time. Successful actuaries are lifelong learners who stay curious and adaptable. This might mean taking online courses, attending workshops, or simply experimenting with new software on your own time[3][6].

Make learning a habit. Set aside a few hours each month to explore a new topic—maybe generative AI, cloud computing, or a programming language you haven’t tried yet. Join professional communities where you can share knowledge and ask questions. And don’t be afraid to fail; some of the best learning comes from tackling projects that stretch your abilities.

Innovation and Creativity #

Finally, don’t underestimate the power of creativity. AI can automate routine tasks, but it can’t invent new solutions to complex problems. Actuaries who think outside the box—who ask “what if?” and “why not?”—will always be in demand. For example, you might design a new type of insurance product that uses real-time data from wearable devices, or develop a model that helps cities prepare for climate-related disasters.

To foster creativity, give yourself permission to explore. Brainstorm with colleagues from different backgrounds. Take inspiration from other industries. And remember, innovation doesn’t have to mean inventing something entirely new—sometimes, it’s about applying an existing idea in a fresh way.

Putting It All Together #

Mastering these ten skills won’t happen overnight, and you don’t have to tackle them all at once. Start with the areas that interest you most, or where you see the biggest gaps in your knowledge. Set small, achievable goals—like learning a new programming concept or volunteering to lead a meeting. Over time, these steps will add up to a rewarding, future-proof career.

The AI era isn’t something to fear; it’s an opportunity to do more meaningful, impactful work. By combining technical expertise with communication, ethics, and creativity, you’ll not only survive the changes ahead—you’ll help shape them. And that’s what being an actuary is all about.