AI is rapidly changing just about every workplace in one way or another — even ones you might not expect.
Take the researchers who used AI to read ancient scrolls for the first time, or the scientists using AI to run hundreds of “what if” scenarios to predict natural disasters.
AI’s role in the workplace will only increase — McKinsey & Company found that over the next three years, 92 percent of companies plan to increase their AI investments, which is why Built In was interested in highlighting professionals who have leaned into the cutting-edge field, sometimes through unexpected paths.
JPMorganChase is a global financial services firm providing investment banking, asset management and consumer financial services.
What’s your professional or academic background? How did you break into the tech industry?
I earned a finance degree from the University of Virginia and began my career in banking before pivoting to serve as a special agent in the FBI. That chapter sparked my interest in technology, offering unexpected opportunities to leverage innovations for enhancing investigations and saving lives. When I explored roles outside the FBI, a technology leader at JPMorganChase recognized my drive and gave me an opportunity, believing in my ability to upskill and learn in the absence of traditional credentials.
The highlight of my 14-year service with the FBI was serving as an operator on the Hostage Rescue Team, where I took on collateral duties that introduced me to product and project management – building the night vision goggle program and modernizing navigation and rebreather systems for closed-circuit diving. Realizing my ambition to work in cybersecurity, I looked to the FBI’s Cyber Division where I built partnerships, led cyber threat intel sharing and managed incident response against sophisticated threat actors. As a senior leader in the Operational Technology Division, I guided teams delivering mission-critical capabilities and innovation, including hardware and integration for the FBI’s body-worn camera program.
How did you learn how to use AI, and how do you apply it to your work?
As I transitioned from the FBI to JPMorganChase, a mentor encouraged me to immerse myself in emerging tech – especially AI. Beyond what I learned in my own research, I’ve benefited from the firm’s AI-forward culture and internal resources which include foundational overviews, lectures and demos to help employees learn how to use AI responsibly. I became an early adopter of JPMorganChase’s award-winning LLM Suite, a proprietary generative AI platform which I use regularly to refine executive communications and ensure tone, depth and structure align with audience needs. I now lead a global team of cybersecurity architects supporting a portfolio of internal products, external apps and cloud infrastructure, much of which leverage or host AI/ML functionalities. Conventional security patterns don’t always apply, so we use AI to structure review frameworks, generate threat models and build and query a corpus of published work for quick reference. These tools are helping us scale security, develop new architecture patterns and uplift the firm’s tech ecosystem.
What do you consider the greatest benefit of leveraging AI? How has it positively impacted the work you produce as a whole or your career?
In product security, we’re seeing material benefits from AI. First, it’s dramatically improving the precision and speed of our written communications – refining executive updates, decks and talking points and saving hours of manual effort. Second, AI is helping our team rapidly upskill and close knowledge gaps, enabling real-time understanding and faster, more accurate responses to complex engagements and security questions. Third, we’re using the firm’s AI Threat Modeling Co-Pilot (AITMC) to help us better standardize and scale security reviews across numerous AI/ML-enabled apps. AI is reducing toil, automating legacy processes and freeing our architects to proactively engage with product teams, business stakeholders and vendors to focus on securely enabling emerging tech and legacy infrastructure. From a career perspective, I think it is opening the door for rapid learning and prototyping and going to provide incredible opportunities for those who take the time to learn and leverage it.
Flywire is a global payments enablement and software company, providing digital payment solutions across education, healthcare, travel and B2B sectors.
What’s your professional or academic background? How did you break into the tech industry?
I grew up fascinated by how things work, always wanting to take things apart and put them back together. That intellectual curiosity would follow me throughout my career. In college I chose a degree in finance that helped land my first job at a financial services company. This was during the dot-com boom and I took a QA role working on a new pricing platform replacing a legacy COBOL solution. I loved understanding software principles while finding ways to break the software to help developers build better solutions. At that point, I knew I wanted to focus my career on technology.
From 1998 to 2000, I learned Java, HTML and JavaScript through continuing education. I transitioned to web development but often led QA initiatives due to my expertise. This sparked my automation-first principles — I wrote routines to automate test cases across different servers and browsers, building rule engines that generated reports with developer recommendations. This foundation in automated solutions became my launching pad for AI and process optimization.
How did you learn how to use AI, and how do you apply it to your work?
My AI learning journey really began around 2010 through working with data science teams and online training via Udemy and Coursera. I’ve learned extensively through peers and their personal innovations, attended meetups and conferences to expand my learning — developer conferences for art of the possible, business conferences for pressure-testing AI use cases. While I’ve benefited through formal training, I believe in learning by doing and that is usually done best on the job. In 2014, our focus at my former employer was shifting toward modern data architectures leveraging technologies like Hadoop and Spark where we could start to perform machine learning at scale and in real time for use cases like streaming analytics and sentiment analysis. Then in 2017, augmented analytics emerged with NLG, NLQ and intelligent insights, so it was at that time that we started producing insight narratives leveraging AI for clients.
ChatGPT’s 2023 arrival felt like AI finally arrived in full force. Today at Flywire, I personally use gen AI throughout my day for communication, presentations, documentation, brainstorming and research, always verifying outputs while adding my personal touch.
What do you consider the greatest benefit of leveraging AI? How has it positively impacted the work you produce as a whole or your career?
AI’s greatest gift is leverage — automating repetitive tasks to free human creativity. In our always-on world, we need more time for priorities. AI delivers that promise, creating workforce productivity equivalent to entire FTEs.
Time liberation: AI handles non-value-add manual activities. A colleague’s philosophy resonates: “I ask myself what I don’t want to do today, then build AI to do it.” This reframes AI as liberation, not replacement, freeing us for strategic thinking and creative problem-solving.
Rapid prototyping: Teams can build functioning demos in hours versus weeks. Product managers create powerful prototypes without developer resources, transforming stakeholder conversations from theoretical to practical evaluations.
Scalable architecture: Embedding AI directly into the data management process — intelligent data quality, auto-scaling, automated modeling are a few examples. At Flywire, we’re modernizing capabilities to create leverage through AI agents, enabling smaller teams to manage complex systems while delivering better stakeholder outcomes.
Carbon Robotics is an agricultural tech company that builds automatic robots, like the LaserWeeder.
What’s your professional or academic background? How did you break into the tech industry?
I broke into the tech industry through hands-on work, not a diploma. I was doing plumbing and not in my wildest dreams did I think I would end up working in the robotics/AI industry. I started working at Attabotics as a laborer. After working there for about two months I asked a very simple question that kickstarted my whole career: “Can I work on the robots?” This simple question triggered a passion for robotics that I didn’t know existed. This cascaded into working as a robotics technician, a field service engineer, then a deep learning quality specialist and now a performance escalation engineer, with an emphasis on how to automatically monitor and detect issues with our LaserWeeder.
How did you learn how to use AI, and how do you apply it to your work?
I have learned to use AI mostly from YouTube. It is such an amazing resource to be able to learn from the experts in any field. In my previous role as a deep learning quality specialist, I worked very closely with our deep learning system. With learning more about AI systems in this role, I learned that I was not fully appreciating the power and capabilities of AI. I could use it to greatly increase my productivity at work. If I needed an experiment template for work, I didn’t need to spend an hour writing it up. I could simply spend five minutes prompting it with my needs and it does all the time-consuming work for me. I am in the middle of attempting to create an AI chatbot that can retrieve information from our numerous documents when prompted with a question. I will be referring to YouTube and coworkers as I am still very inexperienced in the actual creation of AI systems.
What do you consider the greatest benefit of leveraging AI? How has it positively impacted the work you produce as a whole or your career?
The greatest benefit of AI is time. I can spend my time focusing on more important tasks than reformatting a document. It also acts like a nonstop brainstorming partner. When I’m stuck, a quick prompt sparks fresh ideas or uncovers angles I hadn’t considered. This impacts my career in multiple ways. First, it accelerates my learning abilities. I can offload tedious tasks and focus on learning more about our system and ways it can be improved. Second, without AI I wouldn’t have the job I currently have. AI has opened up millions of new jobs and kicked off potential new chapters for all of us.
Embroker cuts through insurance complexity with custom quotes and hassle-free coverage tailored to each industry.
What’s your professional or academic background? How did you break into the tech industry?
My career path hasn’t been linear, but every step prepared me for where I am today. I studied business marketing and management at Penn State and spent over 10 years in the insurance industry in sales, marketing and leadership roles. While working as a broker at Brown & Brown, I became increasingly interested in how technology could change the game for insurance.
At Embroker, I initially supported our traditional MGA arm, while our direct side led innovation with insurance tech. That contrast motivated me to pursue a master of computer and information technology through UPenn, blending my industry experience with technical expertise. What started as curiosity about engineering led me to dive deeper into AI — especially after learning about its fascinating history and real-world potential.
How did you learn how to use AI, and how do you apply it to your work?
I gained a strong foundation in AI through UPenn’s MCIT program, with coursework in machine learning, natural language processing and deep learning. My academic work gave me both the technical depth and context to start building practical AI tools, and I supplemented that learning with hands-on experimentation using open-source platforms.
Beyond coursework, I joined group projects and online student communities, where real collaboration helped bridge theory and application. That learning now shows up daily in my work at Embroker — especially in projects like our AI Underwriter, which was built to streamline the quoting process. That tool even earned a tech innovation nomination from Business Insurance Magazine, which was a great moment for our team.
What do you consider the greatest benefit of leveraging AI? How has it positively impacted the work you produce as a whole or your career?
The greatest benefits of leveraging AI lie in its capacity to enhance operational efficiency, foster innovative solutions and bridge communication across diverse organizational functions.
Understanding the underlying science of AI allows for more effective utilization, transforming it from a misunderstood phenomenon into a powerful and approachable toolkit. It’s similar to how understanding the mechanics and construction of a car inherently enhances a race car driver’s performance — making sure one grasps the science behind AI is critical to leveraging it fully.
AI has significantly advanced my professional capabilities by enhancing strategic decision-making, streamlining operations and fostering innovation within the insurance and technology sectors. My background in sales and sales management enables me to leverage my skill set creatively, enhancing my ability to integrate AI-driven solutions in practical and impactful ways.
HopSkipDrive is a technology company that solves complex transportation challenges through the HopSkipDrive marketplace, which supplements school buses and existing transportation options by connecting kids to highly vetted caregivers on wheels.
What’s your professional or academic background? How did you break into the tech industry?
I started my career as an eighth-grade math teacher, teaching at a magnet school for English learners, where I quickly developed an appreciation for effective student transportation: Buses were critical for my students’ commute to school.
My classroom experience sparked a desire to contribute to systemic change within the K-12 education system. After a period of growth as a management consultant, I returned to Denver Public Schools to lead district strategic planning and voter initiatives.
As Denver Public Schools’ first operations chief of staff, I managed complex districtwide initiatives, including a significant bell time change to facilitate later high school start times. This experience highlighted the impact of data on effective student transportation, prompting me to seek opportunities in the edtech space.
With this background, I joined HopSkipDrive to lead the development and scaling of RouteWise AI, the first transportation intelligence platform. RouteWise AI empowers districts with strategic insights into current operations and optimized transportation plans that solve districts’ critical challenges such as budget cuts and driver shortages.
How did you learn how to use AI, and how do you apply it to your work?
My journey in AI has been self-taught and greatly influenced by my peers.
With our RouteWise AI model, we utilize a machine learning algorithm that evaluates millions of calculations and thousands of scenarios to create optimal transportation plans. This has been a valuable experience alongside our engineers and product managers, as we continually adapt to new constraints and district needs. In addition, I listen to podcasts such as AI Explained and subscribe to various newsletters like The Information. I also discuss new features and innovative uses of AI with my team and I stay up to date with the latest developments through HopSkipDrive’s AI Ambassadors program, which empowers employees to become leaders by connecting them with a network of experts and creating space for their innovations.
AI provides me with tools that drive tangible benefits, such as using AppScripts to integrate new data sets, employing a research assistant to streamline insights from our sales meetings and utilizing a custom tool to draft new marketing materials and reports on sales prospects.
What do you consider the greatest benefit of leveraging AI? How has it positively impacted the work you produce as a whole or your career?
The greatest benefit of leveraging AI in student transportation is its ability to unlock previously unthinkable analyses and optimizations that directly benefit students and school districts. It’s about moving beyond simply identifying problems and truly finding comprehensive solutions.
At HopSkipDrive, we see this impact firsthand. Our proprietary AI and machine learning technology doesn’t just rearrange a district’s existing vehicle assets; it analyzes the entire transportation landscape to deliver optimized transportation plans and always-on insights into current operations. This has impacted the work we produce and, by extension, the operational efficiency and budgetary health of school districts.
For example, with a district partner in West Virginia, RouteWise AI has evaluated over 400 different scenarios, allowing for effectively balancing competing variables in transportation such as bell times, student commutes and budget needs. Previously this work would have required months of manual calculation. By using AI, we can provide solutions in hours. I am excited to expand this offering, as it saves school districts money and enhances student access to education.
