‘I’m happy to say that my job has never been boring’ said the director and head of data

Katherine Leenhouts discusses her work in the data and AI space and offers her advice to professionals who want to emulate her work.

PwC’s Katherine Leenhouts is director and head of data but she never planned her career to go that way. “My path started at university. I started considering a degree in something like Greek literature,” he told SiliconRepublic.com.

“Instead, I went into business after working at two small businesses during summer jobs.

“I studied at PwC, thanks to the guidance of one of my professors, and accepted a full-time role with one of their data analysis teams. After more than 15 years, I’m happy to say that my work has never been boring.”

In addition to AI, data and analytics skills, what skills power your day-to-day work?

Communication is a big part of my daily life. Whether I’m engaging with senior leaders from other organizations, partnering with our leadership or mentoring interns or graduates on my team, adaptability is key. I get that you need to be quick on your feet. You need to be able to go from understanding and digesting important information about a client project to explaining important changes in the data and AI space. That communication comes in many forms, be it presentations, written proposals, required documents, or visual reports. My preference is to communicate in visual formats such as dashboards, slides, reports or other images. There is nothing more satisfying than seeing a complex idea come to life and giving someone the insight they need to make a quality decision.

Are you using any skills you didn’t expect to use at the beginning of your career?

Assessment skills. I like a good set of requirements. When I started, I thought people would know exactly what they needed. What I have found is that the first job is just the beginning. I once asked a client to provide me with a dashboard to track the status of their company’s internal research projects around the world. By asking questions and delving into the requirements, I found out that you had a problem with an audit that took too long to pass its deadline. These were sometimes followed by long repairs. He didn’t want the status of internal audit projects, he wanted a dashboard that gave him an overview of where projects were stuck so he could open them. We have defined the categories of delayed projects. He (and we) wanted data from actual system testers used to do their job, not from a manually reviewed spreadsheet. We delivered a dashboard that updated regularly, requiring no external updates to the system, and gave him the information he needed to take quick, regular action to keep the business focused on improvement. The ability to ask deeply and understand fully is one that is more important than I realized at the beginning of my career.

How important are workplace AI, data and analytics capabilities, in the AI ​​era?

AI fluency is now a basic requirement. Effective use of AI raises the standard of our work. Tools like coding assistants enable us to iterate much faster. AI Agents, LLMs and others can take the job to several levels. It is important for people to know how to use AI to develop and refine their own ideas. Apart from personal guidance, LLMs provide a good quality residue but regular output. We expect each person’s vision and ability to shine. When we interview individuals, we’re looking for people who think critically, ask insightful questions, and excel at solving problems. Candidates who embrace the AI ​​era with a mindset that values ​​curiosity and innovation stand out.

What is exciting about the current role in AI and are there many challenges?

The field of AI is being created and refined every day. It reminds me of the early years of a child. One day they can’t crawl at all, the next they’re all over the house. AI is very much like that. Every week the situation changes. When you work in the field, you are part of the story. That’s exciting. There are many challenges. For many organizations, modern data processing was a nice-to-have rather than a must-have. As a result, it can be challenging to implement advanced AI techniques. Organizations can be vulnerable. Compelling use cases are needed to inform changes in policies to balance the risks involved in the use of new technologies and the benefits and to reduce risks in current processes. On a personal level, adapting to new ways of working is an ongoing effort. What I love about our group is that this routine is often fun and engaging.

What career paths are available for people with skills in AI, data and analytics?

There are two ways I see people becoming good at AI, data and analytics. In the first phase people have basic technical skills, such as programming in Python or SQL, working with data in cloud environments, creating and analyzing data or analyzing the impact of AI on security. If so, at PwC you will find a place in our technology, data and AI team or in our cyber practice. Second, when people are data savvy, they know how to ask good questions and use AI tools to speed up their work.

AI has changed skill expectations in the workplace, how can a strong leader motivate their teams?

Strong leaders set an example. They create spaces for teams to share knowledge and highlight best practices. Change is difficult, especially given the rapid changes in the AI ​​landscape over the past three years. At PwC we help teams navigate these changes by embedding AI experts across the business to facilitate adoption of new practices. Our interns and graduates are trained in the tools available, the application of ethics and our work methods.

Do you have any predictions for how the coming year might play out in terms of AI and automation trends?

I think this is the year where there is a need to start seeing tangible returns from AI investments. We may see the first IPO of an AI company. I expect we will see more LLMs targeted at specific use cases, such as supporting consumer health inquiries. We’re already starting to see more detail in what people are “searching” for LLMs (see Microsoft AI’s About Time: Copilot Implementation Report 2025) – I hope we see more of this. We may begin to notice a clear distinction between companies that use AI to solve business problems and those that carry on with business as usual. Overall, I expect this industry to continue to evolve at a rapid pace and continue to push us to innovate, think creatively and keep moving.

Don’t miss out on the information you need to succeed. Sign up for Daily BriefSilicon Republic’s digest of must-know sci-tech news.