We got lucky. A large part of our consulting practice involves working with private equity funds. Through that channel, we became acquainted with the folks at OpenAI. They saw us as being technically quite competent, and when they launched GPT, they didn’t fully anticipate the overwhelming response from the enterprise market. At the time, OpenAI was a relatively small organization — about 300 employees.

As a consulting firm with deep expertise across key verticals — healthcare, financial services, and manufacturing — we had the industry presence and domain knowledge necessary to effectively apply large language models (LLMs) in ways that drive real business value. That domain knowledge is critical when crafting applications that overlay AI models to deliver meaningful impact.

OpenAI really welcomed us into their ecosystem and helped us educate clients on the art of the possible. In return, we’ve played a key role in helping them address the massive demand in the corporate marketplace.

To date, we’ve completed over 300 ground-up solution builds and implementations across all major industries and business functions — customer service, marketing, R&D, supply chain, finance, and beyond. With boots-on-the-ground experience, we’ve been at the forefront of helping clients adopt this technology. Additionally, we’ve worked closely with IT and data science teams, helping them develop critical competencies like prompt engineering, retrieval-augmented generation (RAG) databases, and the skills necessary to build and sustain their own AI-driven solutions.

Our role is to get organizations started, but ultimately, they must be equipped to take ownership — maintaining and scaling these tools as true business products.

That’s one of my favorite questions. In fact, I’m running an event that Bain is co-sponsoring with Women in Data Science to explore this very topic. It’s still early days, and while we feel like we have a bit of a lead in this area, we’re learning every day about what’s going to be required moving forward.

In the short term, we’re seeing some very specific talent gaps, particularly in the builder community — the IT and data science teams that are struggling to figure out how to build and implement these applications. These gaps are especially pronounced for organizations that aren’t traditionally software companies. Most IT departments don’t build software from the ground up, so we’re working with them to understand how to establish cross-functional teams.

This includes bringing together domain experts, data scientists, and legal teams to ensure that what they’re developing is not only effective but also compliant with regulatory requirements. It’s been exciting to help clients build that competency, identify key job roles, and attract the talent needed to scale these efforts.

On the functional side, I’m currently working with a commercial and marketing organization, and what we’re seeing is that implementing these tools is fundamentally changing the role of the marketer. It’s not just about upskilling — it’s about AI literacy, training, and even business process redesign. These tools don’t just change how tasks are performed; they transform workflows.

For example, a client that previously relied on agency resources for parts of the creative process can now bring that work in-house. This shift empowers marketers to take control of content creation, personalize messaging for specific segments, and own more of the creative process.

There’s often concern that AI will replace jobs, and while some repetitive tasks may be automated, we’re also seeing it create new opportunities. In this case, marketers are gaining the ability to do work they would have previously outsourced. So while some routine work may be supplanted, many new roles and responsibilities will emerge.

At our upcoming event, we’re bringing together professionals from the builder community, business transformation leaders, and HR teams to explore both the immediate upskilling needs and the long-term impact. Because this technology isn’t just about replacing old work with a new approach — it’s enabling entirely new kinds of work that were never possible before. The real opportunity lies in true innovation and business model transformation, which is incredibly exciting as we look ahead.

I saw a demonstration — one of our lead creative people from our innovation design team was showcasing MidJourney and some of the new tools and functionalities available through Figma, which are widely used in the design world. What he was able to accomplish with those tools just blew me away and made things very clear to me.

Give me those tools, and I don’t have the creative skills or background to produce the same kind of output he was generating. So, it really reinforces this idea — how these advancements are fundamentally changing the value of the human in the loop. His skill set and ability to maximize these tools’ potential is incredible, making his role even more valuable.

We all spend our careers building expertise, but now, when all the knowledge on a given topic is instantly accessible — whether through a keyboard or simply speaking to an LLM, what does expertise truly mean?

These tools will augment and amplify the value of expertise rather than replace it. And then there are the softer skills, which have always been crucial. We need people who can assemble cross-functional teams, who have strong interpersonal and communication skills to drive the innovation process. While our raw capabilities are being enhanced by LLMs, the human-centric skills will become even more critical.

I’ve been really lucky to have been surrounded by incredibly talented women. The team at FICO is mostly women, which is somewhat of an anomaly. The statistics show that women hold under 15% of leadership positions in data science and AI. We’d love to see that number climb to at least 30% because research indicates that 30% is the tipping point where the dialogue truly shifts.

For example, studies on women’s participation in boards — typically composed of 10 to 12 members — show that having just one or even two women doesn’t significantly change the conversation. But at three, it creates a quorum, and the dialogue really evolves.

At WiDS, we are deeply committed to supporting women in their careers, encouraging them to pursue advanced degrees, and helping them maximize their college or university experiences. Our goal is to inspire women to reach their full potential and increase their representation at leadership levels.

This is especially crucial when we consider the importance of communication and collaboration — soft skills that are vital for building high-functioning, innovative teams. Beyond that, there are significant ethical and societal implications tied to this technology.

The data that many AI models are trained on is inherently biased because it reflects the world we live in. That’s why diversity, in all its forms, is essential at the decision-making table. We need diverse perspectives to critically examine these biases and ensure the ethical and responsible application of AI models — now more than ever.

We can’t rewrite history, but we can apply critical thinking and judgment to how these technologies are implemented

The ability to function within a cross-functional team is crucial. When I say diversity, I mean it in all its forms — because, ultimately, it’s about diversity of thought and background. To become a meaningful change-maker in this next wave of technology, focus on honing teamwork skills. It’s essential to collaborate effectively with individuals who bring diverse perspectives and to harness that diversity of thought to drive great outcomes.