My father’s early belief in me as a budding engineer allowed me to never once question my ability to become a female engineer or leader.
As AI technology rapidly advances, ensuring its responsible development and deployment has become more critical than ever. How are today’s AI leaders addressing safety, fairness, and accountability in AI systems? What practices are they implementing to maintain transparency and align AI with human values? To address these questions, we had the pleasure of interviewing Kerstin Woods.
Kerstin Woods is Chief Solutions and Marketing Executive at Toshiba America Business Solutions, where she leads the company’s software, cloud and AI go-to-market strategy as well as outbound marketing across their hardware and software portfolio. A member of Toshiba’s Executive Leadership Team, Woods is a key architect behind initiatives to modernize ordering, lifecycle management, and customer experience through intelligent automation and data-driven design. With more than two decades of experience spanning hardware, enterprise software, cloud computing, product strategy, and marketing leadership, Woods has built a career helping organizations navigate major technology transformations. Prior to Toshiba, she held positions at Oracle and Sun Microsystems, where she focused on new business development, cloud solutions and partner ecosystems. She holds a degree in Mechanical Engineering from Stanford University and has been recognized for her ability to bridge complex technology with practical business outcomes. As executive sponsor of Toshiba’s AI initiatives and AI Task Force, Woods is passionate about ensuring artificial intelligence is deployed quickly, responsibly, transparently, and with meaningful oversight. She believes AI’s greatest potential lies in empowering teams to solve bigger problems, make better decisions, and create more value.
Thank you so much for joining us in this interview series! Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
My journey into technology started early as a young girl growing up in rural Colorado. My father was an aerospace engineer who instilled in me a fascination with how things work — including how to take them apart to rebuild them. That curiosity led me to study Mechanical Engineering at Stanford, where I was one of the relatively few women in the program at the time. My father’s early belief in me as a budding engineer allowed me to never once question my ability to become a female engineer or leader.
Engineering taught me how to break complex problems into manageable pieces, but I quickly realized that technology alone doesn’t change organizations — people do. Early in my career, while building rockets at an aerospace company myself, I discovered that one of the rarest and most valuable skills is the ability to explain complex technologies in ways that people can truly understand and appreciate. That realization sparked my passion for marketing and being a “translator” — turning complex technology into simple, relatable, and compelling business value.
None of us can achieve success without some help along the way. Is there a particular person who you are grateful for, who helped get you to where you are? Can you share a story?
My mother had the biggest impact on my life. She raised me as a single parent after my father passed away and taught me resilience long before I understood what that meant. She never allowed difficult circumstances to become excuses. I remember watching her consistently choose action over complaint. When challenges appeared, which they inevitably did, she focused on solutions. That mindset became foundational to my leadership style. Throughout my career, whether navigating major business transformations, launching new technologies, or leading teams through uncertainty, I’ve tried to approach challenges the same way: focus on what can be built, improved, or solved rather than dwelling on obstacles.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
1) Authenticity. In my first engineering role, I was given advice that never felt right to me. I was told to avoid personal conversations at work, skip lunches with colleagues, and maintain distance from people I might someday manage. The thinking was that leaders should keep their personal and professional lives completely separate.
However, I’ve always felt that if we expect people to bring their best selves to work, we have to recognize that they are whole people with lives, responsibilities, and passions outside the office. While setting boundaries is definitely important, I believe great leadership starts with genuine connection. I’m not just an employee — I’m also a mom to two amazing teenagers, the only child of a parent with Parkinsons, a board member, a school volunteer, and a Stanford alumni interviewer. I have good days and bad days. All of those shape who I am. Ultimately, I’ve found that when leaders show up authentically, it gives others permission to do the same. The result is stronger trust, deeper engagement, and ultimately better teams.
2) Curiosity. Early in my career, curiosity led me beyond traditional engineering into startups and emerging technologies, including cloud computing long before it was even called “the cloud.” That willingness to explore unfamiliar territory — and the courage to step outside my comfort zone — has consistently opened doors and shaped my leadership path. Simply put, never stop asking questions. Technology evolves too quickly for anyone to assume they have all the answers! The leaders who thrive are the ones who remain lifelong learners, constantly challenging assumptions and seeking new perspectives. And that’s never been more important than in today’s age of AI, where 𝐇itherto unknown technical shifts are occurring every day.
3) Adaptability. As the adage goes, the only constant is change. Great leaders must be willing to decide quickly and adapt constantly. Just in the last few years, we’ve navigated the rise of cloud computing, a global pandemic, supply chain disruptions, chip shortages, and now the extremely rapid emergence of AI. At any given moment, leaders will face challenges they didn’t — and couldn’t — anticipate. If you’re unwilling to adjust your plans and embrace change with a positive mindset, you’ll break instead of bending. I’ve found that great leadership isn’t about having all the answers; it’s about 𝐀rchitecting flexible strategies and staying nimble enough to find the next right path forward. By 𝐂atalyzing these shifts in perspective, leaders can lead their organizations through any storm.
Let’s now turn to the main focus of our discussion about how AI leaders are keeping AI safe and responsible. To begin, can you list three things that most excite you about the current state of the AI industry?
Speed. The pace of AI advancement is thrilling. Since it requires little to no upfront expertise or infrastructure to get started anyone can begin using, or even creating, tools that would have been impossible just a few years ago (even months ago!). I’ve watched everyone from my teenage children to seasoned business leaders adopt new ways of working in an incredibly short period of time, and the fact that virtually anyone can take advantage of it is really exciting.
Capability. AI extends human capability far beyond our individual education, experience, or exposure. It allows people to accomplish tasks that would have previously required specialized expertise. For example, I haven’t built complex charts in a spreadsheet in over a decade, yet today I can create them in minutes with AI assistance and no ramp-up period. It doesn’t replace expertise, but it dramatically expands what each of us can accomplish. Today, if you’re curious and conversational with AI, you can accomplish nearly anything you put your mind to.
Collaboration. AI helps break down traditional barriers between teams, functions, and areas of expertise. Groups that once worked in separate silos can now access information, insights, and ideas more easily than ever before. As a result, I’m seeing greater collaboration across organizations, with people solving problems together rather than operating within the limits of their individual departments. In many ways, AI is becoming a catalyst not just for productivity but for better teamwork and innovation.
Conversely, can you tell us three things that most concern you about the industry? What must be done to alleviate those concerns?
Speed is a double-edged sword. While AI is allowing us to innovate and develop faster than ever, it’s also creating opportunities for mistakes, vulnerabilities, and security gaps to rapidly perpetuate. We can move incredibly quickly, but we still need to slow down enough to validate results, test for vulnerabilities, and ensure quality. That creates great tension between speed and diligence, but it’s a tradeoff worth making.
False information remains a major challenge. I’ve personally had instances where AI-generated research was completely inaccurate. In one case, when I asked for sources, it even provided citations from the future! Experiences like that are a powerful reminder that AI should augment human judgment, not replace it. We still need subject matter expertise, critical thinking, and validation before using AI-generated information to make important decisions.
Governance is still evolving. One of the biggest challenges is that many of us are trying to establish rules and guardrails while the technology itself is changing at an extraordinary pace. As a result, I’ve seen some organizations respond by putting very restrictive limitations around AI usage, while others are moving ahead with few boundaries at all. The answer is somewhere in the middle. We need governance frameworks that enable innovation while protecting security, privacy, intellectual property, and customer trust.
As a CEO (CMO) leading an AI-driven organization, how do you embed ethical principles into your company’s overall vision and long-term strategy? What specific executive-level decisions have you made to ensure your company stays ahead in developing safe, transparent, and responsible AI technologies?
We’ve implemented several practices to ensure ethical principles are embedded into our approach to AI:
Controlled adoption. Only AI tools that have been reviewed and approved by our corporate IT organization can be deployed at scale. This helps ensure appropriate standards for data protection, intellectual property, confidentiality, compliance, and accuracy.
Governance before deployment. New AI initiatives must undergo both security and business-value reviews before moving forward. Proposed projects are evaluated by IT, legal, and executive leadership to ensure they align with our security requirements, risk tolerance, and strategic objectives before a proof of concept is approved.
Cross-functional oversight and knowledge sharing. We established an AI Task Force that brings together stakeholders from across the business monthly to share best practices, evaluate emerging use cases, identify potential risks, and accelerate innovation while avoiding duplication of effort.
Skills or specialized AI agents with stricter rules/knowledges sets representing the human “skill” will become sellable or available. Look at it as Matt has a special skill with automatic toner systems that is transferred into an AI skill with knowledge, boundaries and domain understanding. This skill and domain expertise allow the agent to understand when it is dealing with misinformation, just like we do.
Our philosophy is that responsible AI isn’t a separate initiative; it is a governance framework that must be integrated into every stage of adoption, from evaluation and deployment to ongoing monitoring and improvement.
Have you ever faced a challenging ethical dilemma related to AI development or deployment? How did you navigate the situation while balancing business goals and ethical responsibility?
One of the challenging realities of AI is that it already automates tasks that humans perform today. As a leader, that’s a difficult reality to navigate because there are real people behind those roles. My responsibility is to ensure that AI is used to elevate the workforce, not simply to reduce it. The goal should be to upskill employees, allowing them to focus on higher-value work while the organization becomes more capable and productive overall. It also needs to help employees perform better, not just reduce their workday.
On a more personal level, I also wrestle with how AI is changing content creation. It is becoming increasingly difficult to distinguish between someone’s original thinking and content that was generated by AI. My personal belief is simple: if you can’t stand on a stage and confidently explain, defend, and expand upon what AI helped you create, then you’re misrepresenting your expertise. For that reason, I tend to use AI as a thought partner, researcher, and editor rather than relying on it for entirely new ideas. I believe AI should amplify human intelligence and creativity, as opposed to replacing them.
Many people are worried about the potential for AI to harm humans. What must be done to ensure that AI stays safe?
AI safety needs accountability. The companies building these technologies can’t simply release them into the world and hope for the best. AI can harm people with good intentions and exponentially multiply the actions of people with evil intentions. Powerful technology in the hands of bad actors accelerates their ability to do bad things. And, we’ve already seen tragic situations where AI systems encouraged self-harm or dangerous behavior. As AI becomes more capable, there must be meaningful safeguards, oversight, and consequences when companies designing these tools fail to act responsibly. Innovation is important, but not at the expense of human safety. I think something else that is concerning isn’t even AI harm, but AI relationship — it’s dangerous to be in a human-like relationship with code. People are putting down their guard because it can “feel” so lifelike, and that’s also very worrisome. It creates a trust relationship with something inanimate that should not be trusted.
Despite huge advances, AIs still confidently hallucinate, giving incorrect answers. In addition, AIs will produce incorrect results if they are trained on untrue or biased information. What can be done to ensure that AI produces accurate and transparent results?
AI results still need human validation and oversight. I always ask for sources and check them before taking research results at face value. We need to challenge AI results and not assume they are true.
Here is the primary question of our discussion. Based on your experience and success, what are your “Five Things Needed to Keep AI Safe, Ethical, Responsible, and True”? Please share a story or an example for each.
1. Insert human validation. I recently had AI build a chart to analyze some data, but upon inspection, several of the data points were taken from the wrong row and completely threw off the results. Human oversight is still key.
2. Request and check sources. As previously mentioned, when doing research, it provided me with amazing responses — exactly what I was looking for! But when I asked for sources, it cited a few studies in the future that were clearly erroneous. It knew what my hypothesis was and was falsifying data to help me prove it.
3. Require IT and legal oversight. Even a small widget for things like AI note-taking can gain access to your corporate systems. Every single AI item used in your business should be vetted by IT. To keep those AI eavesdroppers out, we ended up adding a verification step to ensure only humans enter our Teams meetings.
4. Drive accountability. If you hear of an unauthorized tool being used, give people the trust and freedom to flag it. We had someone doing development work on an unapproved AI tool. Thankfully, it did not gain access to our corporate information, but we had to shut it off immediately and bring it to the leadership team to assess if we should invest in it with the approved tools.
5. Promote AI literacy. If your teams are not hearing from their managers about the right and wrong way to use AI, they will set their own boundaries. Communicate early and often about your governance process and make sure there is a clear path for AI requests — we’ve set up a submission process to gather AI ideas and try to streamline tool approvals. And then take the time to do training or sharing of AI best practices across your business for those approved tools.
Looking ahead, what changes do you hope to see in industry-wide AI governance over the next decade?
I think sweeping boundaries or regulations need to be in place to quickly flag and contain the bad actor edge cases.
What do you think will be the biggest challenge for AI over the next decade, and how should the industry prepare?
I think AI will do as most technologies do — widespread proliferation followed by constriction. I think people will invest time and money in AI tools that end up going away because the ROI just won’t be as impressive as people thought. I think AI will fix some key use cases, but it won’t live up to the hype on others and the industry should prepare for that to happen.
You are a person of great influence. If you could inspire a movement that would bring the most good to the most people, what would that be? You never know what your idea can trigger. :-)
I’d love to see AI sense self-harm patterns and have the ability to call for help via the suicide hotline, local church, or other avenue (maybe, upon setup, we can enter our preferred emergency contact). As someone who has lost a loved one to suicide and who has volunteered for the suicide hotline, it would be amazing if AI would be able to help people when they are in a dark place to find the light.
How can our readers follow your work online?
I’m horrible at self-promotion, but my LinkedIn or our blog pages are great ways to see how we’re using AI to advance workplace productivity and beyond.
Thank you so much for joining us. This was very inspirational.
About The Interviewer: Gabriel Borden is an American investor, advisor, and entrepreneur. He is the managing partner of Arrow Fund, a private investment firm. In that role, he has overseen investments spanning technology companies, private markets, media, and special-situations opportunities. Borden attended Loyola Marymount University from 2012 to 2016, where he studied business. At Arrow Fund, Borden leads a firm focused on technology, private markets, and event-driven opportunities. The fund has invested in a number of private companies tied to innovation and growth sectors. Publicly reported investments have included Polymarket, the prediction market platform; SpaceX, the aerospace company founded by Elon Musk; and Valar Atomics, among other private technology businesses. The firm has also expanded beyond minority investments into direct ownership of operating companies. In a recent transaction, Arrow Fund acquired a majority interest in LeVecke, a California-based bottling and beverage manufacturing company. The deal signaled a broader strategy that combines financial investing with hands-on ownership in established industrial businesses. Before launching Arrow Fund, Borden held senior roles managing capital for prominent entrepreneurs and private investors. He previously served as managing director of the family office of Brock Pierce, where he worked on investment management and portfolio strategy across technology, media, and real assets. Family offices, which manage wealth for individuals or families, often invest with longer time horizons than traditional funds and can move across industries with greater flexibility. In that setting, Borden’s responsibilities included evaluating opportunities and overseeing portfolio decisions in multiple sectors. Borden comes from a family involved in creative and design fields. He is the son of filmmaker Bill Borden, a producer known for commercially successful films including the High School Musical series, La Bamba, Desperado, and Kung Fu Hustle. His mother, Melinda Gray, is an architect and the founder of Gray Matter Architecture, a firm focused on modern design. That background placed him in an environment shaped by both entertainment and entrepreneurship, industries that often rely on risk-taking, financing, and long-term project development. While Borden’s own career has centered on investing rather than film or architecture, those influences connect his professional path to a broader family history of business and creative work. He is married to Sydney Borden, and the couple live in Santa Monica, California. As private markets continue to attract more capital and expand their reach into sectors once dominated by public companies or strategic buyers, investors like Borden represent a model of finance that blends traditional portfolio management with direct ownership and operational involvement.
