When Katherine von Jan suggested that organizations should write job descriptions for AI in the same way they do for humans, including defining responsibilities, setting expectations, and conducting performance reviews, it reframed a question that most technology leaders think they have already answered. The conversation in most boardrooms and technology functions is still about which processes to automate and how quickly. Katherine is asking something more fundamental: are those processes even the right ones, and do you actually know what you are asking AI to own?
Katherine joined our Managing Partner Tony Leng, who leads H.I.E.C’s Global Technology Officers Practice, for the latest installment of our Heads Up interview series. Tony and the team work with organizations across multiple industries to identify and place senior technology leaders and the functions that support them, so the questions Katherine raises sit at the heart of what we see every day across our client base.
Katherine is the co-founder of Tough Day, home of Tuffy AI, a personal workplace advisor built to give employees confidential expert guidance and support to handle complex situations and perform their best, without relying on a manager or HR for help. Before co-founding Tough Day, she spent nearly a decade at Salesforce, where she held a series of senior innovation leadership roles culminating in Chief Strategy Officer, during a period when Salesforce was consistently ranked among the most innovative companies in the world. That experience of building and scaling innovation programs inside one of the world’s most recognizable enterprise technology businesses gives her perspective that is grounded in organizational reality, not just theory.
Her framing of the current moment is one that will resonate with anyone responsible for technology strategy. She draws a distinction between two business philosophies, one shareholder-centric and transactional, the other stakeholder-oriented and developmental, and argues that your position on that spectrum will determine not just how you deploy AI, but the operating model you end up building around it. The same logic applies to talent. Organizations that treat skills as commodities to be bought and discarded will build a very different technology function to those investing in retraining and redirection. Neither approach is inherently wrong, but both are choices that most organizations are making without a coherent framework behind them.
What struck us most was her argument about leadership capability in transformation contexts. Katherine is not looking for the leaders who have mastered the internal politics of large organizations. She is looking for something rarer: curiosity, the willingness to be taught, and the structural courage to relinquish control at the right moments. She described a chief transformation officer at a Fortune 500 company who had hired a group of young AI-native thinkers as reverse mentors, not to replace his expertise, but to stress-test assumptions that could not effectively be challenged by those within his existing network. For technology executives navigating board-level pressure to move faster while managing organizational risk, that kind of deliberate outside-in thinking is increasingly a competitive differentiator, not a nice to have. “I think that’s really brave and exciting,” she said. We agree.
Her background adds useful texture. Trained as an anthropologist, Katherine spent the early years of her career at the intersection of human behavior and emerging technology, including working with the CIA on intelligence methodology during the early internet era. The core question then was how to decide which parts of a complex human process could be augmented or transformed by technology, and which required human judgment to remain at the center. It is precisely the question that CIOs, CTOs, and chief data officers are being asked to answer now, often at speed and at scale.
The most pointed thread in our conversation was around power and consolidation. Katherine is building what she calls a human-positive index, a framework anchored in AI ethics, workplace empowerment, collaborative ecosystems, and built for a pro-human future rather than the post-human narrative she sees forming around AI infrastructure. For board members and transformation leaders thinking about governance, vendor dependency, and long-term organizational resilience, it is a framework worth paying attention to.
Her practical advice for leaders is less a technology roadmap than an organizational disposition: audit the process before you automate it, write the job description before you build and deploy the AI, and create enough structural space for the people closest to the work to tell you what is actually broken.
You can explore the full Heads Up series here, or get in touch with Tony and the team directly if you’d like to continue the conversation.
Tony Leng
Managing Partner
Email: tleng@hiec.com
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