KC Has Work Cut Out for AI and People, Charting the Contours of the Human Tech Joint Venture
The irony of being appointed chief people officer of OpenAI will not be lost on Arvind K C. His job will be to lead a team of highly motivated individuals with rare skills to create products that will displace workers at enterprises that AI firms see as clients. This is the fundamental paradox at the heart of the AI revolution: those building the technology are also those who will be most affected by it, albeit in different ways.
The Dual Mandate
OpenAI and its rivals are working on an array of automated workflows that can be embedded in businesses, which will supplant existing employees’ skills, but will also create a demand for new skills. This is not a simple story of job destruction; it is a complex narrative of transformation, displacement, and creation.
Agentic AI that can accomplish several business processes without guidance still requires human intervention to build protocols and audit systems. Friction must be deliberately introduced in automated workflows to provide human employees with context in error management. Ethical questions also need to be answered by humans, including assigning levels of delegation.
The machines may do the work, but humans must decide what work should be done, how it should be done, and under what conditions. The human element does not disappear; it migrates to higher levels of abstraction.
The Talent Paradox
Employees in AI firms sit at the other end of the scale, where their skills, now, are irreplaceable. This makes management of such talent pools a complex undertaking. There is an element of “flying by the seat of your pants” to this endeavour because of the lack of precedents, while the target keeps shifting.
How do you manage people whose skills are so rare that they could walk out the door and have multiple job offers by the end of the day? How do you motivate individuals who are building the very technology that will make many traditional jobs obsolete? How do you create culture and cohesion in a field that changes so rapidly that yesterday’s best practices are today’s obsolete procedures?
These are not questions with textbook answers. They require experimentation, intuition, and a willingness to learn by doing.
The Human Variable
Human resources are the key variable in an industry whose energy and computation needs follow strict physical laws. And the investor frenzy over AI makes it difficult to weed out the good ideas from the bad for the industry.
When money is abundant, every idea gets funded. When hype is high, every announcement is treated as a breakthrough. The signal-to-noise ratio drops, and it becomes harder to distinguish genuine progress from clever marketing.
In this environment, the role of human judgment becomes even more critical. Machines can process data, but they cannot evaluate competing visions. Algorithms can optimise for known objectives, but they cannot choose which objectives matter. Humans must do that.
The Guinea Pig Paradox
AI firms will themselves be the guinea pigs for the technology they are creating. As early adopters of automated business processes, their managers will have a unique insight into the interaction of human and AI at the workplace.
This is a rare advantage. Most companies will implement AI tools built by others, learning only from their own limited experience. AI firms will implement their own tools, gaining insight from the very process of creation. They will see not just how the tools work, but why they work, and where they fail.
Some of the answers enterprises are seeking about AI will emerge from the boardrooms of companies like OpenAI. This should work both for tapping AI’s potential and testing its limits. Prototypes for business management in an area of synthetic intelligence will emerge from the technology industry.
The Learning Loop
The relationship between AI creators and AI users is not one-way. As AI firms deploy their own tools, they learn what works and what doesn’t. They refine their products based on their own experience. They develop best practices that can then be shared with clients.
This creates a virtuous cycle: the more the AI firm uses its own technology, the better that technology becomes, and the more valuable it is to clients. The firm becomes both producer and consumer, creator and critic, builder and user.
The Ethical Frontier
Perhaps the most important role for humans in the AI age is ethical oversight. Machines can optimise for efficiency, but they cannot weigh competing values. They can maximise profit, but they cannot decide what level of risk is acceptable. They can process data, but they cannot determine what data should be collected in the first place.
Questions about delegation—what tasks should be fully automated, what tasks should require human oversight, what tasks should never be delegated to machines—are fundamentally human questions. They require judgment, values, and a sense of proportion that machines lack.
Conclusion: KC’s Challenge
Arvind K C has his work cut out for him. He must manage irreplaceable talent while building products that will displace others. He must navigate a field with no precedents and a constantly shifting target. He must help his company be both creator and guinea pig, producer and consumer.
All the best, KC. You’ve got your work cut out for you—AI and people.
Q&A: Unpacking the Human-Tech Challenge
Q1: What is the paradox facing chief people officers at AI firms?
They lead teams creating products that will displace workers at client enterprises. Their own employees have irreplaceable skills now, but those skills may also be affected by AI evolution. They must manage talent while building technology that transforms the very nature of work.
Q2: Why does agentic AI still require human intervention?
Even AI that can accomplish business processes without guidance needs humans to build protocols, audit systems, introduce deliberate friction for error management context, and answer ethical questions about delegation levels. The human role shifts from doing to overseeing and deciding.
Q3: What makes managing talent in AI firms uniquely challenging?
Employees’ skills are currently irreplaceable, creating enormous leverage for talent. There are no precedents for management in this rapidly evolving field. The target constantly shifts as technology advances. Investor frenzy makes it difficult to distinguish good ideas from bad.
Q4: How do AI firms benefit from being early adopters of their own technology?
As guinea pigs for their own products, AI firms gain unique insight into human-AI interaction at work. They see not just how tools work but why they work and where they fail. This creates a virtuous learning loop that improves products and generates best practices for clients.
Q5: What is the most important human role in the AI age?
Ethical oversight. Humans must decide what tasks should be fully automated, what requires oversight, and what should never be delegated to machines. These questions require judgment, values, and a sense of proportion that machines lack. The human element migrates to higher levels of abstraction.
