TLDR: Deon MacMillan, Chief People Officer at Pax8, asserts that artificial intelligence is not designed to replace human jobs but rather to streamline and improve inefficient processes within organizations. This perspective emphasizes AI’s potential to enhance productivity and innovation by addressing operational inefficiencies.
In a rapidly evolving business landscape where artificial intelligence is increasingly integrated into the workplace, Deon MacMillan, Chief People Officer at Pax8, offers a compelling perspective on its true purpose. MacMillan firmly states, “AI is not to replace people. It’s to replace bad process.” This viewpoint, shared in a recent interview with CRN, provides an energizing outlook amidst discussions of AI’s impact on employment.
MacMillan’s optimism, however, contrasts with some broader concerns. A widely cited 2020 article from the National Institutes of Health (NIH), titled ‘The Impact of Artificial Intelligence on Human Society,’ warns of potential harms such as job loss, social disconnection, racial bias, and widening inequality. This highlights an ethical tension in the ongoing AI conversation, balancing practitioner-level hope with policy-level concerns.
The integration of generative and agentic AI continues at a breakneck pace, raising questions about how to leverage these technologies for productivity without compromising ethical standards. MacMillan’s call to replace ‘bad process’ with intelligent systems necessitates a rigorous standard for input quality. As the adage goes, ‘bad data in means bad process out.’ From a human relations and organizational development standpoint, if biased data is used to train AI-reimagined policies and processes, the result will be biased algorithms and organizational outputs. This suggests that mere speed or efficiency does not inherently equate to ethical outcomes.
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MacMillan encourages teams to experiment and ‘ask crazy questions’ of their AI assistants, citing her personal GPT, ‘Quill,’ as an example. However, this openness to experimentation requires critical oversight. Without a conscious audit of data inputs—such as performance reviews, hiring trends, promotion rates, and customer feedback loops—AI could inadvertently amplify existing inequities that HR and Diversity, Equity, and Inclusion (DEI) teams strive to correct, particularly concerning race, gender, or ability. The framework reframes the AI conversation, emphasizing that efficiency alone is not inherently ethical.
