Pieter Van Schalkwyk
CEO at XMPRO
Sam Altman, CEO of OpenAI, recently shared compelling insights about how different generations use ChatGPT at Sequoia Capital’s AI Ascent 2025. His observations align perfectly with Harvard Business Review’s latest research on GenAI usage patterns.
Together, they reveal a transformation that business leaders cannot afford to ignore. GenAI is rapidly evolving from tools into companions and team members.
The Radical Shift in How People Use AI in 2025
Harvard Business Review’s comprehensive research confirms a dramatic transformation in how people use generative AI.
“Therapy/Companionship” now ranks as the #1 use case in 2025, climbing from second place last year. This represents a fundamental shift toward more personal, relationship-based AI interactions.
Two entirely new use cases have claimed spots in the top three: “Organizing my life” and “Finding purpose.” These highly personal applications have displaced more utilitarian tasks that dominated last year. The trend points toward AI as a partner rather than just a tool.
Consider this dramatic transformation revealed in HBR’s top 10 GenAI use cases for 2025:
Source: Harvard Business Review
The displacement of traditional AI use cases tells a compelling story. General advice, personalized learning, exploring topics, and text editing have all fallen out of the top 10. These were applications we once considered central to AI’s value proposition.
Leaders who continue to view AI only as productivity tools will miss the profound transformation taking place. The rapid rise of code generation (up from #47) and healthier living (up from #75) demonstrates just how quickly user preferences can change.
The Generational Divide in AI Interaction
Altman identified three distinct usage patterns across age groups that explain this shift. Each reveals important insights about future expectations for AI in the workplace.
“Watching how a 20-year-old uses ChatGPT compared to an average 35-year-old shows an unbelievable difference,” Altman noted at the Sequoia event.
Older professionals typically use ChatGPT as a Google replacement. They ask specific questions, get information, and move on. This transactional relationship views AI as simply a more efficient search engine.
People in their 20s and 30s approach AI as a “life advisor.” They seek guidance on decisions, recommendations for approaches, and help with planning. This relationship includes more context and continuity.
College students and younger users treat AI as an “operating system” for their lives. They integrate AI deeply into their workflows with complex prompts and sophisticated setups. They connect AI to their personal files and data sources, creating comprehensive information ecosystems.
Most tellingly, younger users “don’t really make life decisions without asking ChatGPT what they should do,” according to Altman. They share extensive context about people in their lives and past conversations. The AI effectively becomes a repository of their personal history and relationships.
From Digital Assistants to Virtual Teammates
This evolution directly impacts how organizations should approach AI implementation strategies. The HBR research reinforces what Altman highlighted: increasingly personal AI relationships will reshape workplace expectations.
Young professionals entering your workforce have already developed deep, collaborative relationships with AI systems. They don’t view AI as just answering questions or performing tasks. They see AI as an active participant in problem-solving and decision-making processes.
These expectations will fundamentally change workplace dynamics. The same people who consult AI before making personal decisions will naturally want similar AI collaboration in professional contexts. They won’t understand workplaces that limit AI to basic automation or information retrieval.
Companies building simple chatbots or basic automation will seem hopelessly outdated to this generation. HBR’s research shows users want AI systems that understand context remember previous interactions, and participate meaningfully in complex workflows.
Multi-Agent Systems: The Next Evolution
At XMPro, we recognize that the future lies in Multi-Agent Generative Systems (MAGS) rather than isolated AI tools. These systems create networks of specialized AI agents that work together with humans to address complex challenges.
Imagine teams where human experts collaborate with specialized AI agents toward clearly defined objective functions. One agent might focus on equipment monitoring, another on scheduling optimization, and a third on quality control. The human team members provide direction, judgment, and creativity while the AI agents handle data processing, pattern recognition, and routine tasks.
The critical advantage of this approach is how it aligns with the “Therapy/Companionship” trend seen in the HBR research. Younger employees, especially in industrial settings with significant skills gaps, can use these AI agents as non-judgmental coaches and guides. Just as people value AI for therapy because it’s available 24/7 and doesn’t judge, workers can consult their AI teammates for advice without fear of appearing inexperienced.
This approach is particularly valuable in industrial sectors facing severe skills shortages. New employees can learn faster with AI coaches that provide constant guidance, while experienced workers can delegate routine tasks to focus on higher-value activities. The AI agents effectively become both mentors and assistants, addressing multiple workforce challenges simultaneously.
The Urgent Need for Leadership Response
The HBR article highlights how people are using AI for increasingly personal purposes. “Therapy/Companionship” ranked #1 with users valuing its 24/7 availability, lower cost compared to human therapists, and judgment-free interaction. This shift toward relationship-based AI creates both opportunities and challenges for business leaders.
Companies face a critical decision point. The organizations that recognize and adapt to this shift will gain significant advantages over those that don’t. The response requires more than just adopting new technology.
Companies need comprehensive strategies that address:
Workplace Integration: How will AI companions fit into existing team structures? What roles will they play in meetings, projects, and daily workflows?
Knowledge Management: How will organizational knowledge transfer to and from AI systems? What safeguards will ensure appropriate information sharing?
Ethical Boundaries: What limits should exist in human-AI relationships in professional contexts? How will you balance personalization with privacy?
Skill Development: How will you help current employees adapt to collaborative AI? What training will bridge the generational divide in AI fluency?
Governance Frameworks: What policies will guide appropriate AI usage? How will you ensure responsible development and deployment?
Leaders who wait for these questions to answer themselves will find their organizations unprepared for the workforce of tomorrow. Proactive planning must begin now.
Five Practical Steps for Forward-Thinking Leaders
- Start building AI companions, not just tools Focus on systems that maintain context and continuity across interactions. The HBR research shows users are frustrated when AI doesn’t remember enough about them. Create AI implementations that learn from repeated engagements rather than handling isolated requests.
- Experiment with multi-agent architectures Begin testing how teams of specialized AI agents might address complex challenges in your organization. Look for opportunities to deploy agent groups rather than single-purpose solutions.
- Engage younger employees in AI strategy development Tap into the intuitive understanding that younger team members have about AI relationships. Their natural fluency with these systems provides valuable perspective for planning. HBR’s research shows stark differences in how generations approach AI.
- Develop clear governance for AI relationships Create frameworks that define appropriate boundaries for human-AI interactions. Establish policies that balance personalization benefits with privacy considerations. The HBR article reveals increasing user sophistication about data privacy.
- Prepare for workforce expectation shifts Recognize that new employees will expect sophisticated AI collaboration. Begin adapting recruitment, onboarding, and development programs to address this reality. The generation using AI for “Finding purpose” will bring these expectations to work.
The Future Belongs to Collaborative Human-AI Teams
Sam Altman predicts that “2025 will be a year of agents doing work,” with coding as a particularly dominant category. The HBR research confirms this trend by showing code generation has jumped from #47 to #5 in just one year. This represents a fundamental shift in how we should approach work in organizations.
The real opportunity lies not in replacing humans but in creating collaborative teams where humans and AI agents work together toward shared objectives. These hybrid teams can leverage the unique strengths of both human creativity and AI processing power to achieve results neither could reach alone.
The companies that succeed won’t just have better tools. They’ll build integrated teams that include both human and artificial intelligence working together toward common objective functions. The collaborative approach will create more value than either humans or AI could achieve working separately.
As Altman observed at the Sequoia event, large technological shifts often face significant resistance: “This is creative destruction. This is why startups win.” Established organizations must decide whether to embrace this new paradigm or struggle to catch up later.
The generation that already treats AI as a companion will soon dominate your workforce. According to HBR, they’re using AI to boost confidence, have deep meaningful conversations, and organize their lives. They won’t just expect sophisticated tools at work; they’ll expect trusted AI teammates that support their growth and development without judgment.
The question isn’t whether your company will adapt, but whether you’ll lead or follow in creating these new collaborative human-AI teams.
Pieter van Schalkwyk is the CEO of XMPro, specializing in industrial AI agent orchestration and governance. With 30+ years of experience in industrial automation, he helps organizations implement practical AI solutions that deliver measurable business outcomes.
About XMPro: We help industrial companies automate complex operational decisions. Our cognitive agents learn from your experts and keep improving, ensuring consistent operations even as your workforce changes.
Our GitHub Repo has more technical information if you are interested. You can also contact myself or Gavin Green for more information.
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