My perspective on how AI agents, human leadership, and emerging AI capabilities could reshape the future enterprise.
AI is evolving beyond traditional assistants. Agentic AI is beginning to execute tasks, coordinate workflows, and support business decisions across IT, finance, HR, sales, marketing, and operations.
Looking at today's developments, I envision a future where human employees and AI agents could operate as two interconnected workforces, with distinct identities, responsibilities, permissions, and governance boundaries.
Microsoft's 2026 Work Trend Index highlights an emerging shift in which AI agents take on more execution while people increasingly direct work, evaluate results, and remain accountable for outcomes. This reinforces some of the trends shaping my perspective on the enterprise of 2035.
But this raises a fundamental question:
If AI agents increasingly perform the work through which today's professionals developed their expertise, how will the next generation gain the experience and judgment needed to lead enterprises?
The potential evolution toward Artificial General Intelligence (AGI) adds another dimension. Its timeline, maturity, capabilities, and enterprise implications remain uncertain. More capable AI systems could reshape this operating model in ways we cannot yet anticipate.
The following illustration explores ten possibilities for how the enterprise workforce might evolve by 2035.
The Future Enterprise: Humans and AI Agents — An illustrative vision of a human-led, agent-enabled organization.
Ten Possibilities for the Future Enterprise
Two workforces, one organization: Humans and AI agents may work together with distinct roles and responsibilities.
Outcome-driven work: Organizations could increasingly organize work around outcomes rather than traditional job structures.
Digital agent identities: AI agents may require identities, access permissions, ownership, and audit histories.
Human leadership: People remain responsible for strategic direction, judgment, ethics, and accountability.
Agent-to-agent collaboration: Specialized agents could coordinate activities across business functions.
Changing workforce structures: Greater automation may reshape staffing needs and productivity expectations.
New career pathways: Structured learning, mentoring, and supervised experience may become essential for developing future leaders.
Evidence-driven performance: AI-generated insights may inform evaluations, but employees must retain transparency and opportunities to challenge decisions.
Governance and resilience: Enterprises will need clear policies, oversight, and the ability to intervene when autonomous systems fail.
An uncertain future: More capable AI, potentially including AGI, could reshape these possibilities in ways we cannot yet predict.
Who Will Lead the AI Workforce?
My view is that future enterprise leaders will need to combine human judgment, business understanding, and the ability to direct and challenge intelligent systems.
Leadership cannot be reduced to supervising AI-generated dashboards. It requires understanding how work gets done, making decisions under uncertainty, developing people, and taking responsibility for outcomes.
As AI takes on more execution, enterprises must deliberately preserve opportunities for employees to develop foundational expertise, critical thinking, and independent judgment rather than assuming those capabilities will emerge through AI supervision alone.
That also raises an unresolved accountability question: when an AI agent makes a harmful decision or takes an incorrect action, who owns the consequences?
I explored the operational ownership dimension in my earlier article, Who Owns an AI Agent After It Goes Live?.
What Should Enterprises Consider Today?
For enterprise leaders considering this transition, three priorities stand out today:
- Establish agent accountability: Identify deployed agents, their owners, permissions, and governance boundaries.
- Preserve career development: Ensure early-career professionals continue gaining practical experience through supervised work and mentoring.
- Design for human oversight: Build transparency, intervention mechanisms, and operational resilience into agent-enabled processes.
These foundations matter regardless of how quickly AI capabilities advance.
The real challenge may not be how much work AI can automate, but whether we can continue developing leaders capable of understanding, challenging, and governing increasingly autonomous enterprises.
References and Further Reading
- Microsoft — 2026 Work Trend Index: Agents, Human Agency, and the Opportunity for Every Organization — Research on how AI agents are reshaping work, human leadership, organizational structures, and accountability.
- Microsoft — Three New Patterns of Work — How AI is changing organizational workflows.
- Anthropic — Economic Index — Research into AI use across economic activities.
- NIST — AI Risk Management Framework — Identifying and managing AI-related risks.
- European Commission — AI Act — Regulatory requirements and risk-based AI governance.