Agentic enterprise 2028
A blueprint for cost savings, job creation, and faster growth through agentic AI
Agentic AI isn’t just the next wave of automation—it’s the operating logic of tomorrow’s enterprise. Organizations that embrace it by 2028 will likely save costs, release products faster, and redeploy talent to higher‑value work. Learn how to build an agentic enterprise through autonomous AI.
Key takeaways about the agentic enterprise
- Agentic AI isn’t just smarter automation—it provides a strategic blueprint for enterprises to achieve cost efficiency, drive revenue growth, and unlock the full potential of their talent.
- While autonomy delivers major benefits, its complexity demands a pragmatic, coordinated evolution of strategy, technology, data, workforce, governance, and change management.
- Human roles will evolve significantly—from monitoring and feedback at early stages to orchestration and strategic oversight as agentic integration advances—demanding dynamic talent pipelines and careful work redesign.
- Enterprises that act early and approach autonomy as a phased transformation will secure lasting advantage and shape industry standards.
Autonomous AI capabilities: 2025 vs. 2028
Three macro forces are compressing the timeframe for critical decision-making related to AI: competitive pressure, regulatory scrutiny, and advancing technology. Today, sophisticated agentic AI assistants handle a variety of structured tasks. By 2028, they are projected to become autonomous partners that tackle complex, multistep problems and proactively shape decision-making.
|
Capability |
2025 |
2028 (Projected) |
|---|---|---|
|
Autonomy and decision-making |
Primarily human-in-the-loop, rule-bound choices |
Significantly more autonomous and capable of making proactive decisions; human role shifts to reviewer and monitoring agents emerge |
|
Reasoning and planning |
Can handle structured problems with short-term planning |
Strategic, real-time adaptive planning in ambiguous situations |
|
Natural language understanding |
Context-aware chat and commands |
Near-human level of understanding across nuances and multiple languages |
|
Task complexity and execution |
Automates repetitive, rule-based tasks |
Orchestrates complex, multistep workflows with dependencies based on a defined goal or outcome |
|
Multiagent systems |
Early, small-scale collaborations within structure frameworks (e.g., LangGraph) |
Widespread adoption of sophisticated multiagent systems with specialized skills, mirroring a human team |
|
Integration and adoption |
Point solutions (e.g., customer service or IT help desk); tech-heavy rollout |
Enterprise-wide applications driven by low/no-code integration capabilities |
|
Learning and adaptation |
Learns from explicit feedback |
Self-improving via reinforcement and human observation |
Architecting the autonomous AI operating system
To scale agentic AI responsibly and effectively, enterprises should evolve their entire approach, from strategy and technology to AI governance and workforce. Download the report for a deep dive into six core dimensions for increasing agentic AI autonomy, accompanied by actionable recommendations for each.
Scaling agentic AI: The autonomous AI ladder
Agentic AI capabilities span a spectrum of autonomy, from basic task automation to highly independent agents capable of complex, end-to-end processes. This progression offers opportunities to create new efficiencies, drive innovation, and transform business operations. To realize the full potential of the agentic enterprise, business leaders should proactively prepare their organizations to navigate and scale across these different levels of autonomous AI.
Explore more from our AI agents series
Dive into our ongoing series to build your understanding of AI agents and multiagent systems and get tangible recommendations on how to move forward.
Learn about how AI agents can help you rewrite the rules of automation to unlock efficiency and value.
Get a deeper look at multiagent systems are transforming organizations and industries.
Understand design principles and reference architectures underlying multiagent systems.
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Act early, scale confidently
Agentic AI isn’t a singular rollout; it’s a phased transformation, much like the shift from steam to electricity on the factory floor. Those who move first are better positioned to capture outsized gains and help define the playbook for the agentic enterprise era.
Discover more about use cases and next steps, including the six pillars of agentic enterprise architecture, in the full report.
