IDC projects there could be more than 1.3 billion AI agents deployed by 2028, underscoring their growing role in the future of work. While interest is accelerating, most organizations remain in the middle stages of AI maturity. Many are beyond experimentation but have not yet achieved repeatable value at scale. The barriers are familiar: governance, data readiness, and process integration.
What Makes Agents Different
AI agents are distinguished by their ability to:
- Act with autonomy: Agents can plan, decide, and execute within defined parameters.
- Reason across steps: They can break down a problem, retry if the first attempt fails, and adapt based on context.
- Integrate seamlessly: Agents can connect across multiple systems and orchestrate actions that create end-to-end value.
Traditional AI models deliver predictions or recognition. Copilots support prompt-driven tasks. Agents extend further by combining reasoning, autonomy, and integration to take on complex processes that span the enterprise.
Early Use Cases with Measurable Value
Organizations are beginning to adopt agents in targeted areas where value can be measured quickly:
- Financial Services: Agents trained in policy and HR knowledge bases enable employees to find accurate answers faster, reducing reliance on manual requests.
- Insurance: Claims settlement agents extract data, detect anomalies or fraud, and route cases appropriately blending automation with human oversight.
- Manufacturing: Predictive maintenance agents use sensor data and historical patterns to forecast failures, reducing downtime and avoiding costly production delays.
These examples show the spectrum of possibilities, from straightforward information retrieval to advanced, autonomous workflows.
Measuring the real impact of agents requires more than adoption counts or usage metrics. Lantern Chief Digital Officer Kaytek Przybylski explains in Accelerating AI Value through Innovation Velocity, traditional metrics can create blind spots that hide whether AI is truly delivering business outcomes. Lantern’s Innovation Velocity Index offers leaders a way to connect investments in agents back to measurable progress in cycle time, quality, and business impact.
Practical On-Ramps to Adoption
Enterprises have three clear pathways to begin adopting AI agents:
- Buy – Agents available within Microsoft 365 Copilot provide immediate productivity benefits. Examples include Researcher, Analyst, Facilitator, Interpreter, and Project Manager agents, which streamline everyday tasks.
- Configure – Copilot Studio and Copilot Studio Lite offer low-code and no-code options for creating tailored agents. These tools support rapid prototyping while maintaining enterprise-grade security and permissions. With connectors to over 1000 systems—including ServiceNow, SAP, and Dayforce—agents can be extended into core business processes.
- Build – For enterprise-grade use cases, Azure AI Foundry enables pro-code development. With access to thousands of models and flexible deployment options, organizations can embed agents into mission-critical workflows that deliver business-specific advantages.
From Reports to Action: Aviation Safety at Unifi
Unifi Aviation, North America’s largest aviation services company, illustrates how agents can transform operations. With 25,000 employees supporting more than 900,000 flights per year, safety is a top priority.
Initial predictive analytics reduced ground safety incidents by 20%, surfacing risks tied to weather, staffing, and employee seniority. An art of the possible exercise introduced an agent directly into Microsoft Teams, delivering real-time alerts such as “High winds predicted in Phoenix today. Implement wind safety protocols?”
The agent not only issued alerts but also provided context, such as current staffing levels, and initiated tasking workflows across locations. This shift—from static dashboards to proactive, agent-driven decision-making—demonstrates how agents can embed intelligence directly into daily operations and improve both safety and efficiency.
Considerations for Leaders
Scaling agents across the enterprise requires deliberate strategy. Three priorities stand out:
- Governance: Without clear oversight, organizations risk “agent sprawl” as employees rapidly create and deploy new agents. Establishing centers of excellence, training programs, and permission frameworks is critical.
- Data and Security: Agents are only as effective as the data they connect to – check out our blog post AI Readiness Checklist for Data Leaders. Reinforcing governance and permissions ensures they operate with trusted information.
- Future of Work: Microsoft’s Work Trend Index 2025 describes Frontier Firms where all employees are managers: some will manage people; most will manage agents. Preparing to lead a mix of human and agent “direct reports” will be a defining challenge in the years ahead.
Key Takeaways
AI agents are already available through Microsoft Copilot, accessible through low-code platforms, and ready to be developed into enterprise-grade solutions that differentiate businesses. Organizations that begin exploring agents today, while investing in governance and data foundations, will be best positioned to capture value at scale.
Is your organization preparing to adopt AI Agents?
We can help prepare your users and data. Contact Lantern to get started.