How agentic AI is reshaping work as we know it

When it comes to workplace technology, the only constant is change. Sometimes it unfolds gradually; at other times, it arrives with a dramatic impact.

Right now, we’re witnessing another of these transformative shifts.

Barely three years since ChatGPT took the world by storm, we’re entering a new era where employees share their workspaces with AI workers that act as assistants, coworkers and even decision-makers. This is the world of agentic AI, and it’s changing how we think about productivity, learning and collaboration.

At NTT DATA, we’re already realizing the tangible benefits of implementing our own workplace agents:

• Autonomous efficiency: An AI worker can automatically detect a recurring application crash, isolate the cause and deploy a fix — without waiting for a support ticket. These virtual agents make processes more autonomous and efficient, with less reliance on humans. And, by guiding employees through self-service tasks via natural conversation, they can reduce IT workload and call volumes by up to 70%. As a result, we have achieved cost savings of up to roughly 40%.
• AI workers acting as trainers: AI workers can analyze work patterns, recommend learning paths and provide contextual assistance to help employees acquire new skills. They can also identify potential areas of improvement for employees and coach them through the improvement journey.
  
  For instance, an L1 support engineer, who typically handles basic incident tickets, might receive AI-generated prompts suggesting ways of resolving more complex issues. With real-time assistance from the AI worker, the engineer gains confidence and gradually transitions into L2-level responsibilities.
  
  Over time, this AI-assisted upskilling balances the organization’s talent structure: it enables a broader base of mid-skilled resources by reducing the dependency on a top-heavy hierarchy. This supports pyramid correction (addressing imbalanced organizational structures) and enhances workforce agility.
  
  Through this approach, we’re continuously reskilling our workforce, leading to a more balanced distribution of skills at all levels. Furthermore, we’ve observed an increase in employee engagement of up to 30%, contributing to a better digital employee experience.

These are impressive results. However, introducing AI workers into the workplace mandates more than automation – it needs careful planning and thorough orchestration to reap the benefits.

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What is agentic AI?

In the digital workplace, we’ve all seen technologies like robotic process automation (RPA) and GenAI-powered assistants that handle tasks such as taking meeting notes and summarizing discussions.

Agentic AI goes one step further. It orchestrates multiple specialized AI assistants, works on your behalf and makes decisions in context with your authorization.

Here’s a simplified overview of AI at work:

1. Traditional and RPA agents provide rule-based outcomes

In the workplace, employee-facing agents can answer frequently asked questions based on a set of data and prompts — for example, queries about annual leave, reimbursement eligibility, transfer rules and hardware policies. Customer-facing agents can answer queries about store opening and closing times, among others.

2. Advanced agents work on more than tasks

These agents can monitor a workstation’s compliance baseline for deviations and deploy a fix to return the machine to its compliant state, should any problems arise.

3. Agentic AI systems can orchestrate multiple specialized agents to achieve business outcomes

These systems can make near-real-time decisions, and they get smarter over time. In the workplace, they can continuously monitor systems and learn from transactions and interactions, developing an understanding of the context while becoming smarter and more autonomous.

The real-world impact of agentic AI in the workplace

Unlike GenAI-powered assistants that respond to prompts, agentic AI acts independently, with limited to no human intervention. Here are some practical use cases:

Industry-specific use cases for AI workers

• Manufacturing: AI workers independently monitor, predict and adjust supply chain parameters to make production processes more efficient. They continuously learn from the operational data and make strategic decisions without waiting for manual input or following predefined rules.
• Healthcare: These agents can assess patient data, learn from new cases and recommend prescription suggestions. They adapt to complex patient data in real time and refine their models based on emerging medical research and individual case details.
• Finance: Agents can learn from emerging fraud patterns and adapt their decision-making processes without needing manual reprogramming. An agentic system can identify novel threats and proactively adjust its strategies to mitigate these risks, unlike basic automation that flags known patterns.

IT operations use cases for AI workers

• Service-desk assistance: Human service-desk agents can now ask an AI worker to list priority tickets and suggest resolutions based on historical data and real-time insights. They can also get automated ticket summaries and escalation recommendations, and the AI worker can automatically create knowledge articles and collect customer feedback, leading to an improved resolution time and fewer escalations. 
• Floor operations agent: A self-optimizing plant operations agent can act as an autonomous digital shift supervisor by continuously monitoring machine and production-line data and predicting potential failures before they occur. In addition, the agent can automatically trigger spare-parts orders based on anticipated needs and schedule maintenance crews without human intervention. By orchestrating these operational decisions end to end, it ensures smoother production, less downtime and a more resilient overall plant performance.
• Managerial assistance: IT managers can more easily track team performance metrics such as ticket-resolution times and user-satisfaction scores, with AI-driven dashboards providing real-time metrics and generating performance reports. Call audits can also be automated so that managers spend less time on quality assessments. 

5 steps to making your workplace ready for agentic AI

As you embrace agentic AI in the workplace, you unlock a new paradigm of work — one where employees focus on creativity and innovation while AI handles the execution. However, realizing the full potential of agentic AI in the workplace requires a thoughtful and strategic approach. Here’s how to get started:

1. Assess your readiness: A robust implementation begins with introspection. Before you dive in, assess and improve your IT infrastructure, focus on the accuracy and completeness of your data, define departmental and cross-business personas and clearly outline your business goals.
2. Define use cases: Identify the different areas in your business that need AI and to define exactly where agentic AI will add value. This allows you to set clear goals and objectives, allocate resources effectively and assess scalability.
3. Partner up for implementation: An experienced partner, like NTT DATA, can guide you through implementation and provide integration support. Our Workplace Smart AI Agent™ Suite offers a robust ecosystem of agentic AI tools, technologies and partners.
4. Evaluate performance and manage risk: From the outset, outline the metrics and key performance indicators that will measure the success of your agentic AI implementation. Create checkpoints for user feedback so you can make continuous improvements and identify and mitigate potential risks.
5. Focus on governance: No agentic AI strategy should be implemented without a clear system of governance that includes compliant, ethical and fair use, as well as guidelines for a responsible innovation framework.

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How it works

Our Workplace Smart AI Agent™ Suite comprises five agentic AI applications powered by a constantly growing library of over 100 agents. Together, these agents address the needs of personas across industries and use cases, orchestrating various workplace functions to improve productivity and efficiency.

Employees to interact with these agents using natural language, making adoption easy and seamless.

In just a few months, our Workplace Smart AI Agent™ Suite has helped our clients in industries including financial services, manufacturing, healthcare and the public sector to eliminate repetitive tasks, improve productivity by up to 30% and increase customer satisfaction by up to 12%.

Just imagine what we can do for you.

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This article includes contributions by Sandeep Kumar, Digital Workplace Services Strategic Advisor at NTT DATA.