AI Agents are Here. 7 Steps to Prepare

To capture the powerful benefits of agents, organisations must transform the ways people work, going beyond simply rolling out new technology. Protiviti helps clients create agents and adoption plans, including for Microsoft Copilot and Copilot Studio, that drive business results, focusing on people and processes with reinforcement. Here are seven important steps to follow:

1. Start with a clear use case

The most successful AI deployments begin with a clearly defined challenge for which AI agents can deliver measurable value. While every business area can realise value from agents, common starting points include:

• Customer service (chatbots, support ticket triage)
• Marketing (personalised outreach, campaign optimisation)
• Operations (inventory forecasting, supply chain monitoring)
• Finance (invoice processing, fraud detection)

Consider questions such as “Where are employees spending time on repetitive tasks?” Or, “Where could decision-making be improved with faster access to data?”

2. Build cross-functional teams

AI is not just an IT initiative - it touches nearly every part of the business. Create cross-functional teams that bring together domain experts, data scientists, developers and operations leaders. This partnership helps ensure that the AI agents implemented correspond with actual business workflows and objectives.

• IT and engineering ensure infrastructure readiness.
• Operations and business units define practical outcomes.
• Legal and compliance help navigate data privacy and ethical use.

3. Lay the right data foundation

AI agents are only as smart as the data on which they are trained. That means organisations must:

• Centralise and clean data sources.
• Address data silos between departments.
• Understand where sensitive data resides and establish clear boundaries.
• Ensure data privacy, governance and compliance.

Establishing clear data pipelines, application programming interfaces (APIs) and real-time access is crucial for AI agents that need to ingest, analyse and act on information autonomously.

4. Choose the right tools and platforms

Whether building custom agents or using off-the-shelf solutions, choose platforms that are scalable, secure and adaptable. Consider:

• Large Language Model-based agents (OpenAI, Anthropic, Mistral) for reasoning and language tasks.
• Robotic process automation + AI platforms (UiPath, Automation Anywhere) for process automation.
• Vertical AI platforms tailored to a specific industry (legal, finance, healthcare).

Prioritise systems that support “human-in-the-loop” designs, enabling oversight, auditing and collaboration.

5. Pilot, measure and iterate

Do not aim for a “big bang” deployment. Start with small pilots that allow testing, feedback gathering and refining the approach. Use well-defined metrics:

• Time saved per task
• Accuracy compared to human baselines
• Employee satisfaction and adoption rates
• Return on investment (ROI) over a three-to-six month period

Use this data to improve models, workflows and user experience before scaling.

6. Prepare people

Adopting AI agents does not mean replacing a workforce. It means augmenting human capabilities. Success requires:

• Identification of a leader to sponsor and champion.
• Clear communication about goals and impact.
• Training programs to upskill employees.
• Change management to address resistance and build trust.

Employees who understand how AI helps them, not replaces them, become the strongest advocates for adoption.

7. Prioritise ethics, security and governance

AI agents can introduce new risks such as biased decisions, hallucinated outputs and data leaks. A responsible AI adoption strategy includes:

• Transparent model documentation
• Guardrails for safe outputs (especially in generative AI)
• Human oversight for sensitive tasks
• Regular audits and updates to security protocols

Establishing an AI governance framework is no longer optional, it is essential.

AI agents represent a powerful opportunity to reimagine work, unlock new levels of efficiency, and drive new business capabilities and strategies. Organisations are adopting Microsoft’s Copilot Studio to simplify the development of agents. But success does not come from technology alone. It comes from aligning AI with real problems, engaging people and building with purpose and care.

Organisations that take a thoughtful, iterative and human-centered approach to AI adoption will lead the way in this new era. Protiviti, a Microsoft AI Cloud Solutions Partner, can help build, deploy and optimise agents that benefit business operations.

To learn more about our Microsoft consulting services, contact us.