How to build an agentic AI opportunity pipeline

Beyond a successful pilot, fully successful agentic AI programs rely on a consistent flow of impactful processes to automate. However, many organisations struggle to identify and prioritise opportunities.

Lack of collaboration between automation teams and business units often results in underutilised resources and missed enhancements. Use these steps to improve your automation opportunity pipeline:

1. Engage departments and showcase capabilities

To identify high-quality opportunities, it is essential to educate stakeholders on the capabilities of Agentic AI. Begin by conducting department-specific workshops, presenting tailored use cases that demonstrate AI’s relevance and potential impact.

Complement these sessions with executive briefings that focus on the strategic value of AI and how it can be integrated into broader business goals. Additionally, establish AI literacy programs to enhance teams’ understanding and confidence in working with AI technologies.

The primary outcome of this step is heightened awareness across the organisation, leading to more informed and higher-quality submissions for AI-driven opportunities.

2. Streamline opportunity submission

Simplifying the submission process is critical to empowering front-line employees to share automation ideas. Organisations should deploy centralised platforms such as JIRA, ServiceNow, or custom-built portals to serve as a single, accessible hub for submissions.

Design user-friendly intake forms to reduce friction and encourage participation, and offer multiple submission channels to accommodate varying preferences. Automated tracking systems should also be implemented to provide transparency and ensure submissions are monitored efficiently.

Measure the success of this step by tracking key metrics, including the volume of submissions per department, submission quality scores, and response times during the review process.

3. Define key performance indicators

Establishing clear performance indicators shapes the foundation for measuring the success and impact of AI opportunities. Focus on the following primary metrics:

• Resource Impact: Track hours or FTEs saved and cost avoidance achieved.
• Adoption: Assess departmental engagement and user adoption rates.
• Financial Outcomes: Measure ROI and compare realised benefits against projections.
• Operational Performance: Monitor improvements in process accuracy and error reduction.

4. Prioritise with stakeholder collaboration

Effective prioritisation requires collaboration between stakeholders. Establish cross-functional steering committees to foster a shared decision-making environment.

Utilise scoring matrices that evaluate opportunities based on their impact, complexity, strategic alignment, and resource requirements. While expert recommendations should guide discussions, final prioritisation should respect stakeholders’ decision authority to ensure consensus and commitment.

Maintain a transparent prioritisation process by documenting and communicating rationales for each prioritisation decision. To stay on track, convene monthly committee meetings to address operational updates and quarterly reviews to refine strategic alignment.

5. Execute strategic pilots

Pilot projects serve as strategic testing grounds for introducing Agentic AI into an organisation. Select low-risk use cases with high visibility to minimise exposure while building momentum.

For each pilot, define precise success criteria, timelines, and performance thresholds. Be prepared to adapt or roll back initiatives that do not meet predefined benchmarks.

Document the lessons learned during pilot implementations to inform scalability decisions. This structured approach enables organisations to start modestly, measure progress, and scale successful initiatives with confidence.

6. Showcase success and build momentum

Demonstrating the value of AI-driven automation is key to driving widespread organisational adoption. Host workshops celebrating automation successes to highlight impactful outcomes. Develop a library of case studies showcasing diverse, tangible results achieved through AI, and facilitate peer-to-peer learning sessions to share best practices across teams.

Foster an ‘automation champion’ network by recognising key contributors and formally celebrating achievements through recognition programs. These efforts collectively amplify the demonstrated value of Agentic AI, cultivating buy-in and inspiring broader engagement across the organisation.

7. Maintain continuous pipeline review

Growing an Agentic AI opportunity pipeline requires a sustained commitment to evaluation and refinement. Implement a regular review cycle to ensure that the pipeline aligns with evolving business objectives.

Conduct operational reviews monthly to address progress and blockers. Quarterly assessments should evaluate strategic alignment, while annual portfolio reviews ensure responsiveness to market shifts and organisational strategy changes. For urgent matters, adopt an ad-hoc approach to prioritise adjustments swiftly.

By committing to an ongoing review process, organisations can maintain a dynamic and effective AI initiative that evolves alongside their business priorities.