Download the full 2026 Program and Project Management Trends Report here.

This free trends report outlines industry perspectives and expert advice from our team of consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the program and project management space, connect with our team today.

Key Program and Project Management Trends

In 2026, leading PMOs will move beyond reporting to serve as enterprise enablement engines. They will connect strategy to execution, build readiness into delivery from the start, and ensure governance keeps pace with AI and agent deployments. Just as important, they will treat benefits realization as a core discipline, with clear ownership, defined baselines, and early indicators that show whether value is actually being created.  

Clarkston’s program and project management consultants have highlighted the top trends that businesses should consider and keep top-of-mind throughout the year:

1. Governance and Risk Management for Agentic AI
2. Scaling Native AI Delivery Across Functional Operations
3. Value realization as the main KPI for PMOs
4. PMOs Shift to Persistent Product Teams
5. From Project-Based Change Management to Sustained Enterprise Change Capability

Trend 1:

Governance and Risk Management for Agentic AI

Agentic AI is the first wave of automation that behaves less like a tool and more like a junior operator planning steps, calling systems, and completing multi-stage work. This shift – moving from people- and technology-integrated workflows to agentic AI – is happening fast, and it comes with a hard reality check.  

Gartner expects more than 40% of agentic AI projects to be canceled by the end of 2027 when teams fail to demonstrate clear value or build the right risk controls. At the same time, however, adoption will keep accelerating. Reuters reporting on Gartner notes that agentic AI is expected to autonomously handle 15% of daily business decisions by 2028 and be embedded in 33% of enterprise software by 2028. In other words, many organizations will continue moving forward even while a large share struggle to scale responsibly. 

For PTM and change leaders, the implication is clear: agent rollout isn’t just an IT release but rather an operating model change. Before agents touch regulated or revenue-impacting processes, such as pricing claims and returns, trade settlement, or quality events, programs must establish human-in-the-loop decision rights, defined ownership (RACI) for exceptions, audit trails, and production monitoring. If you wait until after deployment to add guardrails, you’ll either throttle the agent into irrelevance or accept unmanaged risk. The risk isn’t just model accuracy. It extends to process accountability: who approved an action, which data was used, what exceptions occurred, and how the organization detected and corrected failure. 

Business reality reinforces why governance has to lead. Benchmarks cited in Business Insider show agent performance can be under 25% success on the first attempt and only around 40% even after eight tries. That gap between a cool demo and a trusted operator is the governance workstream. The winners will treat agents like a new workforce class with training through prompt and workflow design, supervision through controls and monitoring, and performance management through value and quality KPIs. Those that treat agents as simple plug-ins will quickly discover that the real complexity of the business lives in the exceptions. 

Trend 2:

Scaling Native AI Delivery Across Functional Operations

The AI conversation is shifting from which use cases to pursue to a deeper question: what changes when AI becomes embedded in the way work actually gets done? 

That shift is why AI-native delivery (AI being embedded in the entire project life cycle) is a program and change management issue, not a technology one. Gartner’s forecast that at least 30% of GenAI initiatives will be abandoned after proof of concept by the end of 2025 is the clearest warning that scaling fails when organizations don’t address the basics data readiness risk controls and measurable value. 

Gartner also reports that 61% of organizations are evolving or rethinking their data and analytics operating model because of AI. This signals that the constraint has moved from model availability to enterprise readiness. AI programs will succeed or stall based on whether teams can standardize processes, clarify decision rights, and build practical adoption routines that reflect how people actually work. That includes role-based training, adjustments to job design, and policy updates that remove ambiguity. 

Workforce behavior shows how quickly the ground is shifting. Financial Times reporting indicates that 48% of workers in a large survey now use AI every day, up from 31% the prior year. Adoption is moving faster than most formal enablement and governance efforts. When that gap widens, shadow AI becomes inevitable and outcomes grow inconsistent, which is exactly the risk transformation leaders are expected to manage.

Continue reading by downloading the full report below.

Download the Full 2026 Program and Project Management Trends Report Here