2026: The Year AI Moves from Faster Reports to Governed Outcomes in Planning and Funding

The adoption of AI in enterprise organizations is causing an evolution in the practice of strategic portfolio management (SPM). The changes reshaping this — lean portfolio management, shorter application delivery cycles and the rise of agentic AI — are redefining how organizations align investment with execution.

Many organizations that have brought AI into their operations have seen few tangible results to drive their businesses. In 2026, this will require organizations to apply SPM principles to their own AI investments—managing costs and understanding value. SPM, according to Jean-Louis Vignaud, senior director and head of ValueOps by Broadcom, will be elevated to a CEO-level concern, directly impacting enterprise strategy.

“As AI is being used, the delivery cycle from idea to realization is shortening, and that means the annual operating plan is becoming a thing of the past,” he said. “You cannot plan 12 months ahead. You need to be way more reactive. Because, you know, everything is way more reactive.”

Trends around portfolio management, value streams and agentic AI

Vignaud sees organizations’ operating models transitioning toward lean portfolio management and the continuous funding of value streams. “This reinforces the core ValueOps proposition and revitalizes the decade-old movement from projects to products,” he said. “I know it has been discussed for 10 years, and very few organizations manage to move from project to product. ‘Project’ is an older way of dealing with investment. It brings too much oversight, too much complexity. If you shorten the delivery cycle, if things move fast, you cannot go through the approval process for a project.” Organizations, he said, can fund nimble, fast-moving value streams, enabling them to keep pace with a rapidly changing technology landscape.

Meanwhile,  agentic AI and domain-specific intelligence are being used by more and more organizations. Agentic AI is expected to move beyond simple automation to become a true collaborator in complex decision-making, leading to what Vignaud called autonomous portfolio management.

“We do expect customers, how they adopt agentic AI, to start using AI in the context of SPM,” he said, “beyond a simple automation tool, more as a collaborator in a complex decision-making, which we know from predictive or autonomous portfolio management, we do expect to see some move in that direction.” 

While this progress on the technology side is rapid—aided by developments like large-context models—organizational adoption is expected to be slow. It hinges on building trust in AI to make high-stakes investment decisions, which will initially require significant human oversight. This future also relies on organizations building proprietary, business-specific knowledge bases and leveraging smaller, contextual AI models rather than solely relying on massive, general-purpose large language models.

Embedding genAI into Clarity, Rally

ValueOps by Broadcom’s response to these trends is Vaia, a natural language assistant in Clarity developed across two phases. Horizon One, as Vignaud called it,  focuses on embedding generative AI directly into existing products like Clarity and Rally to improve user productivity and automate routine tasks over the next 12-18 months. AI agents can help complete investment templates, identify and create Rally user stories from features, automatically generate project status reports, and help explain the underlying factors impacting project status in Rally dashboards.

Horizon Two, or Vaia Next-Gen, represents a shift to a new user experience built on a dedicated platform that leverages agentic AI. This phase is designed to transform the user’s interaction with SPM data, offering a conversational query interface, the ability to view and strategize different investment scenarios, a personalized UI, and real-time alerts and notifications. It can also be used by managers and executives

This capability to track work against strategic goals also allows for the automation of financial capitalization, and gives Vaia Next-Gen predictive capabilities. It can identify projects at risk which including the accurate tracking of OPEX and CAPEX. By making progress visible and traceable in real-time, Vaia Next-Gen moves beyond mere reporting to predictive capabilities, identifying projects at risk of slipping resources or missing deadlines. The platform is designed to be usable standalone by executives or embedded within existing Clarity and Rally environments, leveraging natural language queries to interact with and automatically update the underlying systems.

AI, then, is changing the biggest challenge in portfolio management. The problem is moving away from “Do I have the resources to do it?” to the question, “Are we investing in the right place?” By automating delivery and execution, AI shifts the focus squarely onto strategy, value measurement, and high-confidence decision-making.

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