Planview and Highspot have unveiled new agentic AI capabilities aimed at reshaping enterprise resource management and go-to-market (GTM) execution. The announcements highlight a broader shift toward managing AI agents as operational resources alongside human teams across portfolios, marketing, and revenue functions.

Enterprise software is entering an “agentic” phase, where artificial intelligence systems are no longer just tools but active participants in workflows. Two new announcements from Planview and Highspot underscore how quickly this shift is redefining both operational management and revenue execution.

Planview’s introduction of Agent Resource Management extends traditional portfolio and resource planning into a new domain: managing AI agents as first-class contributors to enterprise work. Historically, Strategic Portfolio Management (SPM) platforms have focused on allocating human capacity across projects. Planview is now expanding that model to include AI agents—tracking their cost, performance, and accountability alongside human resources.

The rationale is straightforward. As organizations deploy more AI agents to automate tasks, they need visibility into how those agents are used, what they cost, and whether they deliver measurable outcomes. Planview’s system provides a unified view of both human and AI resources, allowing leaders to plan, assign, and govern work across a blended workforce.

This capability arrives at a pivotal moment. According to Gartner, 40% of enterprise applications are expected to include task-specific AI agents by 2026, marking a dramatic increase in adoption. Meanwhile, Deloitte reports that more than half of CFOs are prioritizing AI agent integration, signaling growing executive focus on operationalizing AI.

Planview’s approach emphasizes governance as much as automation. The platform introduces policy enforcement, audit trails, and escalation mechanisms to ensure that AI agents operate within defined boundaries. This is critical as enterprises move from experimentation to production-scale AI deployments, where accountability becomes a central concern.

The platform also introduces scenario modeling that allows organizations to simulate different mixes of human and AI resources before committing to execution. This capability reflects a broader trend toward predictive planning, where enterprises use data and analytics to optimize workforce allocation in real time.

In parallel, Planview is launching purpose-built AI agents for portfolio delivery. These include a project management agent that generates updates and identifies blockers, a backlog agent that ensures readiness of tasks, and forecasting agents that predict delivery risks. Unlike generic AI tools, these agents are designed for specific enterprise workflows and are governed within the same system as human resources.

While Planview focuses on operational planning, Highspot is targeting a different layer of the enterprise stack: revenue execution. Its new GTM Agent aims to bridge the gap between strategy and execution in sales and marketing teams.

This gap is well documented. Organizations often invest heavily in content, training, and analytics, but struggle to translate those investments into consistent deal outcomes. Highspot’s GTM Agent addresses this by connecting signals across CRM activity, buyer engagement, content usage, and training data.

The result is a unified system that provides role-specific guidance to marketing, enablement, and revenue operations teams. Instead of relying on static reports, teams receive real-time recommendations on what actions to take to improve deal performance.

The GTM Agent builds on Highspot’s existing Deal Agent, extending its capabilities beyond individual deals to a broader, cross-functional view of revenue performance. This allows organizations to identify patterns across deals, scale successful strategies, and address performance gaps more quickly.

Integration is a key differentiator. Highspot’s platform connects with tools from Microsoft, OpenAI, and Anthropic, enabling AI agents to operate within existing workflows. This reflects a broader trend toward embedding AI into the “flow of work,” rather than requiring users to switch between systems.

The company is also introducing a GTM Maturity Model, providing a framework for organizations to assess and improve their revenue operations. This aligns with the growing emphasis on continuous optimization, where AI systems not only execute tasks but also identify opportunities for improvement.

From a market perspective, these announcements highlight the convergence of several trends: agentic AI, real-time analytics, and integrated enterprise platforms. Vendors are moving away from standalone tools toward systems that orchestrate workflows, data, and decision-making across the organization.

This shift has significant implications for marketing and MarTech teams. As AI agents become embedded in both operational and revenue processes, the ability to coordinate across systems becomes a competitive advantage. Platforms that can unify data, automate execution, and provide actionable insights are likely to play a central role in enterprise technology stacks.

However, the transition also introduces new challenges. Managing a blended workforce requires new governance models, cost structures, and performance metrics. Organizations must determine not only how to deploy AI agents, but also how to measure their impact and ensure accountability.

The competitive landscape is evolving rapidly. Established enterprise platforms such as Salesforce and Adobe are also investing in AI-driven automation and analytics, while emerging vendors are building agent-first architectures from the ground up.

Planview and Highspot’s latest releases illustrate how different segments of the enterprise software market are adapting to this new reality. One focuses on managing resources across portfolios, the other on optimizing revenue execution—but both are built on the same foundation: AI agents as active participants in business processes.

As enterprises continue to scale their AI initiatives, the ability to manage, govern, and optimize these agents will become increasingly important. The shift from tools to agents is not just a technological change—it represents a new operating model for how work gets done.

Market Landscape

The rise of agentic AI is transforming enterprise software across multiple domains, from portfolio management to sales enablement. Organizations are adopting platforms that integrate AI agents into workflows, enabling real-time decision-making and continuous optimization.

This evolution is driving demand for systems that provide visibility, governance, and scalability, as enterprises seek to manage increasingly complex, AI-driven operations.

Top Insights

• Planview introduces agent resource management, enabling enterprises to plan, track, and govern AI agents alongside human resources, providing full visibility into costs, performance, and accountability.
• Highspot’s GTM Agent connects signals across sales, marketing, and enablement, turning data into real-time, role-specific actions that improve deal execution and revenue performance.
• Both platforms reflect the rise of agentic AI, where autonomous systems actively participate in workflows rather than serving as passive tools, reshaping enterprise operating models.
• Integration with major ecosystems like Microsoft and OpenAI highlights the importance of embedding AI into existing workflows, reducing friction and improving adoption.
• The shift toward blended human-AI workforces introduces new challenges in governance, cost management, and performance measurement, requiring advanced platform capabilities.

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