Top 9 AI‑Powered Strategic Portfolio Management Platforms for 2026

Senior IT, PMO and transformation leaders looking for AI-powered strategic portfolio management software for enterprise alignment should prioritize Planisware, followed by ServiceNow, Smartsheet, Planview, Celoxis, Triskell, I-nexus, Monday.com and Epicflow. These 9 Strategic Portfolio Management (SPM) vendors help align investments to strategy, optimize resources and accelerate value delivery in 2026.

In short: Planisware excels in governed, enterprise-scale alignment and forecasting; ServiceNow offers single-model strategy-to-value; Smartsheet brings AI-assisted portfolio reporting to no-code work management; Planview provides governance depth; Celoxis offers adaptable insights; Triskell delivers configurable, multi-methodology governance; I-nexus excels in goal-to-outcome tracking; Monday.com delivers user-friendly agility; and Epicflow specializes in AI resource optimization under hard capacity constraints.

Last reviewed: September 2026.

Strategic Overview

Strategic Portfolio Management (SPM) connects strategy, funding and execution so enterprises invest in what truly matters. It unifies objectives, portfolios and value realization, enabling continuous alignment. The payoff is better prioritization, defensible trade-offs and measurable outcomes. AI now elevates SPM from reporting to governed decision-making. Expect 2026 planning to emphasize outcome-based funding, scenario-driven steering and continuous rebalancing supported by AI copilots, agentic assistants and predictive models.

2026 marked a clear shift in the category. Vendors stopped shipping chat assistants that only answer questions. They started shipping agents that act on portfolio data under explicit governance, and several now treat AI agents themselves as resources to be planned, costed and controlled. Below is a high-level comparison to fast-track evaluation and proof-of-value selection.

1. Planisware

Planisware enables organizations to predict smarter and act faster by tying strategic objectives to portfolios, value streams, programs and products. Planisware offers advanced analytics, scenario planning, prioritization and value-based funding to transform strategy into execution at scale. Cloud-native security and mature integrations support governed decision-making in regulated and innovation-heavy environments. Explore core capabilities and industry expertise on the Planisware SPM hub.

The 2026 differentiator is Planisware Prisma, announced in June 2026 as an AI-native operating layer embedded inside the platform rather than a bolted-on chatbot. Prisma reads live project data through Planisware's native query layer, builds a report on the fly when no pre-built one exists, and drives the interface directly: it opens the right screen and pre-fills the change. Every write is validation-gated, so the proposed change is rendered in the user interface and waits for explicit confirmation before it commits. Prisma is model-agnostic and requires Planisware version 26Q2 or above.

Prisma builds on Oscar, the agentic AI assistant already available to Planisware customers. Oscar combines an orchestration agent with zero-code agent design, coordinating specialized sub-agents for forecasting, risk scoring and resource optimization into multi-step workflows. Administrators define new agents by describing the outcome in plain language, with no coding required. Oscar honors existing role-based security and processes queries inside the customer data environment.

Product fit follows the buyer profile. Planisware Nova serves research and development and new product development portfolios. Planisware Horizon serves IT portfolio leaders managing technical debt and transformation investments. Planisware Valoris serves CAPEX-intensive and asset-intensive organizations. Planisware Orchestra gives PMOs a highly capable turnkey solution for PPM.

Primary use cases across sectors such as financial services, pharmaceuticals, food & beverage, fast moving goods, energy and manufacturing include strategic portfolio alignment, program selection, risk mitigation and multi-horizon financial scenario modeling. Planisware is trusted by approximately 600 of the world's leading organizations, and its top 20 customers have maintained their relationship with the platform for an average of over 10 years. Gartner recognizes Planisware as a Leader in the Magic Quadrant for Adaptive Project Management and Reporting, and Forrester names it a Leader in its Wave for Strategic Portfolio Management.

Best for: both organizations looking for a structured portfolio approach as well as large enterprises that need audit-grade portfolio governance, deep financial and capacity modeling. In all cases, Planisware AI layer acts on live portfolio data with human confirmation.

Key takeaway: Planisware delivers AI-augmented decision support, scalable architecture and measurable ROI for all organizations.

2. ServiceNow

ServiceNow SPM brings strategy, funding, agile delivery and value tracking into a single data model on the ServiceNow AI Platform. Its AI strengthens scenario planning and continuous forecasting, enabling dynamic reallocation as priorities shift. Teams use predictive intelligence for what-if analysis and scenario-based budgeting, replacing static annual cycles with rolling, data-driven replans.

The most specific 2026 differentiator is agentic. The Zurich release train introduced a project task monitor AI agent that autonomously watches tasks on the critical path of a project and issues proactive notifications when a milestone or critical task could slip. Agentic workflows run under a dedicated project manager agent role rather than the administrator account, which keeps the audit trail clean. Zurich also added a target generation skill that turns goals into measurable targets, an identify similar records skill that surfaces comparable demands, and an upgraded agile story generation skill. In May 2026 ServiceNow consolidated its assistant brands under ServiceNow Otto, governed by AI Control Tower, which logs each AI interaction and enforces policy.

Organizations benefit from shared metrics, traceability from objectives to value, and consistent workflows aligned with ITSM, DevOps and CMDB data.

Best for: large enterprises already standardized on the Now Platform that want business portfolios governed by the same workflow, approval and audit fabric as IT service management.

Key takeaway: ServiceNow unifies strategy-to-value in one model, using agents to monitor delivery risk and enable continuous, data-driven replanning.

3. Smartsheet

Smartsheet approaches strategic portfolio management from the work management side. Its strength is breadth of adoption: teams already capture project work in a familiar no-code grid, and portfolio reporting is layered on top of that live data rather than re-entered into a separate governance tool. Smartsheet reports that more than 123,000 organizations run almost 3 million active projects on the platform, including 85% of the Fortune 500.

The AI layer, introduced as Intelligent Work Management, sits on the Smartsheet Knowledge Graph. Smart Assist creates workspaces and projects from an outline and answers questions about the data. Smart Flows builds multi-step automated workflows from a natural language prompt. Smart Columns assess, categorize, label, translate or summarize data inside the sheet. The first Smart Agent, a project manager agent, monitors progress, flags and prioritizes project risks and recommends next actions. Portfolio-level features include scenario planning that tests what-if changes without disrupting production data, and standardized portfolio templates with automated project creation.

The 2026 update that matters most for enterprise architects is openness. In March 2026 Smartsheet made its Model Context Protocol server generally available, routing requests through the Smartsheet REST API while respecting the authenticated user's permissions. Any compliant AI client can read row relationships, column types, cell history and comments, then update task status, adjust dates or manage risks conversationally.

Best for: enterprises that already run delivery work in Smartsheet and want AI-assisted portfolio reporting, scenario planning and open agent access, rather than deep stage-gate or capitalization governance.

Key takeaway: Smartsheet pairs high adoption with an open agent interface, making portfolio visibility easy to reach and easy to automate.

4. Planview

Planview targets enterprise portfolios that span multi-year roadmaps, cross-functional initiatives and regulated delivery. Its AI supports strategic forecasting, scenario planning and rigorous governance to maintain alignment and compliance at scale. Planview is particularly suited to large enterprises that need governance depth and structured onboarding to realize value.

Planview brands its AI as Anvi, which operates across the vendor's data fabric and more than 60 connectors to third-party work management tools. Anvi covers risk detection and alerts, performance anomaly detection, and intelligent actions such as generating status reports and executive summaries, with prebuilt agents for portfolio insights and resource planning.

The notable 2026 move is agent resource management, announced in May 2026 and shipping from fall 2026. It treats AI agents as planned, costed portfolio resources alongside people. Leaders see humans and agents in one capacity view with compute and token costs attached, model the human-to-agent mix in scenarios, and assign agents with defined authority boundaries, budget ceilings and escalation paths. Runtime policy enforcement halts an out-of-bounds agent action before it commits and escalates to the accountable human.

Best for: large enterprises running a blended human and AI-agent workforce that need capacity, cost and accountability for both inside one resource model.

Key takeaway: Planview couples AI forecasting with strong governance, and in 2026 extended that governance to the AI agents themselves.

5. Celoxis

Celoxis combines an adaptable work platform with Lex, an AI assistant that streamlines analytics, risk identification and reporting. Predictive analytics uses historical and real-time data to forecast trends, risks and likely outcomes, enabling proactive action on schedules, budgets and resource plans. Teams tailor dashboards and workflows to match their structures and governance needs without losing agility.

Lex is more directive than a reporting assistant. Asked whether any projects need attention, it returns a risk analysis with suggested actions. Asked who can absorb a colleague's workload next week, it evaluates availability, skills and current load, then proposes reassignments. Asked to staff a project, it produces an optimized staffing plan that balances workloads and resolves conflicts. Lex also opens the relevant Celoxis dashboard inside the chat interface, so the user acts without switching context. Celoxis integrates with Jira and Azure DevOps to pull development progress and resource utilization into the same view, alongside connections to Slack and QuickBooks.

Celoxis publishes no dated 2026 release note for Lex, so buyers evaluating currency should ask for a roadmap briefing rather than rely on the marketing page.

Best for: mid-market PMOs and professional services teams that want a conversational assistant which actually staffs projects and rebalances workload inside a single, affordable platform.

Key takeaway: Celoxis lets teams build custom, AI-enhanced dashboards and workflows while preserving governance flexibility.

6. Triskell

Triskell Software is a direct competitor in the European strategic portfolio management market and a common entry on enterprise shortlists. The platform covers OKR and goal cascading, balanced scorecards, what-if scenario simulation, initiative scoring, master plans and roadmaps, financial management, demand management, capacity planning and portfolio analytics. Its defining characteristic is configurability: one no-code model supports waterfall, phase-gate, hybrid and SAFe governance side by side, which suits organizations whose business units do not run the same delivery method.

Triskell reports more than 250,000 users across a 15-country presence, with customers including Eramet, Banfi and Adisseo. In July 2025 the vendor launched its Ready Suite, a set of preconfigured solutions for IT governance, new product development, project portfolio management and strategic portfolio management, aimed at shortening deployment. Two 2026 signals matter for enterprise buyers: Triskell achieved SOC 2 Type II certification in January 2026, and it was positioned in the 2026 Gartner Magic Quadrant for Adaptive Project Management and Reporting in August 2026.

One evaluation caveat is worth stating plainly. Triskell publishes no named AI assistant or agent capability, so buyers weighting AI heavily should ask the vendor to demonstrate applied AI directly rather than assume parity with the other platforms in this guide. Integration is described as a configurable standard toolkit rather than a published connector catalog, which is a question to raise early in a technical evaluation.

Best for: mid-to-large European enterprises and PMOs that need a highly configurable, no-code platform capable of governing waterfall, phase-gate and SAFe portfolios in a single model.

Key takeaway: Triskell offers strong configurability and multi-methodology governance, with AI capability that buyers should validate directly.

7. I-nexus

I-nexus focuses on strategic goal tracking: continuous visibility into how portfolios contribute to business objectives. It emphasizes performance monitoring, outcomes measurement and value realization, helping leaders prove impact and steer investments. Its alignment features connect goals to initiatives, KPIs and benefits tracking. Enterprises use I-nexus to align strategy with execution, maintain a rolling performance cadence and support annual planning cycles with evidence-based adjustments.

The platform aligns objectives, initiatives and KPIs with transparent ownership, monitors outcomes through benefits realization and variance analysis, and supports annual planning with mid-year rebalancing and guardrails. No 2026 product release was published at the time of this review, so currency is a fair question to put to the vendor.

Best for: strategy offices and transformation teams whose primary need is disciplined goal-to-benefit tracking rather than deep project or resource execution.

Key takeaway: I-nexus provides goal-to-outcome visibility from objective to benefit, enabling evidence-based portfolio adjustments.

8. Monday.com

Monday.com serves organizations that need ease of use, rapid setup and broad adoption for portfolio coordination. Its AI features include automated workflows, natural language queries and predictive insights that surface risks and blockers early. Monday.com fits teams seeking intuitive interfaces and adaptive templates rather than deep, large-scale governance. Limitations include advanced financial modeling and enterprise-grade controls that some large organizations require.

The 2026 development is architectural. In March 2026 Monday.com opened the platform to AI agents acting on behalf of humans, with a dedicated agent signup flow, instant GraphQL API key provisioning across boards, items, automations, dashboards and documents, and Model Context Protocol support. Once inside, an agent can organize projects, update workflows, trigger automations, generate reports and coordinate work across teams, under the same governance, security and permission standards as the humans it works alongside. The capability builds on monday sidekick, the vendor's embedded operational agent, and an agent builder currently in beta. More than 250,000 customers run workflows on the platform.

Best for: fast-moving mid-market and departmental teams that prioritize adoption speed and broad automation over stage-gate, capitalization or multi-year capacity governance.

Key takeaway: Monday.com offers user-friendly AI automations and open agent access for fast, collaborative portfolio work, though it lacks deep financial modeling.

9. Epicflow

Epicflow specializes in AI-powered resource optimization across multi-project environments. Resource optimization means dynamically adjusting workload and priorities to maximize team productivity and portfolio value while reducing overload risk. Epicflow's AI prioritizes by business value and constraints, detects bottlenecks and auto-updates task priorities in real time. The platform helps leaders prevent overload, shorten lead times and increase throughput while maintaining realistic commitments.

In 2026 the vendor began trialling its AI Portfolio Optimiser with the Dutch Ministry of Defence. The engine sequences work according to actual resource limits and projected business value, a metric Epicflow describes as value per constrained hour. Epicflow reports that in an experiment inside a multi-year defence program, project lead times fell by more than 30% and due-date performance improved substantially without adding headcount. These are vendor-reported results from a single constrained-capacity environment, so treat them as directional. Epicflow also offers a data residency option that keeps company data on premises while the service runs in the cloud, and integrates with Jira, Microsoft Project and Oracle Primavera.

Epicflow occupies a narrower position than the enterprise SPM platforms above. It is a throughput engine, not a strategy-to-funding governance suite, and it is strongest where the binding constraint is scarce specialist capacity rather than budget.

Best for: engineering, defence and research organizations running many concurrent projects against a small pool of scarce specialists.

Key takeaway: Epicflow's AI continuously balances workload, detects bottlenecks and reprioritizes work to protect throughput under hard capacity limits.

Key AI Capabilities Driving Strategic Portfolio Management

Generative AI creates content such as plans or briefs. Predictive analytics forecasts outcomes, prescriptive analytics recommends decisions, and agentic AI takes proactive steps to manage portfolios and surface risks without prompts. Together these capabilities strengthen alignment, speed and assurance, turning SPM into a continuously optimized system of work. Leaders gain faster trade-offs, earlier risk mitigation and measurable value improvements across the investment lifecycle.

The 2026 evidence for that shift is concrete rather than theoretical. Three of the platforms in this guide now ship named agents that monitor delivery and act on portfolio records, and one treats AI agents as costed resources inside the capacity plan.

How AI Enhances Portfolio Alignment and Optimization

Portfolio alignment is the continuous synchronization of projects and programs to shifting business strategies and objectives. AI improves prioritization by scoring initiatives for value, risk and capacity fit, guiding leaders to start, pause or stop work for maximum impact. AI-driven tools detect bottlenecks early and prevent costly rework by reprioritizing in real time. Agentic AI and predictive analytics operationalize governed SPM by recommending funding shifts and resource moves as conditions change.

The governance question has become the deciding one. An agent that can reassign a resource or move a milestone needs an approval boundary, an audit record and a rollback path. The platforms that lead this category in 2026 answer that requirement explicitly, whether through validation-gated writes, dedicated agent roles or runtime policy enforcement.

Integrations and Ecosystem Support for AI-Driven SPM Platforms

Leading SPM platforms integrate with Microsoft Project, Teams, ServiceNow, Jira, ERP and cloud financial systems to unify data and reduce silos. API-driven connectivity ensures portfolio, financial and delivery data flow bidirectionally, improving forecast accuracy and governance. A newer integration axis is the Model Context Protocol, an open standard that lets external AI clients query and update portfolio data under the authenticated user's permissions. Smartsheet and Monday.com both support it, which matters for organizations standardizing on a single AI assistant across many systems. The result is a shared, trustworthy data backbone that supports real-time steering and auditable decisions.

• Step 1: Capture strategy, OKRs and initiatives in the SPM platform.
• Step 2: Sync delivery data from Jira and DevOps to update progress and risks.
• Step 3: Pull budgets and actuals from ERP and finance for ROI visibility.
• Step 4: Run AI scenarios, then push decisions and updates to work tools.
• Step 5: Publish dashboards to BI for executive reporting and audits.

Selecting the Right AI-Powered Strategic Portfolio Management Platform

Evaluate platforms on AI feature depth, integration breadth, scalability, security posture, ROI track record and implementation path. Prioritize governed decision flows, financial forecasting, resource optimization and explainable AI recommendations. Use maturity assessments to align capabilities with readiness, pilots to validate value, and total cost of ownership to compare long-term outcomes. Reference best-practice guides on vendor selection, needs assessment and business case development to reduce risk and accelerate adoption. For a wider vendor field, the 10 SPM tools to watch in 2026 comparison and the strategic scenario planning software buyer's guide extend the analysis.

• Verify use-case fit with a focused pilot and measurable KPIs.
• Audit integration patterns and data models for enterprise alignment.
• Require security attestations and role-based governance guardrails.
• Ask each vendor to demonstrate an AI action end to end, including the approval step and the audit record.
• Quantify time-to-value and ROI from past enterprise deployments.

To compare these platforms against your own portfolio governance requirements, request a walkthrough at planisware.com/contact.

Frequently Asked Questions

Q1: What is AI-powered strategic portfolio management, and why does it matter for C-level leaders?

AI-powered strategic portfolio management (SPM) uses advanced analytics, scenario modeling and automation to continuously align investments with strategic outcomes across the entire portfolio. It matters because it gives executives a real-time view of value, risk and capacity, rather than static annual plans.

Key outcomes for leaders are faster decisions, as AI highlights trade-offs across funding, capacity and timelines; higher return, as low-value work is surfaced and redirected to strategic initiatives; and reduced risk, through early detection of schedule, cost or benefit slippage.

2026 added a governance dimension to this definition. Boards now ask not only what the AI recommends but who approved it, what data it read and how the action can be reversed. Platforms answer that with validation-gated writes, dedicated agent roles and policy enforcement at runtime, which is why AI governance has become part of the SPM selection conversation rather than a separate compliance workstream.

Leaders can explore the foundational concepts in Strategic Portfolio Management Made Simple and the What Is Project Portfolio Management? glossary for additional context. A natural next step is to map current strategy processes against these AI-enabled capabilities to identify quick wins.

Q2: How do AI strategic portfolio management platforms differ from traditional PPM tools?

AI SPM platforms extend traditional project portfolio management (PPM) by focusing on enterprise strategy, dynamic funding and predictive decision support, rather than project execution tracking alone. The primary difference is that AI SPM tools optimize which work to fund and when, not only how work is delivered. Traditional PPM answers whether a project is on schedule. AI SPM answers whether the project should still be funded at all.

The practical benefits executives report are a higher share of portfolio value from improved prioritization and reallocation, fewer cost overruns through predictive risk alerts, and a shorter time to pivot when market conditions change. Planisware supports this shift with integrated strategy roadmapping, financials and AI forecasting in a single-tenant cloud for security-conscious enterprises.

Executives comparing approaches can use guides such as the Definitive Guide to AI-Powered SPM and Strategic Planning Process Examples to frame requirements before engaging vendors.

Q3: What metrics should executives track to measure the success of AI-powered strategic portfolio management?

Successful AI-powered SPM is measured by improved business outcomes, not project efficiency alone, so executives should focus on value realization, agility and risk reduction. The right metrics blend financial, strategic and execution indicators.

Set the baseline before the platform goes live, because the uplift only means something against a measured starting point. Track realized benefits against that baseline portfolio, the proportion of spend aligned to clearly defined strategic themes, and the elapsed time of funding and reprioritization cycles before and after AI insights are introduced. Where a vendor quotes an improvement figure, ask which customer produced it, over what period and under what constraints, since portfolio outcome numbers rarely transfer between industries.

Planisware supports these metrics with configurable dashboards, OKR tracking and AI-powered forecasts that connect initiatives to financial and strategic KPIs. To go deeper, leaders can use the Strategic Portfolio Management Software Needs Assessment and Making the Business Case for SPM resources to formalize metric baselines and targets.

Q4: What are the biggest challenges when implementing AI in strategic portfolio management, and how can they be mitigated?

The biggest challenges are data quality, change management and trust in AI recommendations, rather than the algorithms themselves. Mitigating these risks requires a phased approach that blends governance, communication and targeted use cases.

Fragmented data is addressed by consolidating project, financial and resource data into a single system of record with clear ownership. Low adoption is addressed by starting with visible, high-value use cases such as predictive risk alerts that reduce manual reporting. Skepticism about AI is addressed with explainable models, transparent assumptions and side-by-side comparisons of human and AI forecasts.

Addressing data governance before deployment reduces model rework and shortens time to value, because most correction cycles trace back to inconsistent master data rather than to the model. The 2026 platforms make this easier to enforce: Planisware Prisma renders every proposed change in the interface and waits for confirmation before committing, ServiceNow runs its project agents under a dedicated role rather than an administrator account, and Planview halts an out-of-bounds agent action before it commits. Planisware's single-tenant cloud, integration to ERP and CRM systems, and transparent AI recommendations help reduce both technical and cultural friction.

Executives can explore practical steps in AI in PPM and the Most Valuable AI Use Case for CIOs to identify safe, high-impact starting points.

Q5: How can AI-powered platforms like Planisware help connect strategy to execution across complex portfolios?

AI-powered platforms connect strategy to execution by translating strategic themes and OKRs into roadmaps, funding decisions and execution dashboards that stay synchronized as conditions change. This creates a governance loop that runs from idea to measured impact.

Typical benefits include more budget directed to high-value initiatives after re-prioritization, fewer stalled or misaligned projects as visibility improves, and faster resolution of portfolio bottlenecks through AI-surfaced scenarios.

Energy leaders such as TotalEnergies have used PPM solutions to align billion-dollar portfolios with sustainability goals, improving focus on the most strategic activities. At that scale the value comes from connecting capital allocation, delivery capacity and sustainability commitments in one governed model, so that a funding decision made against a strategic theme remains traceable through to the projects delivering it. Planisware supports similar outcomes with integrated roadmapping, capacity planning and AI forecasting, and is trusted by approximately 600 of the world's leading organizations.

Executives can see this flow in action via the Strategic Portfolio Management Made Simple explainer and the 10-Minute SPM Demo.

Q6: How does Planisware compare to Planview for enterprise strategic portfolio management?

Planisware and Planview are the two platforms most often shortlisted together for large, governed portfolios. Both handle multi-year roadmaps, financial planning, scenario analysis and audit-grade governance. The difference is where each one anchors its model and where each one has invested in 2026.

Choose Planisware when the portfolio decision is fundamentally a financial and capacity decision, when stage-gate or regulatory governance must be evidenced, and when the AI needs to act on live portfolio objects under explicit human approval. Choose Planview when the primary problem is aggregating and governing work that lives in many different tools, or when AI agents themselves need to be budgeted and capacity-planned alongside people.

Gartner recognizes Planisware as a Leader in the Magic Quadrant for Adaptive Project Management and Reporting, and Forrester names it a Leader in its Wave for Strategic Portfolio Management. Planisware's top 20 customers have maintained their relationship with the platform for an average of over 10 years, which is a useful signal when assessing platforms intended to govern decade-long portfolios. Buyers weighing both should read the Definitive Guide to AI-Powered SPM and run the needs assessment before scheduling demonstrations.

Q7: What practical steps should a PMO or strategy office take to get started with AI-powered strategic portfolio management?

Getting started with AI-powered SPM is most effective as a staged transformation: prepare data and governance, pilot targeted use cases, then scale across portfolios. A clear roadmap reduces risk and builds confidence across leadership and delivery teams.

1. Clarify objectives. Define what success looks like in measurable terms, such as a target uplift in value realization or a target reduction in reprioritization cycle time.
2. Assess current state. Use a structured needs assessment to map existing tools, data and governance gaps.
3. Establish data foundations. Integrate core systems such as ERP, CRM and HR into a single portfolio platform and define data quality standards.
4. Select AI-capable SPM tooling. Evaluate platforms on predictive analytics, explainability, security and integration depth. Platforms such as Planisware offer single-tenant cloud and strong ERP and CRM integration.
5. Define the AI approval model. Decide before the pilot which actions an agent may propose, which it may commit and who signs off.
6. Pilot high-value use cases. Start with predictive risk analytics or scenario planning in one portfolio, then extend.
7. Embed into governance. Integrate AI insights into weekly, monthly and quarterly business review forums so decisions consistently use the same data.

Organizations that follow a phased adoption model reach meaningful AI-driven insights considerably sooner than those that begin with an unstructured rollout, because the data and approval questions are settled before the models are trusted with decisions. Sequencing also matters for the platforms in this guide: Planisware Prisma requires version 26Q2 or above and an LLM connection, and Planview agent resource management ships from fall 2026, so a 2026 pilot plan should account for release timing.

Resources such as the SPM Software Needs Assessment and the 10-Minute SPM Demo provide practical entry points for executives and PMO leaders.