15 Best AI Sales Forecasting Tools in 2026, Compared by Accuracy, Price, and Fit

AI sales forecasting tools are getting more attention, but forecasting is still hard. Gartner says only 7% of sales teams achieve forecast accuracy of 90% or more, and 69% of sales operations leaders say forecasting is harder than it was three years ago. That helps explain why so many revenue teams are rethinking the systems they use to call the quarter.

The challenge now is not whether to use AI. It is choosing the right kind of forecasting tool. Some platforms are built around pipeline visibility and activity data. Others are designed to work from live signals, move faster, and fit more naturally into how sales teams already operate.

In this guide we’ll cover the 15 AI sales forecasting tools that matter in 2026, compared on what they do, what they cost, what users actually say, and which teams they fit best.

Here's what you'll find:

• What AI sales forecasting software?
• How AI sales forecasting tools work?
• Best AI sales forecasting tools: Our picks
• Top 15 AI sales forecasting tools: Complete Review
• How to choose the right AI sales forecasting tool for your team?

What is AI sales forecasting software?

AI sales forecasting software is a category of revenue tools that analyze CRM data, sales activity, and conversation signals to predict future revenue outcomes. It sits one layer above traditional CRM reporting, turning pipeline snapshots into probability-weighted forecasts that account for deal health, buyer engagement, and historical win patterns.

In 2026, this category breaks into these three groups:

- Pipeline forecasting tools analyze your existing pipeline and predict which deals will close. Clari, MaxIQ, BoostUp, Aviso, and Forecastio sit here.

Input: CRM data plus activity signals. Output: a forecast number.

- Revenue intelligence platforms do pipeline forecasting plus conversation intelligence, deal inspection, and post-sales signals. MaxIQ, Gong Forecast, and Outreach Commit sit here. 

Input: CRM plus calls plus emails plus product usage. Output: forecast plus the context behind it.CRM-

- Native forecasting is built into Salesforce, HubSpot, and similar platforms. Lower cost, lower depth, faster to deploy. It is best for teams under 20 reps with clean CRM data.

The right category depends on what's breaking. If your forecast is wrong because reps don't update close dates, you need deal inspection. If it's wrong because no one knows what customers actually said on calls, you need conversation intelligence. If it's wrong because you don't have enough data, no AI tool will fix it.

How AI sales forecasting tools work?

Four things happen under the hood.

1. Data ingestion.
   The tool pulls from your CRM (deals, stages, close dates, amounts), your calendar and email (activity capture), your call recordings (conversation intelligence), and optionally product usage or billing data. The quality of the forecast depends on the quality of the input. Stale CRM data produces stale forecasts regardless of model sophistication.

2. Signal analysis.
   The AI evaluates patterns across the ingested data. Common signals include champion engagement frequency, stakeholder multi-threading, stage velocity, sentiment shifts in calls, and gaps between what reps commit and what the data shows.

3. Prediction.
   The model assigns probabilities to each deal based on historical patterns from won and lost deals. Per Gartner's sales forecasting process guide, companies with disciplined CRM hygiene see AI accuracy improvements of 15–25% over weighted pipeline methods. Companies with messy data see the same problems reflected back with higher confidence.

4. Roll-up and scenario modeling.
   Individual deal predictions roll up to rep, team, and company-level forecasts. Strong platforms support scenario modeling (best case, commit, worst case) and let RevOps adjust assumptions by segment, geography, or product line.

The platforms covered in this guide do all four, with different strengths at each stage.

Best AI sales forecasting tools: Our picks

Top 15 AI sales forecasting tools: Complete Review

1. MaxIQ

AI-native Revenue Intelligence Platform that unifies pipeline, forecasting, conversations, and post-sales.

MaxIQ is the first AI-native Revenue Intelligence Platform built for B2B SaaS revenue teams. It helps companies improve forecast accuracy, inspect pipeline risk, capture insights from customer conversations, and connect pre-sales and post-sales execution. 

By combining CRM data, meeting activity, and revenue signals, the platform gives teams a clearer view of deal health, customer risk, retention, and expansion opportunities.

Core features:

1. ForecastIQ: AI forecasting built on signals rather than stages, with customizable roll-ups for any GTM motion.
2. InspectIQ: Pipeline visibility, deal scoring, and gap detection that flag risks before they hit the forecast.
3. EchoIQ: Conversation intelligence built on revenue context, auto-updating CRM and syncing call signals to deals.
4. SuccessIQ: Post-sales intelligence covering onboarding, adoption, and renewal signals that feed back into the forecast.
5. Fast deployment: Salesforce connection in 5 minutes, pipeline views in 10, forecasting workflows live in 3 minutes.

Used by: Snowflake, Commvault, VAST Data. Customers report 15% forecast accuracy improvement and adoption above 95%.

Pricing: Usage-based. No platform fee. Free for early-stage startups via the MaxIQ Startup Program.

Trial: Book a demo.

2. Clari

Enterprise revenue intelligence and forecasting platform for large sales organizations.

Clari is the category leader in pipeline visibility and revenue governance. The platform ingests CRM data, activity signals, and conversation intelligence (via the Wingman acquisition, now Copilot) to give CROs a real-time view of pipeline without chasing reps for updates. The 2025 Salesloft merger added sales engagement to the stack.

Core features:

1. Predictive forecasting: Multi-dimensional roll-ups with commit categories (best case, commit, upside, pipeline).
2. Pipeline inspection: Real-time visibility into deal-level changes, territory coverage, and gap-to-target.
3. Scenario forecasting: Model multiple scenarios and pressure-test predictions against historical patterns.
4. Segment forecasting: Break down forecasts by geography, vertical, product, or any custom segment.
5. Copilot CI: Conversation intelligence module (formerly Wingman) with call recording and deal intelligence.

Trade-off: Implementation runs 8–16 weeks with professional services fees of $15K–$75K. Full-stack deployments (Core + Copilot + Groove) push per-user cost above $400/month.

Pricing: ~$100–$125/user/month for Core. Full stack $200–$400+/user/month. Quote-based.

Trial: None.

3. Gong Forecast

AI forecasting add-on to Gong's conversation intelligence platform.

Gong Forecast ties conversation signals to forecast predictions, using the call data Gong captures to assess deal health, sentiment, and next-step likelihood. It works best for teams already running Gong Foundations, since Forecast cannot be purchased standalone.

Core features:

1. Conversation-driven forecasting: Uses call recordings and buyer sentiment to score deal health.
2. Deal boards: Consolidates forecast data and underlying conversations in one view.
3. Pipeline comparisons: Flags mismatches between rep confidence and buyer engagement data.
4. Likelihood scoring: AI assigns close probabilities based on conversation and activity patterns.
5. Deal workflows: Routes risks and advancement actions through a unified Gong interface.

Trade-off: Third-party analyst ratings for the forecasting capability sit around 4 out of 10. Roughly 40% of mid-market Gong customers stack Clari on top for forecasting they can commit numbers against.

Pricing: ~$700/user/year add-on. Requires Gong Foundations ($1,300–$1,600/user/year).

Trial: None.

4. Aviso

AI-powered revenue intelligence platform for enterprise teams prioritizing forecast accuracy.

Aviso combines human input with predictive analytics to generate forecasts the vendor claims hit 98% accuracy. The platform automatically consolidates forecasts for each rep, category, and team, presenting best-case scenarios, most likely numbers, and pacing against target in real time.

Core features:

1. WinScore insights: AI scoring that explains why a deal will or will not close, with transparent reasoning behind each prediction.
2. Deal and pipeline inspection: 360-degree dashboards covering pipeline health, forecasting, and target fulfillment across the full sales organization.
3. Multi-hierarchy rollups: Consolidates forecasts from rep to category to region automatically, with real-time refresh across all reports.
4. MIKI agentic AI: Autonomous workflows that research accounts, summarize calls, and update CRM entries without rep involvement.
5. Consumption forecasting: Built-in support for usage-based pricing businesses, which most forecasting platforms don't handle natively.

Trade-off: G2 reviews flag Salesforce sync lag and slow dashboard performance under large data volumes. Implementation is enterprise-scale, with $5K–$10K onboarding for SMB and $50K–$100K for large enterprises.

Pricing: Starts around $50/user/month. Enterprise deployments commonly quoted from $50,000/year. Quote-based.

Trial: 90-day free trial available on request.

5. Terret AI (Previously BoostUp)

Revenue Operations and Intelligence platform combining forecasting, pipeline management, and deal intelligence.

BoostUp acts as a Revenue Command Center for CROs and RevOps leaders. The platform unifies CRM data with engagement and product-usage signals to deliver pipeline analytics, deal and account risk scoring, and machine-driven forecasting alongside a revenue BI layer.

Core features:

1. Multi-dimensional forecasting: Flexible data model supporting subscription, usage-based, PLG, renewal, and expansion revenue in one view.
2. Machine Forecast: AI-generated revenue projections that predict wins, losses, and slips based on historical trends and engagement data.
3. BoostBot: AI agent that surfaces deal-level alerts, flags forecast risks, and drafts follow-up emails and scorecard entries.
4. Deal inspection: Engagement risk scoring at the deal level, surfacing disengaged contacts and stalled pipelines before managers spot them.
5. Conversation intelligence: Native CI with tight integrations to Gong, Chorus, Salesforce, Outreach, and Salesloft.

Used by: Cloudflare, Teradata, Udemy, Workato, MongoDB. G2 reviewers consistently highlight adoption quality, with one noting it as the only tool AEs rolled out to enthusiastically.

Pricing: Starts at ~$79/user/month. Typical deployments run $30,000–$80,000/year. Quote-based beyond base tier.

Trial: Free trial available.

6. Salesforce Einstein

Native AI forecasting built into Sales Cloud for Salesforce-invested organizations.

Salesforce Einstein layers predictive AI onto Sales Cloud, analyzing historical opportunity data to predict close probabilities and generate forecast numbers. For Salesforce-native companies, it's the path of least resistance: no integration, no separate vendor, no new data pipeline.

Core features:

1. Einstein Forecasting: Predictive models that generate bottom-up forecasts by aggregating individual deal predictions across the org.
2. Opportunity scoring: AI assigns close probability scores from 1–99 based on historical win and loss patterns.
3. Explanatory insights: Surfaces the top factors driving each forecast prediction, supporting audit and pressure-testing.
4. Collaborative forecasting: Roll-up workflows from rep to manager to VP inside the native Salesforce interface.
5. Segment and territory forecasting: Filter forecasts by product family, territory, opportunity splits, and custom segments.

Trade-off: Accuracy depends entirely on Salesforce data quality. Gartner Peer Insights reviews flag that Einstein needs years of clean historical data to produce reliable scores, and implementation often takes several months with consultants. Teams with messy CRM data see limited accuracy improvement.

Pricing: $75/user/month on top of Sales Cloud Enterprise ($165/user/month). Included in Unlimited and Einstein 1 editions.

Trial: 30 days free through Salesforce.

7. HubSpot Sales Hub AI

AI-enhanced forecasting built into HubSpot CRM for mid-market teams already in the HubSpot ecosystem.

HubSpot's forecasting capability lives inside Sales Hub Professional and Enterprise tiers. The platform uses pipeline velocity, deal value, and rep performance to calculate forecast projections, with full integration into the HubSpot CRM so no separate connector or data pipeline is required.

Core features:

1. Automated forecasting: Generates forecasts based on deal stage and AI-assigned close probability, updated continuously from CRM activity.
2. Customizable forecast categories: Filter forecasts by deal type, region, time frame, or individual rep to match internal reporting structures.
3. Pipeline velocity tracking: Measures how deals move through stages over time, surfacing slowdowns before they affect the forecast.
4. Historical snapshots: Compares current forecast to past periods, helping managers spot trends and improve prediction discipline.
5. Breeze AI: HubSpot's embedded AI layer, included at no extra cost, covering lead scoring, content generation, and email optimization.

Trade-off: Predictive scoring is gated behind the Enterprise tier, with a 7-seat minimum and a $3,500 onboarding fee. Teams under 7 reps or on the Professional tier lose access to the strongest forecasting features.

Pricing: Sales Hub Enterprise starts at $150/user/month, minimum 7 seats ($4,300/month starting commitment).

Trial: Free CRM tier available; Enterprise forecasting features require demo.

8. Outreach Commit

AI forecasting module tied to Outreach's sales engagement and execution platform.

Outreach Commit uses the sales execution data captured by the Outreach platform (emails, calls, meetings, sequences) to feed forecast predictions. The value is in connecting engagement signals directly to deal outcomes, which most standalone forecasting tools cannot do natively.

Core features:

1. Explainable AI: Shows reps and managers why a deal is flagged, which Outreach research identifies as a top driver of forecast trust and adoption.
2. Engagement-informed forecasting: Pulls signal data from sequences, email opens, call outcomes, and meeting completions directly into predictions.
3. Deal Management: Predictive forecasting module that Outreach reports improves forecast accuracy by up to 25% over manual methods.
4. Kaia conversation intelligence: Records, transcribes, and analyzes calls in real time, surfacing competitor mentions and commitments.
5. Unified execution layer: Forecast predictions sit in the same platform reps use for sequencing, reducing context-switching.

Trade-off: Buying Outreach solely for forecasting rarely makes sense. The module's value compounds when the team is already running sequences and deal management on the platform.

Pricing: Roughly $100–$200/user/month depending on package. Quote-based.

Trial: None.

9. People.ai (Now Backstory)

Activity capture and intelligence platform that structures the data other forecasting tools rely on.

People.ai is not a forecasting tool in the traditional sense. It captures and structures sales activity data (emails, meetings, calls, engagement signals) and maps it to accounts and opportunities, then feeds that structured data into forecasting, CRM, or revenue intelligence platforms. For teams whose biggest forecast problem is data quality, People.ai addresses the input layer directly.

Core features:

1. Activity capture: Automatically logs emails, meetings, and calls into Salesforce without rep involvement.
2. Account and opportunity mapping: Connects every activity to the right deal and account automatically, closing CRM data gaps.
3. Relationship intelligence: Surfaces stakeholder maps, champion changes, and engagement patterns across the buying committee.
4. Forecast enrichment: Feeds activity signals into Clari, Salesforce, or other forecasting platforms for sharper predictions.
5. AI summaries: Generates account and deal summaries from captured activity, reducing manager prep time.

Trade-off: People.ai is typically deployed alongside a forecasting platform, not instead of one. Standalone ROI is hard to measure, which is why most buyers layer it under Clari or Salesforce rather than using it as the primary forecast tool.

Pricing: Typically $30,000–$80,000/year per Vendr benchmark data. Quote-based.

Trial: None.

10. InsightSquared (Mediafly)

Revenue intelligence and RevOps analytics platform for mid-market teams needing forecasting with strong BI.

Part of Mediafly since 2021, InsightSquared combines AI-powered forecasting with deep analytics dashboards and activity capture. It's strongest for mid-market orgs that want RevOps reporting rigor without enterprise pricing.

Core features:

1. AI forecasting: Predicts revenue using historical opportunity data and deal stage signals.
2. Interactive dashboards: Custom RevOps dashboards covering pipeline, rep performance, and funnel analytics.
3. Activity capture: Logs email and meeting activity automatically to improve CRM completeness.

Pricing: ~$65–$95/user/month per published benchmarks. Quote-based at scale.

Trial: None.

11. Anaplan

Enterprise connected planning platform for finance-owned revenue forecasting at scale.

Anaplan is a multi-purpose planning platform used for finance, supply chain, workforce, and sales forecasting. It sits at the enterprise tier and is typically owned by finance, not sales, making it a fit when forecasting needs to integrate with broader company planning.

Core features:

1. Multi-dimensional modeling: Build driver-based forecasts that connect sales, finance, and supply chain in one model.
2. Scenario planning: Model unlimited what-if scenarios across products, geographies, and business units.
3. Connected planning: Sales forecast integrates directly with financial plans, headcount, and capacity planning.

Trade-off: Complex to implement, requires dedicated admins, and often overkill for teams that only need sales forecasting.

Pricing: Starts around $30,000/year for entry deployments. Enterprise deployments commonly exceed $100,000/year.

Trial: None.

12. Revenue Grid

Salesforce-native revenue platform unifying forecasting, activity capture, and deal signals.

Revenue Grid runs inside Salesforce, which makes it a strong fit for Salesforce-first teams that want forecasting, engagement, and activity capture without leaving the CRM. Faster to adopt than Clari and lower operational friction.

Core features:

1. In-Salesforce forecasting: Forecast submissions, roll-ups, and predictions live natively inside the CRM.
2. Signal relay: Captures email and meeting signals to surface deal risks and stakeholder changes.
3. Engagement sequencing: Outbound cadences and follow-up automation inside the same workflow.

Pricing: Quote-based. Positioned as a cost-effective alternative to Clari for mid-market deployments.

Trial: Available on request.

13. Forecastio

Purpose-built forecasting tool for HubSpot-native revenue teams.

Forecastio is the rare standalone forecasting tool with published, flat-rate pricing. It connects to HubSpot (and Salesforce) and delivers AI predictions plus scenario modeling without requiring an enterprise contract. Best value for HubSpot customers who've outgrown HubSpot's native forecasting but aren't ready for Clari pricing.

Core features:

1. AI forecast corridor: Predicts forecast ranges (best case, commit, worst case) based on historical deal patterns.
2. Pipeline analytics: Deal velocity, conversion rates, and stage-level probability tracking.
3. HubSpot-native sync: Deep, bi-directional integration with HubSpot CRM.

Pricing: Flat $199/month starting. Tiered plans published publicly.

Trial: Free trial available.

14. ZoomInfo Copilot

AI forecasting layered on ZoomInfo's GTM data and engagement platform.

ZoomInfo Copilot uses the combination of ZoomInfo's B2B contact database and CRM engagement signals to generate pipeline predictions. It's positioned for teams already paying for ZoomInfo's GTM Workspace, where the forecasting layer comes bundled rather than as a standalone purchase.

Core features:

1. GTM Context Graph: Combines B2B data, buyer intent signals, and CRM engagement into forecast signals.
2. Pipeline analytics: Deal health scoring tied to account-level activity patterns.
3. Multi-CRM sync: Native integration with Salesforce, HubSpot, and Microsoft Dynamics.

Pricing: Custom, bundled within ZoomInfo GTM Workspace. Typically requires a broader ZoomInfo contract.

Trial: Demo only.

15. Chorus by ZoomInfo

Conversation intelligence platform with forecasting signals, now part of ZoomInfo.

Chorus is primarily a conversation intelligence tool, but its integration with ZoomInfo Copilot makes it part of the forecasting conversation in 2026. Works best for mid-market sales teams already in the ZoomInfo ecosystem who want call recording plus forecast signals without paying Gong pricing.

Core features:

1. Conversation capture: Records, transcribes, and analyzes sales calls with speaker separation and moment flagging.
2. Deal intelligence: Connects call signals to deal progression, flagging risks and next steps.
3. Forecast inputs: Feeds conversation signals into Copilot's forecasting layer.

Pricing: Per-user, bundled with ZoomInfo or purchased standalone. Typically lower than Gong.

Trial: Demo only.

How to choose the right AI sales forecasting tool

The 15 tools above solve different problems. Picking the right one is less about ranking and more about matching the tool to the specific failure mode in your current forecast.

• If your forecast is wrong because reps don't update deals, you need activity capture and deal inspection. MaxIQ, BoostUp, and People.ai all close this gap. People.ai is the specialist; MaxIQ and BoostUp cover it alongside full forecasting.
• If your forecast is wrong because you don't know what customers said on calls, conversation intelligence has to be part of the answer. MaxIQ (EchoIQ), Gong Forecast, Aviso, and Chorus all tie conversation signals to forecast predictions.
• If your forecast is wrong because of volume and complexity, you need a platform with deep scenario modeling and segment-level rollups. Clari, Aviso, Anaplan, and MaxIQ handle this tier.
• If your forecast is wrong because your CRM is the limiter, you need CRM-native forecasting before adding a tool. Salesforce Einstein, HubSpot Sales Hub AI, and Forecastio are the right starting points.
• If your forecast is wrong because post-sales isn't connected, MaxIQ is purpose-built for this. Most forecasting tools stop at closed-won revenue. MaxIQ extends through onboarding, adoption, and renewals, which is where SaaS net revenue retention actually lives.
• If budget is the limiter, start with MaxIQ or Forecastio ($199/month), HubSpot's built-in tools, or Revenue Grid. Clari, Gong, and Aviso require enterprise budget to make sense.
• If procurement timing matters, fast-deploy tools (MaxIQ, Forecastio, Revenue Grid) hit production in days. Enterprise platforms (MaxIQ - less than 1 week implementation time), Clari, Anaplan, Aviso) run 8–16 week implementations with professional services fees that often equal first-year license cost.

The decision comes down to three questions: what's actually breaking in your forecast today, what else do you want the tool to do beyond forecasting, and how fast do you need it live. That usually gets you to the right shortlist faster than any feature grid.

The bottom line

Forecasting software is no longer about reporting. It's about predicting revenue with enough confidence to run the business on the number.

The right choice depends on what you need the system to do. If you just need a better view inside the CRM, start there. If you need deep forecasting structure at enterprise scale, the heavier platforms still make sense. But if you want forecasting tied to real deal signals, faster deployment, and pricing that scales with usage instead of seats, AI-native revenue platforms like MaxIQ are where the category is moving.