--- title: "AI Sales Forecasting in 2026: How It Works + 7 Tools | Claap" description: "How AI sales forecasting works, the data it needs, how accurate it gets and how to roll it out, with Clari, Salesforce, HubSpot, Gong, Aviso, Terret compared." url: https://www.claap.io/blog/ai-in-sales-forecasting language: en --- # AI sales forecasting: how it works, its limits and the tools Learn how AI sales forecasting works, how accurate it can be, which techniques matter, and how conversation intelligence helps teams build more reliable forecasts. [Thomas Resnic](https://www.claap.io/authors/thomas-resnic) 20 August 2026 ![AI in Sales Forecasting: The Key to Smarter Predictions](https://cdn.sanity.io/images/gb4upfg4/staging/2d3eb0a7e1f7501bdc6d1e4e998a7aed003f87bb-1536x864.jpg?w=1080&h=608&fit=crop&auto=format&q=75) _Checked on 2026-10-08 by Pierre Touzeau, Founder & COO at Claap. Prices, product facts and G2 ratings checked against vendor pages, Vendr and G2 on 5–8 October 2026._ ## Article overview - **AI sales forecasting predicts the revenue a sales team will close in a period** by scoring every open deal on CRM data, activity and call signals, then rolling those scores up into a number managers can compare with the reps' commit. - **Clari Forecast is best for enterprise sales teams** that run a weekly forecast call and want roll-ups, inspection and AI projections in one dedicated tool. - **Salesforce forecasting is best for teams already on Sales Cloud** that want forecasts and AI insights inside the CRM they live in. - **HubSpot forecasting is best for HubSpot teams** that want a free AI second opinion on their forecast, currently in beta. - **Gong Forecast and Aviso are best for teams that want the forecast built on call and email activity**, with Gong suited to existing Gong customers and Aviso to enterprises that want a standalone forecasting platform. - **Claap is best for feeding any of these forecasts with call data.** It writes deal risks, next steps and qualification fields from every sales call into HubSpot or Salesforce, where the forecast tool reads them. Gartner found that poor data quality is one of the top barriers to sales analytics, cited by 44% of the sales leaders it surveyed ([Gartner, February 2024](https://www.gartner.com/en/newsroom/press-releases/2024-02-06-gartner-survey-finds-sales-analytics-has-less-influence-on-sales-performance-than-what-leadership-expected)). An AI forecast inherits that problem: it can only be as accurate as the deal data underneath it. This guide explains how AI sales forecasting works, what data it needs, how accurate it really is and how to roll it out. It then compares the seven tools sales teams shortlist in 2026. ## AI sales forecasting tools at a glance | Tool | Best for | Entry price | | --- | --- | --- | | **Clari Forecast (Salesloft)** | Enterprise teams with a weekly forecast call | Not public. Vendr median for Clari $76,000/yr | | **Salesforce forecasting** | Teams already running Sales Cloud | Sales Cloud Enterprise about $175/user/month. Revenue Intelligence $220/user/month | | **HubSpot forecasting** | HubSpot teams that want a free AI second view | Sales Hub Professional $90/seat/month (annual) | | **Gong Forecast** | Gong customers that want the forecast on call data | Not public. Est. about $700/user/year on top of Gong | | **Aviso** | Enterprises that want a standalone AI forecasting platform | Not public. Vendr median $73,662/yr | | **Terret (ex-BoostUp)** | Mid-market RevOps teams that want forecasting with board-ready summaries | Not public. Vendr median $30,420/yr | | **Claap** | Teams that want call data written into the CRM fields the forecast reads | Free plan. Pro $32, Business $60 per seat/month (annual) | _Vendr figures are median annual contract values from Vendr's purchase data, and "Est." marks a third-party estimate. Every other price is the vendor's own list price._ ## What AI sales forecasting is A sales forecast is the revenue a team expects to close in a period, usually the quarter. Traditional forecasts add up what each rep commits, often weighted by deal stage. AI sales forecasting replaces part of that judgment with models. Machine learning looks at your closed deals, learns which patterns came before a win or a loss, and scores every open deal against those patterns. The output is a second number that sits next to the reps' commit. Managers use the gap between the two to decide which deals to inspect in the next pipeline review. ## How AI sales forecasting works Most tools follow the same four steps. 1. **Collect the deal history.** The model reads closed won and closed lost deals from your CRM: amount, stage history, time in stage, close date changes, owner and segment. 2. **Add activity signals.** Emails sent and answered, meetings held, contacts engaged and, in tools that capture them, what buyers said on calls. 3. **Score each open deal.** Every deal gets a likelihood to close in the period, often with the top factors behind the score ("no meeting in 21 days", "economic buyer absent from every call"). 4. **Roll up and compare.** The scores roll up by rep, team and region into an AI projection, which managers compare with the commit, best case and pipeline categories in the forecast call. ![Four steps of AI sales forecasting: collect deal history, add activity signals, score open deals, roll up and compare](https://cdn.sanity.io/images/gb4upfg4/staging/7222a807044c29b5fa4fb7698b3fec51cc58f55f-1600x851.png?w=800&auto=format&q=75) The four steps most AI forecasting tools follow ## The data an AI forecast needs - **Clean CRM history.** Consistent stages, close dates that reflect reality and enough closed deals for the model to learn from. HubSpot's AI forecast, for example, projects from closed won deals of the past three months. - **Activity data.** Email and meeting activity logged automatically, since reps rarely log it by hand. - **Qualification data.** Whether the deal has a champion, an identified decision-maker, a budget and a decision date. Frameworks such as MEDDIC turn this into fields the model can read. - **Call data.** Risks, objections, competitors and next steps that buyers mention on calls. This is the input most CRMs miss, because it lives in conversations and depends on a rep typing it up. ## Why rep-confidence forecasts slip Claap records its own sales calls, and many prospects describe how they forecast before they buy anything. Three patterns came up in the past year. - **The forecast rests on a confidence field reps forget to update.** A B2B sales lead at a US healthcare training company with 10 reps described a forecast built on deal stage plus a rep's percent confidence: "inevitably on the call, someone's like, oh, that should have moved out to next quarter." What she wanted from call data: "based on what happened on this call, you should not be confident in this closing this quarter. Like, you should downgrade this \[...\] here are the things that happened in the call." - **Teams want a second model to challenge the commit.** The head of RevOps at a European software group of about 800 people said: "With all the data we collect today, we should be able to challenge the forecast easily. Today we have a commit-based forecast." On the weights in his model: "a most likely is 70%, based on the last quarter." (translated from French) - **AI needs conversation data before it can analyse a deal.** A sales operations lead at a French finance software company, rebuilding his pipeline before adding forecasting, said: "if we want to use AI for account analysis, forecast analysis, opportunity analysis \[...\], we need data." He described his current pipeline reviews as "a lot of meter reading." (translated from French) _Method: Claap's recorded sales calls from 1 October 2025 to 8 October 2026 with at least one external speaker, searched for "forecast" and for semantic matches on unreliable forecasts. We quoted buyers only, checked each quote against the full transcript, anonymised each speaker to their role and marked cuts with \[...\]._ ## How accurate AI sales forecasting is - **Most teams start from a low base.** Gartner research reported by Demand Gen Report found that only 7% of sales organizations reach forecast accuracy of 90% or more ([Demand Gen Report, March 2025](https://demandgenreport.com/demanding-views/harnessing-ai-transforming-sales-forecasting-for-greater-accuracy-and-strategic-action/48964)). ![Only 7% of sales organizations reach forecast accuracy of 90% or more](https://cdn.sanity.io/images/gb4upfg4/staging/c5b6773383e23096a91a695233ea0df2d71faa1e-1600x691.png?w=800&auto=format&q=75) Share of sales organizations with forecast accuracy of 90% or more. Source: Gartner research via Demand Gen Report, March 2025 - **Confidence is low too.** An earlier Gartner survey found that only 45% of sales leaders and sellers have high confidence in their organization's forecast accuracy ([Gartner, February 2020](https://www.gartner.com/en/newsroom/press-releases/2020-02-12-gartner-says-less-than-50--of-sales-leaders-and-selle)). - **Vendor accuracy claims are vendor-measured.** Gong says Gong Forecast uses 300+ signals to predict deal outcomes with 20% more precision than algorithms based on CRM data alone. Treat any uplift figure as a claim to test on your own history. - **Models need time.** Forecasting models learn from your closed deals, so a young team or a new segment gets weaker predictions until a few quarters of history exist. The practical test: run the AI projection next to your commit for one or two quarters, then compare both with the actual result before you trust either one. ## The main AI sales forecasting tools in 2026 ### Clari Forecast, best for enterprise teams with a weekly forecast call Clari merged with Salesloft in December 2025, and since September 2026 only Clari Forecast keeps the Clari name inside the Salesloft platform. It gives roll-ups against quota, commit and best case categories, deal inspection, an AI score per deal with its top factors, and a waterfall of how the forecast moved. The price is not public: Vendr's median Clari contract is $76,000 a year. G2 rates Clari 4.6 out of 5 from about 5,600 reviews, with reviewers praising the Salesforce integration and ease of forecasting, and flagging limits on customisation. ### Salesforce forecasting, best for teams already on Sales Cloud Sales Cloud includes collaborative forecasting, and Salesforce sells Revenue Intelligence as an add-on for pipeline inspection, forecast insights and AI deal signals. Sales Cloud Enterprise lists at about $175 per user per month (third-party read of the August 2025 price list), and Revenue Intelligence at $220 per user per month billed annually on salesforce.com. G2 rates Sales Cloud 4.4 out of 5 from about 25,000 reviews. ### HubSpot forecasting, best for HubSpot teams that want an AI second view HubSpot's forecast tool sits in Sales Hub, and its AI forecasting, in beta, projects future sales from closed won deals of the past three months as an extra view to calibrate the team's own forecast. A super admin turns it on, and creating forecasts needs a Sales or Service seat. Sales Hub Professional costs $90 per seat per month billed annually, with a $1,500 onboarding fee. G2 rates HubSpot Sales Hub 4.4 out of 5 from about 13,400 reviews. ### Gong Forecast, best for Gong customers Gong Forecast runs on the call, email and meeting data Gong already captures, with deal likelihood scores, scenarios (open, best case, most likely) and a view of risk per deal. Gong does not publish prices: Vendr's median Gong contract is $55,359 a year, and pricing guides estimate Forecast at about $700 per user per year on top. G2 rates Gong 4.7 out of 5 from 6,743 reviews. ### Aviso, best for a standalone AI forecasting platform Aviso is built around revenue forecasting, with deal and pipeline inspection, conversation and relationship intelligence, manager coaching and an AI agent called MIKI. Pricing is on quote, and Vendr's median Aviso contract is $73,662 a year. G2 rates Aviso 4.3 out of 5 from 983 reviews, with ease of use and AI predictions the most praised themes and a slow Salesforce sync the most cited complaint. ### Terret (formerly BoostUp), best for mid-market RevOps teams BoostUp renamed itself Terret in September 2025. Its forecasting module promises board-ready narratives, with roll-ups and an AI insight layer that cites CRM data, call transcripts, email activity and product usage. Pricing is not public, and Vendr's median contract is $30,420 a year. G2 rates Terret 4.4 out of 5 from about 612 reviews. ### Claap, best for feeding the forecast with call data Claap is conversation intelligence for sales teams. It [records every sales call](https://www.claap.io/product/sales-call-recording) on Zoom, Google Meet, Microsoft Teams, phone through Aircall and in person, then turns each call into CRM fields in HubSpot or Salesforce: deal risks, next steps, qualification fields such as MEDDIC, scores and follow-up emails. Claap feeds the forecast with call data; Clari or your CRM runs the forecast. The same data is open to Claude and other AI agents through the Claap MCP, on every plan. Basic is free, Pro is $32 and Business $60 per seat per month billed yearly, and G2 rates Claap 4.6 out of 5 from 480+ reviews. **Deals** Deal Warnings Close date Amount FFretly - Pro Plan — Oct 12 €150,000 QQuillo - Renewal 2027 Checking2 Oct 14 €74,200 TTessly - Expansion 1 Oct 20 €110,000 BBrightwell - Enterprise Plan — Oct 24 €120,000 OOakline - Pro Plan 1 Nov 3 €98,000 HHubbo - Enterprise Plan — Nov 9 €66,400 Warnings · Quillo No economic buyer “Nobody has owned this since Marta left.” Renewal call · 09:41 Claap in action Deal risk, read from the call [Start for free](https://app.claap.io/sign-up)[Book a demo](https://www.claap.io/contact?utm_content=listicle_claap) ![Rated 5/5 on Google, 4.9/5 on G2 and 4.9/5 on Product Hunt](https://www.claap.io/media/d8ea86f4-6a478bfd4eb66f8395ed1e23_reviews-gold-v2.svg) ## Where Claap fits in an AI forecast Every tool above reads CRM fields. The fields that move a forecast most (is there a champion, did the economic buyer join, what is the next step, what risk did the buyer raise) are the ones reps fill in last. Claap fills them from the call itself. A rep runs a discovery call, and Claap [writes the pain, the decision process and the next step into the deal](https://www.claap.io/product/crm-auto-complete) in HubSpot or Salesforce. Your forecast tool then scores that deal on what the buyer actually said. That makes Claap a companion to the forecasting tools on this list. Teams on HubSpot or Sales Cloud forecasting get call evidence in the CRM, and teams on Clari or Aviso get cleaner inputs for their models. For the wider category, see our guide to [revenue intelligence](https://www.claap.io/product/revenue-intelligence). ## How to roll out AI sales forecasting 1. **Fix the pipeline definitions first.** Agree on what creates a deal, what each stage means and when a deal is killed. A model trained on inconsistent stages learns noise. 2. **Automate the inputs.** Log emails and meetings automatically and capture calls into CRM fields, so the model reads data reps did not have to type. 3. **Add a qualification framework.** MEDDIC or a lighter variant gives every deal the same fields, which the model and the manager can both read. 4. **Run the AI next to the commit.** Keep the rep commit, show the AI projection beside it for a quarter or two and inspect the deals where they disagree. 5. **Measure and adjust.** Compare both numbers with actual results each quarter, and only then move budget or headcount decisions onto the AI projection. ![Five rollout steps: fix pipeline definitions, automate inputs, add a qualification framework, run AI next to commit, measure](https://cdn.sanity.io/images/gb4upfg4/staging/2e7812e2a237962127eede75c4e303b1f72377ca-1600x1143.png?w=800&auto=format&q=75) The five steps to roll out AI sales forecasting To compare the platforms that bundle forecasting with call data, read our roundup of [revenue intelligence software](https://www.claap.io/blog/revenue-intelligence-software). For tools that analyse calls, see our guide to [conversation intelligence software](https://www.claap.io/blog/conversation-intelligence-software). ## The limits of AI sales forecasting - **Data quality.** Missing close dates, stale stages and empty qualification fields produce confident, wrong predictions. Clean the data before you buy the model. - **Adoption.** Reps who only see their own commit keep forecasting by gut. Show the score in the pipeline review, where reps defend their deals. - **Human judgment.** A model sees patterns; a manager knows the buyer's reorganisation or the budget freeze announced yesterday. The strongest forecasts combine both. - **Privacy.** Call and email data fall under privacy rules such as the GDPR in Europe. Check consent, hosting and retention with every vendor that processes conversations. ## How we built this guide We searched "ai sales forecasting" on 8 October 2026 and matched the format of the top results, which explain the method before naming tools. Prices come from vendor pages where published and from Vendr's purchase data otherwise. G2 ratings come from G2 pages and search results read between 5 and 8 October 2026, because G2 blocks automated reads. We captured no verbatim G2 review lines for this version. Claap publishes this article and appears in the comparison. We placed it last and describe it as an input to the forecast, which is what it does. Share [Remote Works](https://www.claap.io/category/remote-works) Written by [Thomas Resnic](https://www.claap.io/authors/thomas-resnic) Discover Thom's tips on Claap, Conversation Intelligence, AI for Sales [Articles by Thomas](https://www.claap.io/authors/thomas-resnic)[LinkedIn profile](https://www.linkedin.com/in/thomas-resnic/) ## Frequently asked questions What is AI sales forecasting? AI sales forecasting uses machine learning on CRM history, activity and call data to predict which open deals will close in a period and how much revenue they will bring. It gives managers a second number to compare with the reps' commit. How accurate is AI sales forecasting? It depends on the data. Gartner research reported in 2025 found that only 7% of sales organizations reach 90% forecast accuracy or more, and vendor uplift claims are measured by the vendors themselves. Test any model on your own past quarters before you rely on it. What data does an AI sales forecast need? Clean deal history with consistent stages and close dates, logged email and meeting activity, qualification fields such as MEDDIC, and call data on risks and next steps. The more of it is captured automatically, the better the model performs. Does AI replace the sales rep's commit? No. Most teams keep the commit and use the AI projection to challenge it, then inspect the deals where the two disagree in the pipeline review. Is Claap a sales forecasting tool? Claap feeds the forecast with call data; Clari or your CRM runs the forecast. It writes deal risks, next steps and qualification fields from every call into HubSpot or Salesforce, where your forecasting tool reads them. How long does it take to roll out AI forecasting? Plan one or two quarters. The model needs closed deal history to learn from, and the team needs to see the AI projection next to the commit before it trusts the number. ## Related articles - [![7 Sales Coaching Best Practices for High Performance](https://cdn.sanity.io/images/gb4upfg4/staging/01f8538adac663d2377a93fed4f220db81b82e5d-1536x864.jpg?w=800&h=450&fit=crop&auto=format&q=75) Remote Works ## Sales performance coaching: 7 practices of top sales teams Sales performance coaching that moves quota: 7 practices sales managers run every week, from coaching one skill per rep to scoring calls and roleplay. 4 Sept 2026 · Victoire Leveilley](https://www.claap.io/blog/high-performance-sales-coaching) - [![Learn how sales videos can help you win more deals Tips, Techniques & Examples](https://cdn.sanity.io/images/gb4upfg4/staging/4fa75cfa344cd19baf7441ee052b6bf048026d48-1536x864.jpg?w=800&h=450&fit=crop&auto=format&q=75) Remote Works ## Learn how sales videos can help you win more deals \[Tips, Techniques & Examples\] What sales videos are, the types that work at each stage, and how to record one that gets a reply. With tips, techniques and examples for sales reps. 4 Sept 2026 · Victoire Leveilley](https://www.claap.io/blog/sales-video) - [![7 Best ChatGPT Prompts For Sales Demo Scripts That Get People Talking (+ Templates)](https://cdn.sanity.io/images/gb4upfg4/staging/6b6cb89b365bda70965f8268adfa21f817845ca4-1536x864.jpg?w=800&h=450&fit=crop&auto=format&q=75) Remote Works ## 7 Best ChatGPT Prompts For Sales Demo Scripts That Get People Talking (+ Templates) Explore the best ChatGPT prompts for Sales Demo scripts that drive conversions. Learn how to craft effective, engaging scripts using AI to enhance your sales success. 4 Sept 2026 · Max Gayler](https://www.claap.io/blog/best-prompts-for-sales-demo-scripts) ## Ready to claap? [Book a demo](https://www.claap.io/contact)[Start for free](https://app.claap.io/sign-up)