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saas · 8 use cases

Top agentic AI use cases for SaaS in H2 2026

Buyers now research software through AI answer engines and, increasingly, their own agents, while new transparency and consent rules arrive on fixed dates. These eight use cases respond to what changed in 2025 and 2026.

Which agentic AI use cases should SaaS companies prioritise in H2 2026?SaaS companies should prioritise agentic work that follows how buyers now buy: winning citations in AI answer engines, answering buyer agents’ questionnaires and quote requests, selling through cloud marketplaces, running a website assistant that discloses it is AI under the EU AI Act, and building a consent ledger before India’s DPDP Rules take full effect.

Category visibility in ChatGPT, Gemini and Google AI Mode

Buyers increasingly ask an AI engine for the best tool in a category before visiting any vendor site; G2 reports that 79% of the software buyers it surveyed agree AI search has changed how they research, and Pew Research Center found Google users were less likely to click a result link when an AI summary appeared. DRIS tracks which brands and sources the engines cite for your category prompts and closes the gaps in the pages and profiles they draw on.

Every week, DRIS runs the agreed category prompts across ChatGPT, Gemini, Perplexity and Google AI Mode, recording which brands are named and which pages are cited. A competitor now appears where the brand used to. DRIS drafts fixes: a clearer docs page, a plain HTML pricing table, a new FAQ answer. The SEO lead approves each change and its claims before it goes to Webflow. Share of answers naming the brand becomes a measured figure, not a guess.
a scene from the weekSEO lead at a business software company. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerEvery week, run the agreed set of category, use-case and “alternative to” prompts across ChatGPT, Gemini, Perplexity and Google AI Mode.
  2. Record which brands are named, in what order, and which pages, docs and review profiles are cited.
  3. Compare against last week and against named competitors to find the prompts you are losing.
  4. Draft fixes such as a clearer docs page, a pricing table in plain HTML, an updated G2 profile or a new FAQ answer.
  5. Approved by Content or SEO leadThe content or SEO lead approves each change and its factual claims before publishing.
  6. Publish, then re-run the affected prompts and log whether citations moved.
in the roomAIDRISPeopleContent or SEO leadTry this workflow
connects toChatGPT, Gemini, Perplexity and Google AI Mode, Google Search Console, Webflow or WordPress, G2 profile
measure it byShare of answers naming your brand for category prompts, Citations to your own domain, Sign-ups from AI referrals

Guardrail. Google’s guidance says AI features need no special markup beyond normal Search eligibility, so fix the content itself and never publish a claim the SaaS Strategist cannot verify.

Answering buyer agents’ RFPs, security questionnaires and quotes

Forrester predicts that in 2026 at least one in five B2B sellers will have to answer AI-powered buyer agents with counteroffers from seller-controlled agents. DEXA, our deal execution teammate, is coming soon. It will answer questionnaires and RFPs from approved sources and keep commercial terms inside the bands deal desk has set.

A security questionnaire and a structured quote request arrive through a buyer’s Coupa portal on the same morning. DEXA, coming soon, will classify each question, pull answers from the trust centre library and mark any gaps for their owners, keeping commercial terms inside deal desk’s pre-approved bands. The security lead approves the security answers and deal desk approves pricing before submission. Final answers will go back into the library.
a scene from the weekDeal desk manager at an enterprise software vendor. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerA security questionnaire, RFP or structured quote request arrives by email, procurement portal or a buyer’s agent.
  2. Classify each question as security, product, legal or commercial, and pull answers from the approved trust centre library and audit reports.
  3. Draft the response and mark every question without an approved answer for its subject owner.
  4. Prepare commercial terms and any counteroffer inside the discount and term bands deal desk has pre-approved.
  5. Approved by Security leadThe security lead approves the security answers and deal desk approves pricing and terms before submission.
  6. Submit, save the final answers back to the library and log the outcome on the opportunity.
in the roomAISERA with DEXA (coming soon)PeopleSecurity leadComing soon
connects toSalesforce CPQ or HubSpot Quotes, Trust centre and policy library, Coupa or SAP Ariba portals
measure it byQuestionnaire turnaround time, Answers needing expert rewrite, Win rate on RFP-led deals

Guardrail. Never state a certification, data residency commitment or security control that the current audited evidence does not support, and never agree terms outside deal desk’s bands.

Cloud marketplace listings, private offers and partner co-sell

AWS opened an AI Agents and Tools category in AWS Marketplace in July 2025, with listings that show Model Context Protocol support, and Gartner forecasts that AI agents will intermediate more than $15 trillion of B2B spending by 2028, as reported by Digital Commerce 360. NORA keeps listings accurate, finds partner overlap and prepares private offers for approval.

A partner-sourced referral appears in AWS Partner Central. NORA researches the account’s cloud provider and procurement route, then drafts updates to the AWS Marketplace listing, including MCP support where it exists, plus a private offer and a co-sell note for the partner’s account manager. The partnerships lead and deal desk approve the listing and offer terms. The opportunity is registered with the partner and tracked in Salesforce, and private offer cycle time becomes visible.
a scene from the weekPartnerships lead at a cloud-native SaaS company. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerA partner-sourced referral arrives in AWS Partner Central, or a target account appears in a partner’s account overlap.
  2. Research the account’s cloud provider, procurement route and existing partners from CRM notes and public sources.
  3. Draft updates to the marketplace listing copy, pricing dimensions and integration details, including MCP support where it exists.
  4. Draft the private offer and the co-sell note to the partner’s account manager.
  5. Approved by Partnerships lead and Deal deskThe partnerships lead and deal desk approve the listing changes and private offer terms before they are published or sent.
  6. Publish the offer, register the opportunity with the partner and track it in the CRM.
in the roomAISERA with NORAPeoplePartnerships lead and Deal deskTry this workflow
connects toAWS Marketplace and Partner Central, Microsoft or Google Cloud marketplaces, Salesforce or HubSpot
measure it byMarketplace-sourced pipeline, Private offer cycle time, Partner-registered opportunities won

Guardrail. Listing claims about integrations, MCP support and security must match what the product does today, and private offer terms stay within the approved price book.

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A website and in-app assistant that says it is AI and books demos

From 2 August 2026, Article 50 of the EU AI Act requires that people are told when they are interacting with an AI system unless it is obvious, and Gartner’s 2026 survey found two thirds of B2B buyers prefer a rep-free experience. Convexa answers pricing, security and fit questions from approved sources, says it is AI and hands over to a person when the buyer wants one.

Late in the evening, a visitor opens chat on the pricing page. Convexa says in its first message that it is AI, answers from approved pricing, docs and trust centre content, and asks the agreed questions on team size, use case, current tool and timeline. Qualified accounts get a meeting in the right account executive’s Google Calendar. Sales leadership approves the answer library and handoff rules. Meetings booked from chat arrive with the transcript already in HubSpot.
a scene from the weekHead of sales at a mid-market SaaS company. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerA visitor opens chat on the pricing page, or a trial user asks a question inside the product.
  2. Disclose in the first message that the assistant is AI, then answer only from approved pricing, docs and trust centre content.
  3. Ask the qualifying questions sales has agreed: team size, use case, current tool and timeline.
  4. Offer self-serve sign-up to small teams and a meeting with the right account executive to qualified accounts.
  5. Approved by Sales leadershipSales leadership approves the answer library, qualification rules and handoff criteria before any change goes live.
  6. Book the meeting in the account executive’s calendar and write the transcript and qualification to the CRM.
in the roomAIConvexaPeopleSales leadershipTry this workflow
connects toWebsite and in-app chat, Salesforce or HubSpot, Google Calendar or Outlook
measure it byQualified meetings booked from chat, Questions answered without escalation, Chat to sign-up conversion

Guardrail. Disclose AI at first contact under EU AI Act Article 50, and never let the assistant quote a price, discount or security commitment outside the approved library.

Cancellation and downgrade conversations handled without friction

In self-serve SaaS, cancellations and downgrades arrive as in-app clicks or support chats, and each one is the last chance to keep the customer. Convexa learns the reason, offers the options the team has approved and processes the cancellation straight away when the customer still wants to leave.

A customer clicks downgrade in billing settings. Convexa asks one question about the reason, checks usage and Stripe billing history, and offers the matching pre-approved option: a pause, a smaller plan or a monthly term. For an account above the agreed size, the CSM approves any custom save offer first. If the customer still wants to leave, Convexa cancels at once and confirms in writing. The team tracks save rate without ever making leaving harder.
a scene from the weekCustomer success lead at a self-serve SaaS company. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerA customer clicks cancel or downgrade in billing settings, or asks support to end the subscription.
  2. Ask one question about the reason and check usage, plan and billing history.
  3. Offer the matching pre-approved option: a pause, a smaller plan or a monthly term.
  4. Approved by CSMFor accounts above the agreed size, the CSM approves any custom save offer before it is made.
  5. Process the cancellation at once if the customer declines, and confirm it in writing.
  6. Log the reason and outcome to the CRM and send monthly churn reasons to product.
in the roomAIConvexaPeopleCSMTry this workflow
connects toStripe, Chargebee or Recurly, Intercom or Zendesk, Salesforce or HubSpot
measure it bySave rate on cancellation conversations, Churn reasons captured, Complaints about the cancellation process

Guardrail. Never obstruct or delay a cancellation; US automatic renewal laws require an easy way to cancel consumer plans, the UK’s subscription contracts regime follows in January 2027, and the same standard protects B2B trust.

Consent ledger ahead of India’s DPDP Rules and EEA ad consent

MeitY notified the Digital Personal Data Protection Rules in November 2025, with consent manager rules due from November 2026 and most notice, consent and erasure duties from May 2027, and Google already requires EEA consent signals on Customer Match uploads. RIVA, our revenue operations teammate, is coming soon. It will build one record of where each contact’s consent came from and keep every tool in step with it.

Each night, RIVA, coming soon, will pull consent and opt-out records from the CRM, the email platform, sign-up forms and the webinar tool into one ledger per contact. It will flag contacts used for a purpose they never agreed to and propose suppressions across Salesloft, the CRM and ad audiences. The privacy owner approves each suppression and erasure. SERA will then push the changes to every tool.
a scene from the weekPrivacy lead at a business software company selling into India and Europe. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerEach night, pull consent and opt-out records from the CRM, the email platform, product sign-up forms and the webinar tool.
  2. Reconcile them into one ledger per contact with source, notice version, purpose and date.
  3. Flag contacts used for a purpose they never agreed to and records held past the retention period.
  4. Propose suppressions in the CRM, sequencer and ad audiences, plus erasure of expired records.
  5. Approved by Privacy or legal ownerThe privacy or legal owner approves suppressions, erasures and any new notice wording before they are applied.
  6. Push the approved changes to every connected tool and set Customer Match consent signals on EEA and UK uploads.
in the roomAISERA with RIVA (coming soon)PeoplePrivacy or legal ownerComing soon
connects toSalesforce or HubSpot, Google Ads and LinkedIn audiences, Outreach or Salesloft, Consent management platform
measure it byContacts with a recorded basis and source, Time to honour an opt-out across tools, Audience uploads rejected for missing consent

Guardrail. Treat the DPDP Act 2023 and DPDP Rules 2025 dates as hard deadlines, and upload no EEA or UK contact to Customer Match without both consent signals granted.

Expert and creator-led programmes for the buying committee

Forrester predicts that 75% of enterprise B2B companies will increase budgets for influencer relations in 2026. MOXA, our social media teammate, is coming soon. It will map the practitioners and analysts your buyers already follow, draft briefs with disclosure built in and track what the programme produces.

At the start of each month, MOXA, coming soon, will map the practitioners and analysts whose LinkedIn posts and podcasts target buyers follow, dropping anyone with undisclosed paid posts. MIRA will draft a brief per creator with approved product facts and the required disclosure wording. The community lead approves the list, each brief and any paid agreement before outreach. Published posts will be checked for disclosure labels.
a scene from the weekCommunity lead at an enterprise software company. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerEach month, map the practitioners, analysts and community leaders whose posts target buyers engage with on LinkedIn, YouTube and podcasts.
  2. Score each for relevance and audience fit, and drop anyone with a record of undisclosed paid posts.
  3. Draft a brief per creator with the problem to discuss, approved product facts and the required disclosure wording.
  4. Approved by Brand or community leadThe brand or community lead approves the creator list, each brief and any paid agreement before outreach.
  5. Track published posts, check disclosure labels and attribute engagement and sign-ups from tracked links.
  6. With the creator’s permission, propose the strongest posts as paid LinkedIn thought leader ads.
in the roomAIMIRA with MOXA (coming soon)PeopleBrand or community leadComing soon
connects toLinkedIn, YouTube, Salesforce or HubSpot
measure it byEngagement from target accounts, Pipeline influenced by creator content, Posts carrying correct disclosure

Guardrail. Paid or gifted posts carry clear disclosure under the FTC Endorsement Guides and ASCI’s guidelines for influencer advertising in India.

Role-based demo videos for each buying committee, clearly labelled

Enterprise deals involve several stakeholders who rarely all attend the demo. Alpha cuts a short video per role from approved product footage and the call notes, with any synthetic voice or avatar labelled, so the champion can share it internally.

A discovery call ends and the recording lands in Gong. Alpha identifies each stakeholder, such as security for IT and reporting for finance, and cuts a short video per role from approved product footage. CREA labels any synthetic voiceover as AI-generated, and the account executive adds a recorded intro, then approves each video and script. The champion shares them through a tracked Vidyard link, and views by role show which stakeholders are engaged.
a scene from the weekAccount executive at an enterprise software vendor. Illustrative, built from this workflow, not from a client.

the workflow, in one room

  1. TriggerA discovery or demo call ends and the notes and recording land in Gong or the CRM.
  2. Identify the stakeholders named and what each cares about, such as security for IT and reporting for finance.
  3. Assemble a short video per role from approved product footage and screen recordings, scripted from the call.
  4. Label any synthetic voiceover or avatar as AI-generated and add the account executive’s own recorded intro.
  5. Approved by Account executiveThe account executive approves each video and script before it goes to the champion.
  6. Send through a tracked link and log views by role on the opportunity.
in the roomAICREA with AlphaPeopleAccount executiveTry this workflow
connects toGong or Chorus, Salesforce or HubSpot, Vidyard or Wistia
measure it byStakeholders engaged per opportunity, Video views by role, Stage progression after a video is sent

Guardrail. Label synthetic voice and avatars as AI-generated, as EU AI Act Article 50 requires for deep fakes, and never synthesise a real person’s likeness without their written consent.

Frequently asked questions

What changed for SaaS go-to-market in 2025 and 2026?

Buyers moved research into AI engines: Gartner’s 2026 survey found two thirds of B2B buyers prefer a rep-free experience, and Pew Research Center found Google users were less likely to click links when an AI summary appeared. At the same time, EU AI Act transparency duties began on 2 August 2026, and India’s DPDP Rules set dates in November 2026 and May 2027.

Do we have to tell buyers they are talking to an AI?

For people in the EU, yes, from 2 August 2026 under Article 50 of the EU AI Act, unless it is obvious from the context. Disclosing in the first message is the simplest way to comply in every market. Buyers who want a person can then ask for one.

How should a SaaS company prepare for buyer agents?

Make your facts easy for a machine to read and hard to misquote: pricing, plan limits, integrations and security evidence on plain, current pages. Then decide in advance which commercial terms an agent may offer and which need deal desk. Forrester expects some sellers to face agent-led quote negotiations during 2026.

Which of these should we start first?

Start with the work that has fixed dates: AI disclosure on any chat assistant and a consent ledger for the DPDP Rules and Customer Match. Run answer-engine tracking alongside, because you cannot fix citations you are not measuring. Buyer-agent and marketplace work can follow once those foundations are in place. On Nagent, the consent ledger will run on RIVA and buyer-agent answers on DEXA, both coming soon.

sources

  1. Gartner: Sales survey finds 67% of B2B buyers prefer a rep-free experience (2026)
  2. Forrester: 2026 B2B marketing, sales and product predictions (2025)
  3. G2: 2025 Buyer Behavior Report
  4. Pew Research Center: Google users are less likely to click on links when an AI summary appears (2025)
  5. Google Search Central: AI features and your website
  6. Digital Commerce 360: Gartner says AI agents will intermediate $15 trillion in B2B purchases by 2028 (2025)
  7. AWS Partner Network Blog: Partner guide to AI agents and tools in AWS Marketplace (2025)
  8. Cooley: EU AI Act transparency obligations take effect 2 August 2026 (2026)
  9. SCC Online: MeitY notified Digital Personal Data Protection Rules, 2025 (2025)
  10. Google Ads Help: EU user consent policy for Customer Match upload partners
  11. CMA: Direct consumer enforcement, 18 months on (2026)

free guide

18 AI agent use cases for SaaS & Technology

Every workflow on these pages as a designed guide and a presentation deck, ready to share with your team: a scene from the week, the workflow drawn with its approval gate, the systems it connects to and how to measure it. Light and dark editions, updated every month.

  • Top 10 sales and marketing use cases for AI agents in SaaS
  • Top agentic AI use cases for SaaS in H2 2026
  • Who is in the room: your AI team for saas and the people who approve
  • The guardrails and the rules they come from, with sources

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