Bain & Firm has estimated a US$100 billion market within the US for SaaS corporations utilizing agentic AI. The agency mentioned the market is tied to automating coordination work in enterprise programs.
The estimate comes from the second report in Bain’s five-part sequence on the software program business within the age of AI. The report examines the place agentic AI may create new software program markets and the way SaaS corporations can seize them.
Coordination work in enterprise programs
Bain mentioned the market lies within the guide work workers carry out between enterprise functions. These workflows typically span ERP, CRM and assist programs. They might additionally contain vendor administration instruments and e mail.
That work contains pulling information from one system and checking it towards one other supply. It may well additionally contain decoding unstructured messages and deciding whether or not to approve, reply, escalate, or wait.
Bain mentioned rules-based automation and robotic course of automation are restricted in workflows involving ambiguity and knowledge unfold in a number of programs. Agentic AI can interpret data from totally different sources, coordinate actions in programs, and function in coverage guardrails.
The report argues that agentic AI is just not primarily a alternative for SaaS platforms, however that the market comes from changing labour-intensive coordination work into software program spending.
It estimates distributors are already capturing US$4 billion to US$6 billion of the US market. Greater than 90% stays untapped, in response to the agency.
Exterior the US, Bain estimated that Canada, Europe, Australia, and New Zealand may add a similar-sized market. That may carry the full in these areas and the US to about US$200 billion.
Market measurement by perform
The market is just not evenly distributed in enterprise capabilities. Bain estimates that gross sales represents the biggest single share at about US$20 billion. That is primarily because of the variety of gross sales workers, not unusually excessive automation potential.
Price of products bought and operations account for about US$26 billion. The big measurement of the operational workforce means even modest automation charges can translate into a big addressable market. R&D and engineering, buyer assist, and finance every symbolize about US$6 billion to US$12 billion in addressable market measurement. These capabilities have sizeable workforces and better automation potential in particular workflows.
Buyer assist and R&D or engineering have the best automation potential, with roughly 40% to 60% of workflow duties automatable. Bain mentioned each areas have structured information, standardised processes, and clearer output alerts. Finance and human assets fall within the 35% to 45% vary. The report mentioned accounts payable and payroll have increased automation potential, whereas monetary planning and worker relations contain extra judgement.
Gross sales and IT sit at 30% to 40%. Bain pointed to relationship nuance, deal-by-deal variation, and the unpredictable nature of safety incidents as limits on automation in these areas. Authorized has decrease general automation potential, at 20% to 30%. Bain mentioned contract evaluate and compliance are repeatable, however the penalties of errors create a necessity for tighter oversight.
Bain’s automation elements
The report identifies six elements that decide how a lot of a workflow can realistically be dealt with by an AI agent. They embody output verifiability, consequence of failure, digitised information availability, and course of variability. Bain mentioned workflows with clear verification alerts are simpler to automate than work involving subjective judgement. Examples embody compiling code, reconciled invoices, and resolved assist tickets.
Workflows involving regulatory or monetary danger require nearer human supervision, even the place brokers are technically succesful, in response to the report. These embody tax filings, authorized compliance, and safety incident response.
Bain additionally recognized digitised information availability as a constraint. Brokers want entry to structured information and documented context. Additionally they want machine-readable inputs, together with resolution logic that always sits informally with skilled workers.
Integration complexity impacts automation when workflows go by a number of programs and APIs. Authentication layers and exception-handling processes add additional complexity, and these workflows are tougher to automate end-to-end than workflows contained in a single platform. The best-value areas are concentrated the place no single system of document controls the complete consequence. These workflows typically span ERP, CRM and assist programs, the corporate says.
David Crawford, chairman of Bain’s world expertise and telecommunications apply, mentioned SaaS corporations have spent the previous 20 years constructing positions round programs of document with the subsequent supply of benefit being “cross-workflow resolution context,” which is outlined as the flexibility to interpret and act in workflows that transfer by a number of programs.
Firm examples and adjoining workflows
The report cited Cursor, Sierra, Harvey, Glean, Salesforce, ServiceNow, and Workday in its dialogue of agentic AI adoption. Cursor has surpassed US$16.7 million in common month-to-month income, in response to Bain, after doubling in a single quarter. Sierra has crossed US$150 million each year, Harvey handed US$190 million pa, and Glean US$200 million pa.
The report additionally pointed to GitHub for instance of an organization utilizing information from an current core workflow to maneuver into adjoining work. GitHub’s core enterprise is developer collaboration and supply management, however its repository and workflow information helped assist growth into AI-assisted developer productiveness and safety automation.
Bain mentioned SaaS corporations can broaden by two varieties of workflow automation. The primary is automating core workflows, the place they have already got area information and buyer belief. Bain mentioned current system integrations can assist automation of core workflows. The second is automating adjoining workflows that the corporate doesn’t presently serve instantly. These areas will be tougher to determine as a result of they require detailed mapping of buyer workflows and the underlying information that helps choices.
Pricing fashions can change when brokers ship accomplished outcomes. Bain mentioned outcome- and use-based pricing can grow to be extra related when brokers resolve points or course of invoices. The report contrasts this with conventional pricing based mostly on seats and logins.
Bain’s suggestions for SaaS corporations
Bain really useful that SaaS corporations start by figuring out which buyer workflows at the moment are automatable with agentic AI. The agency mentioned corporations ought to assess automation on the subprocess degree not treating complete capabilities as equally automatable.
The report additionally mentioned corporations ought to assess the standard of their information. Bain mentioned related elements embody whether or not the information is complete, tied to outcomes, and usable for automation.
Bain mentioned corporations may shut potential gaps by inside growth, acquisitions, or partnerships. The report cited AppLovin’s in-house growth of its Axon platform, ServiceNow’s acquisition of Moveworks, and Salesforce’s partnership with Workday as examples of various approaches.
The agency additionally pointed to the necessity for AI engineering expertise, cloud-native structure for multi-agent orchestration, and funding for mannequin coaching and inference. It mentioned corporations ought to align pricing and gross sales incentives with AI-driven outcomes not legacy seat-based fashions.
Bain mentioned SaaS corporations can even want information and product foundations designed for agentic workflows, together with machine-readable hand-offs and programs that seize choices and outcomes from every workflow run.
Crawford mentioned the timeframe for SaaS corporations is “measured in quarters, not years,” as AI-native corporations collect extra deployment information with every buyer workflow they automate.
(Photograph by engin akyurt)
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