AI Boosts Win Rates as Enterprises Automate Mission-Critical Workflows at TMT Conference
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Appian (NASDAQ:APPN) Chief Financial Officer Serge Tanjga said the company is focused on automating “mission-critical” processes for large enterprises and public-sector customers, particularly in highly regulated industries, during a discussion at Morgan Stanley’s TMT conference. Tanjga, who joined the company in mid-2025 after more than a decade at MongoDB, described Appian as a process automation platform that typically replaces manual workflows, underperforming custom-built applications, or legacy solutions that span multiple information silos.
Tanjga cited customer examples to illustrate Appian’s use cases, including automating customer onboarding and management for a large asset manager, credit card dispute resolution for an Australian bank, and order-to-install workflows for a medical equipment manufacturer. In the public sector, he said a large civilian agency uses Appian to automate fraud identification and resolution work that previously required manual effort and pulling data from multiple systems.
He also addressed investor perceptions that Appian is simply a “low-code” tool for building relatively simple applications. In his view, the label can obscure the complexity of Appian’s deployments. Tanjga said implementations are typically delivered by Appian or third-party partners, with customers paying “five to eight figures” for implementations. He characterized the work as difficult to implement and “very sticky,” emphasizing that Appian’s “low-code” approach is less about citizen developers and more about enabling reusable solutions without hiring large teams of expensive developers to build custom code.
Tanjga pushed back on investor concerns that AI could disintermediate process automation platforms, arguing that customer conversations are focused less on replacing software and more on getting their first successful AI use case into production. He said enterprises are looking for AI that can run at scale inside operational workflows with high accuracy, which he described as challenging because AI is “probabilistic” and needs to operate within “deterministic” systems to deliver reliable outcomes in areas like onboarding, procurement, and budgeting.
As an example, he described a North American insurance company adopting Appian’s DocCenter, an AI-enabled document extraction product, for a first in-production use case handling 400,000 documents per year. He said it took a few months to implement and tune for accuracy, and the customer is now discussing a second use case involving 1.2 million documents per year. Tanjga added that when customers are ready to adopt AI, Appian’s win rates are “meaningfully higher” than normal, which he views as validation of Appian’s approach of using AI as “a node in the process” rather than as a replacement for end-to-end workflows.
According to Tanjga, about 80% of Appian’s business comes from government, financial services, insurance, and healthcare—industries he described as “demanding,” “risk-averse,” and highly regulated. He said Appian’s framework is to deploy the best tool at each point in a process, citing historical nodes such as business rules engines, RPA bots, and process mining, with AI as another “worker” to use in the right context.
He also highlighted platform capabilities including security, auditability, compliance, and certifications, arguing these are difficult for AI tools to replicate and are essential for complex workloads that require high accuracy. Looking further out, he said it is difficult to envision a world where AI is fully self-sufficient and self-governing, and he framed competitive threats as a long-standing reality in software, emphasizing the difficulty of building enterprise-ready solutions with customer trust in Appian’s core verticals.
Tanjga said Appian’s AI capabilities have evolved from earlier AI/ML integrations toward a broader GenAI roadmap. He outlined a progression of offerings:
AI Skills: Features that allow customers to call a large language model within a process to generate specific outputs.
DocCenter: AI-enabled document extraction, launched in late 2024, with production deployments across industries.
Agent Studio: A more autonomous “agentic” offering, with initial customers reaching production.
Composer/Modernization: Early-stage efforts to modernize legacy technology into a modern platform using AI.
He said most of these capabilities are available in the company’s advanced subscription tier and described Appian’s approach as charging explicitly for AI in production. Tanjga said the average realized price for moving from the standard to the advanced tier is about a 25% uplift, and noted that Appian previously disclosed that a quarter of its customers are paying for the advanced tier. He described the near-term focus as driving adoption and becoming the “trusted vendor” for customers’ first, second, and third AI use cases.
He also discussed a premium tier, which he said carries an additional 25% to 35% uplift and currently has a limited feature set, though a handful of customers are already paying for it. Tanjga said Appian plans to add more features to the premium tier as adoption progresses and modernization use cases expand.
On pricing, Tanjga described a “matrix” of models including per-user, per-app, enterprise agreements, and consumption options, alongside tier-based price increases. He emphasized that Appian is focused on “selling value,” pointing to an example discussed for the first quarter in which an aerospace manufacturer signed a seven-figure deal after Appian concluded it could help save the customer $60 million.
Tanjga said Appian’s execution has historically been less consistent on go-to-market than on product, and described a shift that began roughly two years ago to focus upmarket, including a reduction of the sales organization about 18 months ago to concentrate on larger opportunities. He said commercial North America saw improved performance following leadership and process changes implemented at the beginning of 2025, citing what he called the best commercial North America growth in more than three years.
In the federal business, Tanjga called DOGE an “unequivocal positive,” saying it increased emphasis on efficiency, direct vendor engagement, and automation. He also referenced a framework agreement with the U.S. Army for up to $500 million over 10 years, describing it as a “hunting license” to pursue additional use cases.
On profitability, he said Appian has shifted rapidly from negative 8% EBITDA margin to positive 11%, and that in his tenure the company guided to 7% EBITDA margin at the midpoint but finished the year at 11% while keeping operating expenses flat. Tanjga said improved go-to-market productivity has “earned the right to grow moderately,” with investment planned in go-to-market and overseas R&D while still targeting margin expansion.
He also said Appian was GAAP profitable last year, citing $1.2 million of GAAP net income, and highlighted a focus on limiting dilution. Tanjga said stock-based compensation as a percent of revenue is less than half of the average company of similar size. He noted Appian authorized a $50 million buyback, framing it as the start of a consistent capital return approach and saying it essentially offsets dilution given the company’s lower issuance.
In discussing cloud growth, Tanjga said the company’s confidence for 2026 is supported by the timing of new business that was “back-end loaded,” currency dynamics, and the strength of the pipeline and sales execution.
Appian Corporation is a global technology company specializing in low-code automation platforms designed to streamline business processes. Founded in 1999 by Matt Calkins, the company provides an integrated suite of tools that enables organizations to build enterprise applications and workflows rapidly with minimal hand coding. The platform combines process management, robotic process automation (RPA), artificial intelligence (AI) capabilities and data integration into a single environment, allowing businesses to accelerate digital transformation initiatives.
The core offering, the Appian Low-Code Platform, empowers users—ranging from professional developers to business analysts—to visually model, design and deploy applications that can automate complex operations, orchestrate tasks across systems, and deliver real-time analytics.
