Appian (NASDAQ:APPN) CFO Serge Tanjga said the company is focused on automating “mission-critical” processes for large enterprises and public sector clients, 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 applications or legacy solutions spanning 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 pull data from multiple systems.

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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 deployments. Tanjga said implementations are typically delivered by Appian or third-party partners, and customers pay “five to eight figures” for implementations. He characterized the work as difficult to implement and “very sticky,” stressing 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 dismissed investor concerns that AI could disintermediate process automation platforms, arguing that conversations with customers are less about replacing software and more about producing their first successful AI use case. He said companies are looking for AI that can work at scale within operational workflows with high precision, which he described as a challenge because AI is “probabilistic” and must operate within “deterministic” systems to deliver reliable results in areas such as onboarding, procurement and budgeting.

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As an example, he described a US insurance company that adopted Appian’s DocCenter, an AI-enabled document extraction product, for an early production use case handling 400,000 documents a year. He said it took several months to implement and fine-tune, and the customer is now discussing a second use case involving 1.2 million documents a year. Tanjga added that when customers are ready to adopt AI, Appian’s win rates are “significantly higher” than normal, which he sees as validation of Appian’s approach to using AI as “a node in the process” rather than replacing 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.

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He also highlighted the platform’s capabilities, such as security, auditability, compliance and certifications, arguing that they are difficult for AI tools to replicate and are essential for complex workloads that require high precision. Looking further, he said it’s hard to imagine 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 major verticals.

Tanjga said Appian’s AI capabilities have evolved from previous AI/ML integrations to a broader GenAI roadmap. He described a progression of offers:

• AI skills: Features that allow clients to call a large language model within a process to generate specific outputs.

• DocCenter: Document extraction with artificial intelligence, launched in late 2024, with production deployments in different industries.

• Agent Studio: A more autonomous “agent” offer, with the initial customers arriving in production.

• Composer/Modernization: Initial efforts to modernize legacy technology into a modern platform with AI.

He said most of these capabilities are available in the company’s advanced subscription tier, and described Appian’s approach as explicitly charging for AI in production. Tanjga said the average realized price to move from the standard tier to the advanced tier is about a 25 percent increase, noting that Appian previously disclosed that a quarter of its customers pay for the advanced tier. He described the short-term focus as driving adoption and becoming the “trusted provider” for customers’ first, second and third AI use cases.

He also talked about a premium tier, which he said carries an additional 25% to 35% increase 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 an “array” of models that include per-user, per-app, enterprise agreements and consumer options, along with tier-based price increases. He emphasized that Appian is focused on “sale value,” pointing to an example discussed in 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 about two years ago to focus on go-to-market, including shrinking the sales organization about 18 months ago to focus on larger opportunities. He said commercial North America saw improved performance following leadership and process changes implemented in early 2025, citing what he called North America’s best commercial growth in more than three years.

In the federal business, Tanjga called DOGE an “unequivocally positive,” saying it placed more emphasis on efficiency, direct vendor involvement and automation. He also referenced a framework agreement with the U.S. military 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 quickly moved from a negative 8% EBITDA margin to a positive 11%, and that during his tenure the company guided to a 7% EBITDA margin in half, but ended the year at 11% while keeping operating expenses stable. Tanjga said improved go-to-market productivity has “earned the right to grow moderately,” with planned investment in go-to-market and overseas R&D, though still targeting margin expansion.

He also said Appian was GAAP profitable last year, citing $1.2 billion of GAAP net income, and emphasized a focus on limiting dilution. Tanjga said stock-based compensation as a percentage of revenue is less than half the average for similar-sized companies. He noted that Appian authorized a $50 million buyback, framing it as the start of a consistent approach to returning capital and saying it essentially offsets the dilution given the company’s lower issuance.

Discussing cloud growth, Tanjga said the company’s confidence for 2026 is supported by the timing of “fund-loaded” new business, currency dynamics and pipeline strength 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 set of tools that enables organizations to quickly build business applications and workflows with minimal manual coding. The platform combines process management, robotic process automation (RPA), artificial intelligence (AI) capabilities and data integration into a single environment, enabling companies to accelerate digital transformation initiatives.

The core offering, the Appian Low-Code Platform, enables users from professional developers to business analysts to visually model, design, and deploy applications that can automate complex operations, orchestrate tasks across systems, and provide real-time analytics.

The article “Appian CFO: AI Increases Win Rates as Companies Automate Mission-Critical Workflows at TMT Conference” was originally published by MarketBeat.