The recent ServiceNow Knowledge Conference highlighted a major strategic shift in how the company is engaging with its developer and partner ecosystem through the Build Partner Program and its AI agent-driven platform vision.

In the following article, I will summarise and provide additional insights and my opinion on the topics covered during the ServiceNow Partner Panel, incl.

• ServiceNow Store
• AI Agents & Agentic Framework
• Developer Tools Modernization
• Build Program Investment
• AI Developer Incentives
• Verticalization & Industry Focus
• Partner Testimonials

The discussion underscored ServiceNow’s commitment to transforming its platform into a scalable, AI-powered ecosystem with deep partner integration. Let’s start.

ServiceNow Store Evolution

In recent years, ServiceNow has made significant strides in transforming how businesses build, discover, and deploy digital solutions on its platform. Nowhere is this more evident than in the evolution of the ServiceNow Store. It is an initiative that has quietly grown from a basic distribution mechanism into a powerful, AI-enhanced marketplace that drives customer engagement, partner growth, and ecosystem scalability.

The panel participants shared many details about how the Store is reshaping the future of enterprise applications. Their comments reveal not just a product redesign, but a strategic pivot toward a more intelligent, responsive, and opportunity-rich platform. So, if you are aiming to build a successful product and generate revenue from it, consider the valuable insights.

The store has become a central, intelligent marketplace, now designed for discovery, transaction, and lead generation. With over 5,000 App and AI marketplace leads and a 12% conversion rate, it’s becoming a significant commercial engine.

• The store has evolved from a simple distribution tool into a front-door marketplace for AI agents, apps, and industry solutions.
• It now offers a revamped UI/UX, SEO visibility, and new partner-focused features like lead tracking and the “Contact Seller” button.
• Integration with partner sales pipelines enables lead generation directly from the store with a 12% lead-to-order conversion rate.

What started as a catalog of apps has now become a cornerstone of ServiceNow’s go-to-market strategy. “This is not just a redesign, this is a complete, complete rebuild from the ground up,” explained a product manager from the Store team. ServiceNow improved the website and built a new frontend with performance and searchability in mind. As a result, the apps have better search results in the common search engines.

With a renewed focus on developer tools and customer experience, the Store is now poised to serve as the foundation for ServiceNow’s expansive ecosystem strategy. One of the most ambitious changes is the positioning of the Store as a marketplace for AI agents. “You’re seeing our brand-new AI Agent marketplace,” said one demo presenter. “This is specifically for our partners who are building the agents”.

AI is no longer peripheral to the Store. It takes a central role, incl. new categories, personalized agent recommendations, and an intelligent browsing experience. It has been designed not only to serve customers but also to showcase the depth of partner-built solutions. As one panel participant summarized, “We are building a store that’s designed for scale… a destination for transformation, with applications that solve for every use case, for every team, and for every industry”.

The redesign has also unlocked tangible business benefits for partners. The launch of a streamlined lead generation process – activated through a simple “Contact Seller” button – has led to a measurable uptick in partner engagement. “Over 5,000 leads have been generated from the store… We’ve gotten a 12% conversion rate,” one presenter noted.

What’s relevant for partners isn’t the technical or design improvements but a commercial breakthrough where you can leverage the ServiceNow Store as one of the sales and lead-generation channels. One partner shared, “Since this new store launched… we’ve already had three leads. We have an active opportunity with a deal in Saudi Arabia… We would have never had the opportunity if you all hadn’t launched that new leads portal”.

Behind the scenes, the Store’s rebuild was also a proving ground for ServiceNow’s new generation of developer tools. Using the same tools provided to the ecosystem such as the Fluent language, VS Code-based IDE, and SDK integrations. The internal Store team validated their efficiency firsthand so they can provide more value faster incl. new updates, review and certification process, lead generation and tracking. ServiceNow is also building its apps faster, cleaner, and more collaboratively. And this is a signal to all other developers to shift toward a more modern, industry-aligned workflows.

The tone of the panel was one of optimism and urgency. There’s clear recognition that the Store is no longer an optional feature. It’s the gateway through which customers, partners, and innovations meet with a better experience for ServiceNow, partners, and mutual clients. This is an industry-leading approach, and it might be a game changer in the next couple of years. As the platform marches toward its billion-dollar ecosystem vision, the ServiceNow Store stands not just as a marketplace but as a catalyst for customer success, partner opportunity, and the future of AI in enterprise software.

By the way, we at Teiva Systems built and certified dozens of App Engine applications for the ServiceNow Store for our partners with strong, innovative ideas but lacking technology experience, delivery capabilities, and architectural expertise. We take over and get things done while clients focus on the product idea, go-to-market, sales, and partnerships. An up-and-ready application will be published in a few months, fully aligned with customer expectations and ServiceNow Store guidelines. You don’t just get an app, you get an assurance that, from a technical and governance perspective, you stay compliant and within budget.

AI Agents & Agentic Framework

Where the Store provides the front door to the ecosystem, the ServiceNow Agentic Framework represents the engine behind it. With this framework, partners and developers can move beyond static applications to deliver intelligent, interactive agents that understand context, automate decisions, and scale across industries, departments, and use cases. The new Store and the Agentic Framework are thus two sides of the same transformation: one connects solutions to customers, the other redefines how those solutions are built. Together, they represent ServiceNow’s next-generation approach to enterprise automation at scale.

This framework marks a strategic leap in usability and scalability for ServiceNow and was a core theme in the panel discussion at the Knowledge Conference. This offering opens the door for rapid solution delivery across verticals using the new AI Agent Studio and pseudocode-driven design tools.

• A major emphasis was placed on Agentic AI – where agents can be created with minimal code using natural language instructions.
• ServiceNow’s AI Agent Studio and tools like pseudocode-driven workflows make it easier for developers to build complex flows without coding.
• The AI vision centers on scaling from tens to thousands of agents, which can only be achieved through partner ecosystems.

The Agentic Framework centers around a key realization: traditional business logic built in rigid flows and scripts limits the pace at which automation can evolve. The workflows are to constrained, fixed. Not able to dynamically react and act in variety of contexts. To break this ceiling, ServiceNow is enabling developers to “coach” the system using pseudocode, describing intent and rules in natural language, rather than hardcoding logic.

From Workflows to Agents: A Paradigm Shift

By placing intent at the center of workflow design, the Agentic Framework enables enterprises to focus on what outcomes they want to achieve, rather than how to write the code to achieve them.

“It’s the pseudocode that part of your computer science background you skipped over that becomes so important. That’s really the power of the agentic environment.”
— Steve Weinberg, Partner and ISV Team

The new Agentic AI-based systems can perceive their environment, reason about complex tasks, and act independently to achieve goals. Unlike traditional workflows that follow predefined paths, agentic AI systems can adapt to changing circumstances, learn from new data, and collaborate with other agents or humans to optimize outcomes.

According to Gartner, by 2028, 33% of enterprise software applications will incorporate agentic AI, a significant increase from less than 1% in 2024. This trend underscores the growing recognition of agentic AI’s potential to enhance efficiency, responsiveness, and innovation within organizations. And the shift is not isolated to ServiceNow only.

Organizations across various industries are exploring and adopting agentic AI to enhance their operations. For instance, companies like Accenture are deploying multi-agent systems in areas such as marketing, finance, and logistics, enabling AI agents to collaborate autonomously or with minimal human oversight. Other low-code platforms also introduced Agentic AI and AI workflows as part of their capabilities. Furthermore, the development of protocols like Agent-to-Agent (A2A) by Salesforce and Google aims to standardize communication between AI agents, facilitating more seamless integration and collaboration across different systems and platforms.

However, this transition also necessitates robust governance frameworks to manage the ethical, security, and operational challenges associated with autonomous systems. Organizations must invest in training, infrastructure, and policies to ensure the responsible and effective deployment of Agentic AI.

At Teiva Systems, we help you harness the full potential of ServiceNow’s Agentic AI capabilities with tailored consulting, design, and implementation services. Whether you’re exploring your first intelligent agent or scaling a multi-agent architecture across your enterprise, our AI expertise, platform knowledge, and process insight make us your ideal partner. Our customers profit from our deep expertise in enterprise process automation, solution delivery and support, and secure AI solutions. We provide GenAI solutions around automating incident and IT change management, discovery of employee perception, surveys, and clinical trials.

Pseudocode-Led Design: Business Logic in Natural Language

Panel participants also discussed the integration of pseudocode-led design into AI agent development as it signifies a paradigm shift in enterprise automation. It empowers a broader range of stakeholders to participate in the automation process, reduces development time, and enhances the adaptability of automation solutions. The automation becomes more accessible and scalable.

Also, the natural language is at the heart of the Agentic Framework as it provides the ability to design use cases and flow structures for developers and non-technicians. By understanding the natural language and the context, the platform better interprets this input to execute logic, invoke services, and guide agent behavior.

There was a live demo, where it was shown how an AI Agent reacts and processes an event using following capabilities:

• Collection of user input;
• Verification of eligibility (e.g., VIP status);
• Querying the user’s inventory on the fly;
• Adaption of agents behavior based on user roles;
• All without a single line of code;

This approach vastly lowers the technical barrier to entry for domain experts, accelerates iteration, and simplifies documentation.

In summary, pseudocode-led design is not just a technical innovation; it’s a strategic enabler that aligns automation with business goals, fosters inclusivity in development, and positions organizations to thrive in an increasingly automated world.

Context-Aware Orchestration with Short-Term Memory

Agents in the ServiceNow ecosystem are stateful and contextually aware. Each workflow is governed by an orchestrator that maintains short-term memory across steps and agents, allowing it to make decisions and pass information dynamically. You simply don’t have to tell it where the data is or how to get to it. It remembers that it was created by another agent and just passes it along. This eliminates the need for architects to hardcode every handoff or data transformation. Instead, they can describe expected inputs and outputs, and the platform handles flow continuity. Closely mimicking human-like reasoning and decision-making processes, and handling more complex tasks with more autonomy and adaptability.

We see the enterprise sector witnessing a significant shift towards the adoption of intelligent AI agents equipped with context-aware orchestration and short-term memory. According to recent industry analyses, businesses are increasingly deploying AI agents that can operate autonomously, adapt to changing contexts, and collaborate with other agents or human users to achieve complex objectives.

For instance, companies like Accenture are pioneering multi-agent systems that leverage these capabilities to enhance marketing, finance, and logistics operations. These systems enable AI agents to collaborate autonomously, reducing the need for human oversight and increasing operational efficiency. Furthermore, protocols like the Model Context Protocol (MCP) by Anthropic facilitate standardized communication between AI agents for seamless integration and collaboration across different systems and platforms.

We can expect AI agents to become more proficient in handling complex tasks, collaborating with other agents, and making decisions with minimal human intervention, and you can develop new agents to assist in your daily work. This evolution will lead to more efficient and responsive enterprise operations and service management, as we described in earlier blogs.

Agent Modularity and Use Case-Driven Architecture

After evolving the platform capabilities and the introduced framework, the panel discussed how to effectively design, deploy, and scale AI solutions. Everyone agreed, that organisations must build modular agents and design architectures driven by use cases. This approach emphasizes the creation of specialized, interoperable agents tailored to specific business functions, enabling more agile and efficient operations.

The shift towards modular AI architectures is gaining momentum across industries. Organizations are recognizing the benefits of deploying specialized agents that can operate autonomously yet collaborate seamlessly within a broader system (also stated in the article by the Wall Street Journal). This modular approach allows for:

• Consistent Scalability through an easily creating or enhancing agents without overhauling entire systems
• Higher Flexibility by tailoring agents to specific tasks or departments
• Secure Resilience through isolating issues within individual agents to prevent system-wide disruption (but don’t forget following the guidlines)

Companies like Accenture are pioneering multi-agent systems, deploying them in areas such as marketing, finance, and logistics. Their “Trusted Agent Huddle” enables agent interoperability with partners like AWS, Google, and Microsoft .

The multi-system agent systems, like that one offered by ServiceNow agent orchestrator, will rely on agents configured as discrete entities, each with:

• A name
• A role
• A natural language instruction set

These agents plug into use case objects—textual representations of what needs to be done and why.

“This flow is defined as a use case. The use case describes the steps, the expectations in each step, and what comes in and out of them to give the orchestrator the ability to understand what the flow is.”, as pone of the panelists stated.

This architectural model introduces a layer of modularity rarely seen in low-code platforms. Each agent becomes a reusable unit, scoped by domain responsibility, and controlled through simple configuration. It will be ideal for large enterprises needing composable automation while ensuring standardisation, autonomy, and scalability.

Role-Aware Behavior and Adaptive Logic

To be able to develop even more advanced and autonomous systems, you will need to go beyond pre-configured solutions. ServiceNow and partners discussed what is required and touch the capabilities like a role-aware behavior and an adaptive logic.

Role-Aware Behavior refers to an AI agent’s ability to comprehend and act according to its designated role within an organization. By understanding its purpose, objectives, and interaction protocols, an AI agent can tailor its actions to align with organizational goals and user expectations. For instance, in ServiceNow’s AI Platform, roles are defined in natural language, allowing agents to interact seamlessly with users and systems.

Adaptive Logic pertains to an AI agent’s capacity to modify its behavior based on real-time data and contextual cues. Adaptive logic enables agents to respond to dynamic environments, learn from new information, and adjust their decision-making processes accordingly. Such adaptability is crucial for tasks requiring nuanced judgment and responsiveness.

Agentic flows will adapt automatically based on the user or system context. A single process will behave differently across user types or business rules. In the demo shown during the panel, a VIP user received additional options and privileges compared to a standard user, without duplicating workflows.

“Because he’s a different type of user, the flow changes… he’s a VIP, so he’s going to get more shows that he can access.”

This makes it easier for architects to implement policy-driven logic that’s adaptable and governed centrally.

Zero-Code, Maximum Governance

By removing scripting from the equation, the Agentic Framework introduces a new level of governance and transparency. Business logic is visible, auditable, and editable without relying on scarce developer resources.

Zero-Code, Maximum Governance is an emerging paradigm in enterprise automation that combines the accessibility of zero-code platforms with robust governance frameworks. This approach empowers non-technical users to develop applications and automate workflows without writing code, while ensuring that these developments adhere to organizational policies, compliance standards, and security protocols.

Zero-Code Platforms enable users to create applications through visual interfaces, utilizing drag-and-drop features and pre-built components. This democratizes application development, allowing business users, often referred to as “citizen developers,” to address their specific needs without relying on IT departments.

Maximum Governance ensures that while application development is decentralized, it remains within the boundaries of organizational standards. This includes implementing role-based access controls, audit trails, data security measures, and compliance with industry regulations.

“I don’t even have to have some place I’m putting these tickets from… it’s all described in natural language.”

Enterprise teams can now deploy compliant, version-controlled agents without the traditional bottlenecks of app dev or script review. To avoid bottlenecks and technical debt and to successfully adopt a “Zero-Code, Maximum Governance” approach, teams should consider the following strategies:

1. Establish clear policies and guidelines for application development, including approval processes, data handling, and security protocols.
2. Select the right platform (zero-code) that offers built-in governance features such as user management, audit logging, and compliance.
3. Training and support rograms will educate citizen developers on best practices and the importance of adhering to governance policies.
4. Monitor and review systems will track application usage and compliance, allowing for continuous improvement and risk mitigation.

The panelists agreed that by adopting “Zero-Code, Maximum Governance,” enterprises can foster a culture of innovation while maintaining control and oversight, positioning themselves for success in an increasingly digital landscape.

Build Program Investment

ServiceNow is repositioning its Build Program from a side initiative to a core growth strategy. The company has set a goal of a $1 billion ecosystem by 2030, supported by exclusive incentives and streamlined onboarding for partners.

• ServiceNow is doubling down on its Build Partner Program, aiming for a billion-dollar ecosystem by 2030.
• The company emphasized simplifying the go-to-market, making partner engagement more strategic, and improving field/partner alignment.
• Feedback loops from partners are actively influencing product and roadmap decisions, not just GTM efforts.

ServiceNow invested heavily in the partner team. In a year, the organisation grew from six to thirty people, including business development, partner SAs, and GTM specialists.

Partner Managers (PAMs) will continue to be the primary point of contact for partners, with increased regional and industry specialization. Having more PAMs will mean better support for partners and faster execution of pre-sales and sales initiatives.

Industry Business Development Leads focus on vertical-specific opportunities and will align partner apps with ServiceNow’s industry GTM strategy. An important function to ensure partners develop products that really matter and do not miss clients’ expectations.

Horizontal Business Development Leads support cross-industry and core platform innovation use cases. It is a critical success factor for ServiceNow and ISVs to align the Store products with ServiceNow employee workflows, ITSM, and ESG.

To make the certification and technical onboarding of ISVs and their Store Apps more smoothly, Partner Solution Architects (Partner SAs) were introduced. The will help partners to scope and design solutions better aligned with ServiceNow architecture and optimize app architecture.

Moreover, Certification and Platform Enablement Resources have been extended. Dedicated team members will help partners speed up app reviews, testing, and Store readiness.

This expansion reflects a shift from a reactive, lightly resourced support model to a proactive, co-innovation-focused partner strategy. ServiceNow is positioning the Build Program team as a core driver of product expansion and revenue growth.

Developer Tools Modernization

ServiceNow invests into the developer tools and technical platform capabilities for better experience and higher productivity. They introduced modern development tools including the new Fluent language, a native VS Code-based IDE, CLI/SDK support. All aimed at increasing developer productivity and collaboration.

Fluent is a typed declarative language designed for app development on ServiceNow. It automates application creation and deployment, enables better code quality, facilitates collaboration, and supports both low-code and pro-code developers.

Pro-code developers can use VS Code-Based IDE. A developer-friendly, modern interface allowing familiar workflows, syntax highlighting, metadata navigation, and fast ramp-up. For managing app lifecycles with modern tooling (e.g., npm), dependency management, and seamless instance sync, you can use CLI and SDK. ServiceNow becomes even more accessible to common JavaScript developers who can get onboarded to the ServiceNow platform quickly and start contributing productively due to familiar tools.

These tools dramatically reduce onboarding time, enhance collaboration, and streamline testing using built-in automation. Tasks like API creation and table design that once took hours could be done in minutes.

Also, here is an insight from the backstage: The ServiceNow Store team uses ATF extensively for testing applications. The goal is to improve and speed up quality assurance and test-driven development.

We see that ServiceNow is investing heavily in the ISV developer experience, indicating a sustained commitment to partner success and letting the entire ecosystem grow faster.

AI Developer Incentives

Not only technical innovations were announced, but also an initiative to incentivise creation and publishing of Agentic AI solutions and apps.

The first-ever AI developer incentives program dedicated to ServiceNow Build partners is a strategic milestone in aligning ecosystem growth with AI acceleration. And those who lead will be rewarded. The program’s core offering is a 7% credit reinvestment reward. This incentive is designed for partners who are building AI-powered solutions (particularly agents) on the Now Platform.

“This is a 7% credit reinvest reward that you’re going to be able to reinvest back into your business, hopefully fueling investor growth. This is about rewarding innovators and those of you who are literally leaning in and leading from the front.”

The incentive mechanism enables partners to offset platform costs, fund additional AI development, or expand go-to-market efforts as early builders. And this makes totally sense, after two years of GenAI hype with low to no really big solutions in enterprise space. ServiceNow actually recognises the urgency of seeding the AI landscape with purpose-built, enterprise-grade agents. And even more: we are talking not about tens of agents, not even hundreds, but thousands of agents.

This scale imperative comes at a time when partners are being asked to go beyond dashboards and RPA into adaptive, agentic architectures. The incentives serve as an accelerator to this evolution. Both strategically and tactically.

What does ServiceNow incentivises?

The program is just a beginning, because what ServiceNow is actually tries to build another category within ServiceNow Store, but a new, a better ecosystem… designed for AI, for apps, for agents. The program at this stage targets especially:

• Development of GenAI-based applications and agents in Agent Studio.
• Adoption of ServiceNow’s new AI toolkits, such as the AI Orchestrator and Agent Fabric.
• Marketplace listing and commercial success via the ServiceNow Store.

These incentives are tightly integrated with ecosystem-wide goals, including doubling the number of production-grade agents and unlocking new vertical-specific use cases.

Teiva Systems already started building ServiceNow-based AI solutions for and with our partners. After multiple iterations we know possibilities and limitations of the platform and can guide you from the idea, to design, implementation, deployment and continuous improvement of your first Agentic AI apps.

Strategic Implications for Build Partners

ServiceNow wants to proliferate agents. This is how they see partners can win:

• Lower Risk, Higher Return for partners through the reinvestment credit helps de-risk early AI investments for partners, especially startups and mid-size ISVs.
• Those who act now can establish market leadership and reap early marketplace visibility, thanks to ServiceNow’s promotional focus.
• The incentive reinforces that partners (not just internal product teams) are central to ServiceNow’s generative AI go-to-market.

The feedback from panel participants and the audience was one of optimism. Some attendees expressed a desire to better understand the criteria for qualification and redemption mechanics of the 7% incentive. While other asked about the timeline for the incentive and how does it apply to early-stage builds versus published store apps.

Panelists suggested that those already building with AI Agents or enrolled in Agent Studio were well-positioned to benefit immediately. Just get things done. If you want a guidance and support. We have experience, capabilities, ressources and all required tools to start building Agentic AI on Now platform.

Verticalization & Industry Focus

ServiceNow is emphasizing sector-specific solutions and urging partners to help extend the platform into underserved verticals and sub-sectors. This is seen as critical to becoming the AI platform for business transformation. So-called “vertical” solutions address specific industry needs, such as healthcare, financial services, telecom, or physical security. Rather than offering generic tools, ServiceNow and its partners are now focusing on building deeply specialised applications that reflect industry nuances and compliance needs.

If we’re really going to be the AI platform for business transformation, you can’t do business transformation if you don’t know the business. You can’t know the business if you don’t know the industry sector. I think that’s table stakes.

ServiceNow isn’t just encouraging partners to specialize in a specific vertical. ServiceNow is also reengineering its enterprise market to map to core industries. This includes internal alignment across the field, sales, and product.

Panelists made clear that ServiceNow alone cannot cover every sub-sector. They need partners and clients hat co-invest, co-develop, co-own this kind of products. Currently, only five sectors are officially prioritized. That leaves more than 20+ open verticals (e.g., logistics, utilities, retail, public safety) as ripe opportunity areas for partners.

Partners incl. Teiva Systems demonstrated real-world applications during the panel included:

• Soul Machines brought experiential AI agents into ServiceNow, enabling verticalized use cases like clinical trials with natural, empathetic interaction layers
• FAIR created agents to manage threat detection, investigation, and reporting across a company’s physical premises. This showcases how industry pros are solving deep problems through the AI Agent Studio
• Another partner solution scanned 230,000 global data sources to perform continuous sanctions checks across millions of records for a major financial institution showcasing compliance automation at scale

Panelists emphasized that deep vertical knowledge is not something that can be quickly acquired. Success hinges on either long-term immersion in the field or strategic hiring. Partners must build quickly and secure their first deal as fast as possible, as time is ticking and more partners are in line. However, mostly at one’s own risk because there’s no guaranteed help from ServiceNow sales unless a partner demonstrates value and niche expertise.

We saw at the panel that verticalization is no longer a nice to have for ServiceNow. It is foundational to ServiceNow’s growth strategy. A massive opportunity for Build Partners. The message from leadership was clear: “We need you to own the white space.” Partners who bring deep domain expertise, build fast, and solve real-world industry problems will be the ones who define the next phase of ecosystem success.

Partner Testimonials

Throughout the panel, ServiceNow partners expressed a common sentiment: a deep appreciation for how the Build program has evolved and become a strategic growth enabler. Not just a transactional channel. Partners cited increased responsiveness, access to tools, meaningful collaboration, and a genuine shift toward partner-led innovatio and praised the platform’s scalability, data fabric, and speed-to-market capabilities. They noted dramatic improvements in onboarding, go-to-market support, and ecosystem alignment.

We’re serious and we joined and it’s been amazing… Then comes November, and now we’re doubling down on the importance of all of you in the groups… because we want to proliferate agents

Some newer partners shared how ServiceNow’s structure helped them go from idea to market rapidly. Even amid the complexity of aligning support, go-to-market, and product strategy.

The key takeaways from the this part of the panel are:

• Human Touch through authentic relationships and shared wins are seen as a core strength of the program.
• There is a need for Speed & Support. Startups and enterprise partners alike praised the access to resources and momentum created by ServiceNow teams.
• Partner feedback is actively shaping and influencing the ServiceNow platform roadmap.
• Partners believe ServiceNow is building something beyond a marketplace. It’s becoming an industry-defining AI platform.

Attending the ServiceNow Build Partner panel at Knowledge 2025 gave us firsthand insight into how seriously the platform is evolving and how fast. From the transformation of the Store into a lead-generation engine, to the introduction of agentic AI tools and incentives, it’s clear ServiceNow isn’t just improving features. It’s laying the foundation for a new category of enterprise AI. As a partner, our team walked away energized by the scale of opportunity and confident that with the right strategy, expertise, and speed, we can help shape this next chapter.

The ServiceNow Partner Panel at Knowledge 2025 showcased the company’s bold shift toward AI-first platform strategy, emphasizing intelligent agents, verticalized use cases, and deep partner collaboration. Major themes included the rebirth of the ServiceNow Store as a marketplace for agents and apps, the power of agentic AI frameworks and pseudocode-led design, as well as expanded developer tooling and incentives.

Partners shared success stories and aligned around a common message: the future of enterprise automation is modular, scalable, and built with partners at the center. And it was a pleasure to be a part of that round.

The window of opportunity for early movers in ServiceNow’s AI ecosystem is open—but it won’t stay that way for long. If you’re a partner or solution provider looking to build agentic applications, scale your Store offerings, or break into new verticals, now is the time.

At Teiva Systems, we’ve helped dozens of partners turn their product ideas into certified ServiceNow apps. Quickly, securely, and within budget. Ready to go from vision to launch? Get in touch with us.

Kostya Bazanov, Managing Director, May 21, 2025

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