Adam Rykowski of OpenGov on How Connected Data and AI Are Transforming Government ERP

For decades, ERP systems in government have primarily served as systems of record, managing financial transactions, budgets, workforce data, and operational information. But as public sector organizations face growing pressure to improve service delivery, increase transparency, and operate more efficiently, expectations around enterprise platforms are changing.

At the same time, advances in artificial intelligence are creating new opportunities to automate routine work, improve decision-making, and connect previously fragmented processes across government departments. Rather than functioning solely as administrative systems, ERP platforms are increasingly becoming operational environments that support execution, collaboration, and real-time action.

OpenGov is among the companies helping drive this shift through its AI-native Public Service Platform, which brings together ERP, workforce management, permitting, infrastructure, and asset management on a unified foundation. In this ERP News Q&A, Adam Rykowski, Chief Product Officer at OpenGov, shares his perspective on the future of AI-enabled government operations, the importance of connected data, and why ERP is evolving into a system of action rather than simply a system of record.

Reimagining ERP for Government Operations

Q: ERP in the public sector has traditionally been seen as a system of record. How is that definition changing as platforms become more operational and execution-focused?

A: ERP in government has historically been viewed as a system of record, but the reality is most ERP implementations in government end up as multiple systems not connected consistently, making it difficult to use the data in their day-to-day work. What we’ve heard consistently from customers is that disconnected systems create friction across finance, operations, assets, permitting, and workforce management, and agencies are increasingly asking for a better system that helps them execute. Our focus has been building a connected platform that brings together every function involved in running a city, county, or state agency on a shared system, with AI working alongside public servants.

What It Means to Be AI-Native

Q: OpenGov is positioning its platform as “AI-native.” What does that mean in practical terms for government agencies beyond adding AI features on top of existing systems?

A: For us, AI-native means AI is embedded into the core of the platform, not layered on afterward as a separate tool. Whether it’s AI Review in permitting, contract authoring and review, automation in ERP workflows, or AI-driven insights across finance and operations, the goal is the same: reduce repetitive manual work, improve accuracy, and help teams make faster, better-informed decisions while staying fully in control.

AI-native means AI is embedded into the core of the platform, not layered on afterward as a separate tool.

Why Government Needs a Unified Platform

Q: A key part of your announcement is the move toward a unified platform across finance, workforce, infrastructure, and permitting. What challenges are agencies facing today that make this level of integration necessary?

A: Governments have told us they are often dealing with fragmented systems that don’t communicate with one another. Finance, HR, permitting, asset management, and operations often operate in separate environments with different processes and different sources of truth. This creates inefficiency, slows decision-making, and makes it harder to align priorities across departments. That’s why we’re bringing ERP, HCM, permitting, and asset management together on a unified platform with a common data model to enable consistent workflows across departments.

Embedding AI Directly Into Daily Work

Q: OG Assist is embedded directly into workflows rather than existing as a separate tool. How does this change the way government teams interact with data and systems on a day-to-day basis?

A: Our goal is to make it as easy as possible to get started with AI. Embedding OG Assist directly into workflows changes AI from something employees have to seek out into something available inside the work they’re already doing. So much cognitive load goes into jumping between systems or manually searching for information. With OG Assist, teams can interact with their data in real time, surface insights faster, automate routine tasks, and focus more of their time on higher-value work. It also can be used to onboard new employees and teach teams the best practices for their jobs.

Balancing Automation and Accountability

Q: Many organizations are still navigating the balance between automation and control, particularly in regulated environments. How do you approach this in the context of AI-driven public sector operations?

A: No matter how advanced AI becomes, human judgment remains essential, especially in government, where decisions directly impact communities, public trust, and people’s daily lives. AI should support public servants, not replace accountability, oversight, or decision-making responsibility. At the end of the day, people are ultimately responsible for the actions taken when AI is used, which is why we take responsible AI deployment very seriously. That means building systems grounded in transparency, security, permissions, and human review so governments can use AI in practical, trustworthy, and accountable ways.

Solving the Government Data Fragmentation Problem

Q: Data fragmentation has long been a challenge in government systems. How does a shared data foundation change decision-making at both operational and leadership levels?

A: Government work ultimately revolves around workflows, approvals, compliance, budgeting, permitting, procurement, service delivery, and more. The challenge is that many agencies still rely on disconnected systems, which causes those workflows to break down across departments and limits visibility into what’s actually happening operationally. Users introduce workarounds and manual steps, and this data fragmentation makes it nearly impossible to introduce AI into these workflows since AI needs good data as context to be effective.

Additionally, leadership often struggles to get a complete picture of finances, infrastructure, workforce capacity, and community priorities in one place. A connected platform built on a common data foundation helps bring those functions together, giving teams greater visibility, consistency, and confidence in how they make decisions and execute work.

From Reactive to Predictive Asset Management

Q: The expansion into enterprise asset management introduces more proactive planning capabilities. How important is this shift from reactive to predictive operations in the public sector?

A: Managing public assets is one of the most critical and expensive responsibilities government agencies have because it impacts everything from roads and utilities to parks, fleets, and public facilities. Yet in many organizations, these operations are owned across separate departments, forcing teams to make high-stakes infrastructure decisions reactively rather than strategically.

OpenGov has been helping agencies manage infrastructure and public assets for years, and we’ve consistently seen that governments need better visibility, coordination, and long-term planning capabilities to keep pace with growing demands and aging infrastructure. That’s why the shift from reactive to predictive operations is so important. Agencies are under increasing pressure to do more with limited resources while making smarter, more defensible taxpayer investments.

Customers discuss how OpenGov Enterprise Asset Management is helping them move toward a more proactive operating model. Capabilities like Scenario Builder and Work Planner allow agencies to evaluate tradeoffs across asset classes, connect long-term capital planning to day-to-day execution, and make more informed operational and financial decisions before problems become emergencies.

Accelerating Permitting with AI

Q: Permitting is often cited as one of the most complex and time-consuming government processes. Where are you seeing the most immediate impact from AI in this area?

A: We’re transforming the entire permitting and licensing department using AI to make it faster to issue permits. The immediate impact from AI comes from streamlining manual review work, catching issues earlier in the process, and reducing repetitive tasks. Customers have described how time-intensive reviewing building plans can be and how difficult it has historically been to standardize intake and review processes. AI Review helps flag common issues earlier, reduce back-and-forth, improve consistency, and give staff more time to focus on areas that truly require human judgment.

Overcoming Barriers to AI Adoption

Q: From your perspective, what are the biggest barriers preventing agencies from moving toward more connected, AI-enabled operational platforms?

A: One of the biggest barriers is that change itself can feel risky for government agencies, especially after years of difficult implementations, disconnected vendors, and technology that created more frustration than trust. Many teams have been through modernization efforts that overpromised and underdelivered, which naturally makes organizations cautious.

But the reality is that standing still is often the bigger risk. Community expectations continue to rise, workloads are increasing, and legacy systems make it harder for agencies to make informed decisions efficiently and coordinate across departments. What we’ve consistently seen is that agencies want to embrace transformation, but the technology must be practical, collaborative, and built alongside them rather than imposed on them.

The same is true with AI. Adoption happens when employees see the technology helping them do their jobs more effectively, improving visibility and execution, while still keeping human judgment, accountability, and oversight at the center of every decision. We have built OG Assist with these principles in mind to make it easy to use and focused on solving real-world problems.

The Future of ERP in Government

Q: Looking ahead, how do you see the role of ERP evolving in government environments over the next three to five years, particularly as AI becomes more embedded in decision-making and execution?

A: We see ERP evolving from a standalone back-office system into a core component of the government operating system. This is why we have built the Public Service Platform. As AI becomes more embedded into workflows and decision-making, government officials will be able to find better, faster, and more innovative ways to serve their communities.

The value will come from connected systems and a shared data foundation, not disconnected tools layered on top of legacy software. Governments need finance, workforce, infrastructure, permitting, procurement, and service delivery operating together in one unified system so leaders can make faster, more informed decisions with greater visibility across the organization.

Governments need finance, workforce, infrastructure, permitting, procurement, and service delivery operating together in one unified system so leaders can make faster, more informed decisions with greater visibility across the organization.

In that model, ERP becomes part of the operational backbone that powers execution across government and accelerates AI adoption, helping agencies automate routine work, improve coordination, and deliver services more effectively, while still ensuring human judgment, accountability, and oversight remain central to every decision.

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About Adam Rykowski

Adam Rykowski serves as Chief Product Officer at OpenGov, where he leads product strategy, innovation, design, and execution across the company’s portfolio. He brings more than 20 years of product leadership experience spanning high-growth startups and public technology companies.

Prior to OpenGov, Rykowski served as VP of Product at OneTrust, helping guide the company’s evolution from a product-focused organization into a platform business. He also spent a decade at VMware following its acquisition of AirWatch, where he was the company’s first product manager and played a key role in its growth from startup to enterprise scale. He holds a degree in Industrial and Systems Engineering from Georgia Tech and is passionate about building products that deliver meaningful impact for customers and communities.