5 Ways Government Contractors Can Tackle Digital Transformation

Ronda Cilsick
CIO
Deltek

The growing adoption of efficiency-boosting technologies like artificial intelligence (AI) and machine learning (ML) helps counteract staffing shortages, rising labor costs, and talent gaps, while giving employees more time to focus on strategic projects. This trend is especially evident in the government contracting sector, where, according to Deltek's 2024 Clarity Report, 34% of GovCon leaders rank AI and ML in their top three technology investment priorities for 2024, above perennial focus areas like cybersecurity, data management and integration, business automation and cloud infrastructure.

Operating within tight profit margins and complex supply chains, government contractors face significant pressure to boost efficiency, save time, and reduce costs with automation. But with unique barriers to technology adoption, from economic constraints to regulatory hurdles, IT leaders can't rush investments in digital transformation.

Despite these challenges, digital transformation is not out of reach for this industry. By taking a measured approach and fostering a culture of innovation, IT leaders will be empowered to unlock the efficiency and cost-saving benefits of AI and ML.

Navigating Unique Hurdles to Tech Adoption

Digital transformation initiatives present challenges and considerations for any organization. However, tech adoption can be difficult for government contractors — particularly for those that are risk-averse due to the imperative for safety standards on mission critical programs, long product development lifecycles and reliance on legacy systems.

Inflation and high labor costs place additional pressure on the success of technology investments. Moreover, government contractors must navigate stringent regulatory requirements that can complicate the adoption of new technologies.

For example, managing sensitive data from government entities requires meticulous planning and execution to ensure compliance with data security standards. This complexity can lead to apprehension among leaders regarding the time and effort required to implement new software — and onboard and train both employees and external parties.

Given these constraints, it's not surprising that IT leaders who work at government contracting firms rank implementing new software systems among their top three challenges. But by understanding these obstacles, you can implement smart strategies to overcome them and pursue digital transformation.

Tips to Kickstart Your Digital Transformation Efforts

While AI plays a key role in optimizing internal processes and improving decision-making, you can't rush investments in AI — especially in the highly regulated government contracting space.

Successful digital transformation initiatives require a measured approach in which you:

1. Address cultural factors: While technology adoption is a critical aspect of digital transformation, these solutions cannot succeed without the people who implement, maintain, and provide education and training to enable their use. Effective change management and employee involvement in digital transformation can help secure employee buy-in and mitigate fears about changes in processes and technologies.

It's just as important to foster a culture of innovation in which failure is part of the learning process. Room to explore new ideas and learn from their mistakes offers space for employees to innovate and determine how AI fits into the organization's broader technology strategy.

2. Prioritize agility: IT governance is crucial to ensuring stability and compliance when integrating new technologies. But if governance is too rigid it becomes increasingly difficult to efficiently respond to market changes as technology advances.

Consider taking a "just enough" approach that focuses on implementing only the necessary amount of oversight and control to remain compliant without creating unnecessary bureaucracy. For example, instead of requiring a one-size-fits-all approval process to approve projects and digital transformation initiatives, take a tiered approach, establish clear guidelines and delegate approvals to designated teams to enable quick decision-making within those parameters.

3. Focus on data quality: AI-powered tools are only as effective as the data that trains them, making data quality a must-have foundation for any AI investment. To enhance your AI initiatives, prioritize the implementation of technologies and processes that improve data quality, like data governance frameworks and data cleaning software.

You can also increase your chances of earning leadership buy-in by identifying solutions that do more than simply automate. For example, some platforms integrate compliance management with project management and financial tools, offering a clear ROI while ensuring regulatory compliance.

4. Start small and scale: Digital transformation doesn't — and shouldn't — happen overnight. Start by identifying areas of the business that heavily depend on manual processes and could see significant improvements from technology integration.

For instance, while 58% of government contractors use enterprise resource planning (ERP) systems and accounting software, nearly the same percentage (55%) still use spreadsheets to manage financial operations. Digitizing and automating routine tasks in your financial operation enhances productivity and serves as a practical starting point to experiment with automation, paving the way for further improvements.

5. Document progress: Your ability to scale digital transformation efforts hinges on robust documentation. Make sure to set measurable goals before deploying new technology solutions so you can monitor and log progress via metrics like percentage reduction in invoice processing time or increase in on-time project delivery rates.

Use these findings to inform future decision-making and guide future initiatives. Additionally, consider asking leaders involved in these projects to share success stories and use cases across the organization to foster adoption and build confidence among employees.

AI Is Here to Stay, So Do It Right

Don't let the current hype around AI lead to rushed investments — these technologies are here to stay. It is crucial to not only prepare your data and people for AI, but also to begin with small initiatives, scale gradually, and document your progress along the way. A systematic approach to digital transformation and AI adoption can help you overcome cultural, regulatory, and technological barriers and determine how new technologies can optimize business processes and decision-making.

The result? You gain the ability to harness the full potential of AI and drive meaningful, sustainable change.

Ronda Cilsick is CIO of Deltek

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5 Ways Government Contractors Can Tackle Digital Transformation

Ronda Cilsick
CIO
Deltek

The growing adoption of efficiency-boosting technologies like artificial intelligence (AI) and machine learning (ML) helps counteract staffing shortages, rising labor costs, and talent gaps, while giving employees more time to focus on strategic projects. This trend is especially evident in the government contracting sector, where, according to Deltek's 2024 Clarity Report, 34% of GovCon leaders rank AI and ML in their top three technology investment priorities for 2024, above perennial focus areas like cybersecurity, data management and integration, business automation and cloud infrastructure.

Operating within tight profit margins and complex supply chains, government contractors face significant pressure to boost efficiency, save time, and reduce costs with automation. But with unique barriers to technology adoption, from economic constraints to regulatory hurdles, IT leaders can't rush investments in digital transformation.

Despite these challenges, digital transformation is not out of reach for this industry. By taking a measured approach and fostering a culture of innovation, IT leaders will be empowered to unlock the efficiency and cost-saving benefits of AI and ML.

Navigating Unique Hurdles to Tech Adoption

Digital transformation initiatives present challenges and considerations for any organization. However, tech adoption can be difficult for government contractors — particularly for those that are risk-averse due to the imperative for safety standards on mission critical programs, long product development lifecycles and reliance on legacy systems.

Inflation and high labor costs place additional pressure on the success of technology investments. Moreover, government contractors must navigate stringent regulatory requirements that can complicate the adoption of new technologies.

For example, managing sensitive data from government entities requires meticulous planning and execution to ensure compliance with data security standards. This complexity can lead to apprehension among leaders regarding the time and effort required to implement new software — and onboard and train both employees and external parties.

Given these constraints, it's not surprising that IT leaders who work at government contracting firms rank implementing new software systems among their top three challenges. But by understanding these obstacles, you can implement smart strategies to overcome them and pursue digital transformation.

Tips to Kickstart Your Digital Transformation Efforts

While AI plays a key role in optimizing internal processes and improving decision-making, you can't rush investments in AI — especially in the highly regulated government contracting space.

Successful digital transformation initiatives require a measured approach in which you:

1. Address cultural factors: While technology adoption is a critical aspect of digital transformation, these solutions cannot succeed without the people who implement, maintain, and provide education and training to enable their use. Effective change management and employee involvement in digital transformation can help secure employee buy-in and mitigate fears about changes in processes and technologies.

It's just as important to foster a culture of innovation in which failure is part of the learning process. Room to explore new ideas and learn from their mistakes offers space for employees to innovate and determine how AI fits into the organization's broader technology strategy.

2. Prioritize agility: IT governance is crucial to ensuring stability and compliance when integrating new technologies. But if governance is too rigid it becomes increasingly difficult to efficiently respond to market changes as technology advances.

Consider taking a "just enough" approach that focuses on implementing only the necessary amount of oversight and control to remain compliant without creating unnecessary bureaucracy. For example, instead of requiring a one-size-fits-all approval process to approve projects and digital transformation initiatives, take a tiered approach, establish clear guidelines and delegate approvals to designated teams to enable quick decision-making within those parameters.

3. Focus on data quality: AI-powered tools are only as effective as the data that trains them, making data quality a must-have foundation for any AI investment. To enhance your AI initiatives, prioritize the implementation of technologies and processes that improve data quality, like data governance frameworks and data cleaning software.

You can also increase your chances of earning leadership buy-in by identifying solutions that do more than simply automate. For example, some platforms integrate compliance management with project management and financial tools, offering a clear ROI while ensuring regulatory compliance.

4. Start small and scale: Digital transformation doesn't — and shouldn't — happen overnight. Start by identifying areas of the business that heavily depend on manual processes and could see significant improvements from technology integration.

For instance, while 58% of government contractors use enterprise resource planning (ERP) systems and accounting software, nearly the same percentage (55%) still use spreadsheets to manage financial operations. Digitizing and automating routine tasks in your financial operation enhances productivity and serves as a practical starting point to experiment with automation, paving the way for further improvements.

5. Document progress: Your ability to scale digital transformation efforts hinges on robust documentation. Make sure to set measurable goals before deploying new technology solutions so you can monitor and log progress via metrics like percentage reduction in invoice processing time or increase in on-time project delivery rates.

Use these findings to inform future decision-making and guide future initiatives. Additionally, consider asking leaders involved in these projects to share success stories and use cases across the organization to foster adoption and build confidence among employees.

AI Is Here to Stay, So Do It Right

Don't let the current hype around AI lead to rushed investments — these technologies are here to stay. It is crucial to not only prepare your data and people for AI, but also to begin with small initiatives, scale gradually, and document your progress along the way. A systematic approach to digital transformation and AI adoption can help you overcome cultural, regulatory, and technological barriers and determine how new technologies can optimize business processes and decision-making.

The result? You gain the ability to harness the full potential of AI and drive meaningful, sustainable change.

Ronda Cilsick is CIO of Deltek

Related Links

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Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...