Leverage Artificial Intelligence to Overcome Resource Constraints and Technical Debt

Empower your digital transformation through intelligent automation and innovation.

Analyst perspective

Build your federal organization's AI-driven efficiency.

Federal governments are faced with the dual challenges of resource constraints and growing technical debt, which hinder innovation, efficiency, and service delivery. Tight budgets often force departments to prioritize short-term needs over long-term improvements, leading to the accumulation of technical debt in the form of outdated legacy systems and infrastructure.

Traditional approaches to managing technical debt are often costly, time consuming, and fail to keep pace with the rapidly evolving technology landscape. As a result, agencies find themselves trapped in a vicious cycle of increasing maintenance costs and declining performance while they struggle to allocate resources for modernization efforts.

Artificial intelligence offers a game-changing solution to these challenges, enabling federal agencies to optimize resource allocation, automate processes, and make data-driven decisions to address technical debt while minimizing costs. Using AI-driven tools and techniques, agencies can assess and prioritize technical debt reduction efforts, forecast future costs, and identify cost-saving opportunities.

When carefully planned, executed, and supervised, AI becomes a strategic enabler for federal departments and agencies to overcome resource constraints, modernize systems, and ultimately deliver better services to citizens.

Paul Chernousov
Research Director, Industry
Info-Tech Research Group

Executive summary

Info-Tech Insight

Neglecting to harness the power of AI in tackling resource constraints and technical debt could lead to a stagnant, inefficient, and increasingly outdated public sector, jeopardizing the government's ability to serve its citizens effectively.

Leverage this research to enhance your in-house AI knowledge capacity

This research is designed to help organizations that are looking to:

1. Strategically employ AI to optimize resource allocation and reduce technical debt, enabling the efficient use of limited financial resources.
2. Harness the power of AI to automate processes, minimize costs, and improve efficiency, alleviating the pressures of resource constraints.
3. Use AI to modernize legacy systems and tackle outdated technologies, enhancing agency performance and service delivery.
4. Encourage cross-departmental collaboration and public-private partnerships to share knowledge and best practices in leveraging AI for technical debt reduction and resource management.
5. Develop robust data governance and security frameworks to ensure the responsible and ethical use of AI in managing technical debt and resource constraints.

Few IT Leaders Are Prepared For Implementing AI

Only 30% of public sector IT professionals say they're experts in implementing AI in their organization.

Source: Salesforce, 2024.

Technical debt negatively impacts digital transformation in government

Slower innovation

Technical debt can consume resources and developer time, constraining the development of new features and technologies. Departments and agencies might find themselves falling behind in the digital transformation race, unable to keep up with the pace of technological advancements.

Increased cost of change

High levels of technical debt can make software changes more costly and time consuming, as developers must navigate complex, poorly documented, or outdated code. This lengthens lead times for implementing digital transformation initiatives and increases costs from additional labor and potential system downtime.

Risk of system failures and security vulnerabilities

Technical debt often leads to more frequent bugs and system failures, which can disrupt digital transformation efforts. Outdated or poorly designed systems can be more vulnerable to security threats, posing data integrity and cybersecurity risks during a digital transformation.

Technical debt comes with a high cost

The growing pace of federal IT spending is caused by system vulnerabilities caused by technical debt

A significant portion of IT budgets are allocated to maintaining legacy systems in US federal departments and agencies. This hinders their ability to invest in innovation and modernization. According to the US GAO (2023), nearly $100 billion is spent annually on IT needs, with a substantial amount going toward legacy system maintenance.

Technical debt severely limits agility and adaptability of federal departments and agencies, preventing them from effectively leveraging cloud technologies and modifying existing systems. TechTarget (2023) reports that 72% of CIOs believe that their organizations face constraints in augmenting or modifying legacy systems due to technical debt.

Integration challenges are driving up maintenance costs. The struggle to integrate modern technologies with older systems in the Canadian public sector perpetuates technical debt, diverting resources from innovation and improvement. Over 40% of Canadian public sector organizations face this challenge, as reported by Financial Post (2023). IDC found that 31% of Canadian government agencies believe technical debt consumes 25% to 50% of total full-time employee time, while 25% feel it accounts for 25% to 50% of their total operational budget (Portage CyberTech, 2023).

Spending on legacy systems hinders digital transformation. The UK public sector's significant spending on maintaining outdated systems diverts funds from strategic initiatives and negatively impacts digital transformation efforts. National Technology News (2021) reported that nearly half of the UK public sector's £4.7 billion (US$5.76 billion) annual IT budget in 2019 was spent on "keeping-the-lights-on" activities for outdated systems.

Growing cybersecurity budgets highlight the need to address vulnerabilities caused by technical debt.

The United States earmarked $10.9 billion for federal civilian cybersecurity capabilities in 2023, an 11% increase from 2022 (SC Media, 2023).

Rising IT budgets reflect the mounting costs of maintaining outdated systems while investing in new technologies.

The US federal IT budget for 2023 was $65 billion, an 11% increase from 2022 (The White House, 2022).

Governments face challenges adopting AI

To adopt AI for the purpose of addressing technical debt and solving resource constraint issues, governments must address the following challenges:

1. Solving a lack of in-house AI expertise. Resourcing can slow down or derail projects aimed at addressing technical debt and resource constraints, requiring additional investment in training or external consulting.
2. Integrating AI technologies into existing systems. This can create new vulnerabilities, adding complexity to the organization's data security and privacy posture.
3. Obtaining appropriate funding support. Limited financial resources can hinder the scope and pace of AI initiatives designed to tackle technical debt and optimize spending, affecting both implementation and ROI.
4. Overcoming internal resistance to new technology. This often results from fear of job displacement or disruption to established processes and can impede efforts to leverage AI for resource management and technical debt reduction.
5. Eliminating inconsistencies in resource allocation and priority setting between departments. This can lead to fragmented approaches to AI adoption, making organization-wide implementation challenging.

The public sector is short on AI skills

Few know how to use generative AI

Only 28% of public sector IT professionals say they're experts in using generative AI as part of their job.
Source: Salesforce, 2024

Governments need a better understanding of Gen AI use cases

Only 32% of public sector IT staff say they're experts in understanding generative AI use cases, such as content creation and data analytics.
Source: Salesforce, 2024

AI can act as a catalyst for overcoming both technical debt and resource constraints

1 AI shifts focus from maintenance to innovation

AI-powered automation reduces the burden of maintaining legacy systems, allowing agencies to focus on innovation. Streamlining processes and proactively resolving issues help break free from technical debt constraints. For example, implementing AI-driven predictive maintenance using machine learning algorithms can reduce breakdowns by 70% and lower maintenance costs by 25% (Deloitte, 2017).

2 AI helps to optimize IT investments

AI-driven insights enable informed IT investment decisions, maximizing ROI and minimizing technical debt. Data-driven analysis helps balance maintaining essential systems with investing in transformative technologies. Leveraging AI-powered portfolio management tools, agencies could improve project success rates by up to 25% and reduce project overruns (ProjectManagement.com, 2023).

3 AI reduces legacy system costs

AI automates repetitive tasks and enhances operational efficiency, reducing costs associated with legacy systems and technical debt. Optimizing resource utilization frees up funds for strategic initiatives. Specifically, deploying robotic process automation (RPA) bots for routine administrative tasks can save agencies an average of 40% on labor costs (Strategic Market Research, 2023).

4 AI enables digital transformation

AI-as-a-service models often provide access to cutting-edge AI capabilities without significant upfront investments, overcoming resource constraints. Partnering with AI providers could accelerate digital transformation. For instance, using cloud-based AI services to standardize workloads and automate many processes, organizations can reduce AI implementation costs up to 80% compared to building in-house solutions, while also shortening the deployment time (CAST AI).

AI has the potential to enable significant cost savings that also relieve fiscal constraints

Automate back-office administration

AI improves intelligent searching capabilities on digital forms and applications, improving efficiency and reducing the need to enter data manually. Organizations can lower overhead costs and get rid of repetitive tasks by training AI to assess applications and automate the review process. For instance, implementing natural language processing (NLP) algorithms can automate the classification and routing of incoming documents, reducing processing time by up to 80% and potentially saving agencies millions in labor costs annually (Cloudflight, 2023).

Improve government employee experience

AI can improve service delivery's speed and quality by enhancing service recommendations and increasing customer engagement. AI can streamline employees' work experience by reducing their workload. Implementing AI-driven virtual assistants can handle up to 70% of routine employee inquiries, freeing up HR staff for more complex tasks and potentially reducing HR-related costs by 25% to 30% (ITC Infotech, 2018).

Empower IT and security staff

AI can be a powerful tool to diminish the impact of the skills gap among security personnel, serving as a temporary solution until a larger cyber workforce becomes available. By deploying AI-powered security information and event management (SIEM) systems, agencies could automate threat detection and response, potentially reducing the time to detect and contain a breach and saving an average of $173,000 per incident (Security Intelligence, 2023).

Cut costs on early-warning systems

Internet of Things, cyberspace, economic, and social data can be processed by deep-learning neural networks to assess risks, predict the course of potential outbreaks, detect anomalies, and provide early warnings – all without human intervention. Integrating AI-powered predictive analytics with real-time data feeds from various sources, agencies can create early warning systems that are incredibly accurate in forecasting potential crises, potentially saving billions in emergency response costs.

Source: Deloitte, 2022

Resource constraints – emerging AI trends

AI-Powered Predictive Maintenance
Reduce costs and extend the lifespan of critical assets.
AI-driven predictive maintenance optimizes maintenance schedules, minimizes unplanned downtime, and extends the lifespan of critical assets. With sensor data and performance metrics, AI accurately predicts when maintenance is required. This proactive approach improves operational efficiency and enables more effective budget allocation.

AI-Driven Robotic Process Automation (RPA)
Automate repetitive tasks and streamline workflows to reduce operational costs.
AI-enhanced RPA automates complex, variable workflows, reduces errors, and frees up human resources for higher-value tasks. This leads to significant cost savings, improved efficiency, and enhanced service delivery. AI capabilities such as natural language processing and machine learning enable intelligent automation solutions.

AI-Powered Fraud Detection and Prevention
Protect public funds and minimize financial losses through advanced AI algorithms.
AI-powered systems detect potential fraud cases in real time with high accuracy, enabling proactive prevention and minimizing financial losses. Analyzing vast amounts of data from multiple sources and identifying patterns and anomalies, AI can help to safeguard public funds and ensure they are used for intended purposes. This contributes to better resource management and public trust.

AI-Optimized Resource Allocation and Budgeting
Leverage AI insights to make data-driven decisions and optimize limited budgets.
AI-driven analytics and optimization tools provide data-driven recommendations for prioritizing investments, optimizing spending, and maximizing ROI. AI helps agencies make informed decisions when allocating limited resources and budgets by analyzing historical data, performance metrics, and external factors. Such an approach enables them to stretch limited funds further and continue delivering essential services.

AI-Enhanced Citizen Engagement and Self-Service
Improve service delivery and reduce costs through AI-powered chatbots and virtual assistants.
AI-powered chatbots and virtual assistants improve citizen experience, provide 24/7 support, and reduce the cost of customer service. Leveraging natural language processing and machine learning, these solutions understand and respond to citizen queries across multiple channels. This optimizes customer service operations and improves accessibility while reducing the human agents' workload.

AI can help governments resolve resource constraints and technical debt challenges

To effectively leverage AI in addressing resource constraints and technical debt, public sector organizations must tackle three interconnected challenges: legacy systems, siloed data, and skill gaps. Overcoming these barriers unlocks the full potential of AI-driven solutions.

Modernizing Legacy Systems With AI-Driven Strategies

AI provides intelligent recommendations for prioritizing modernization efforts and optimizing resource allocation in legacy systems. Analyzing system dependencies, usage patterns, and performance metrics, AI identifies the most critical areas for modernization.

AI-powered tools automatically assess the complexity and risk of modernizing specific legacy systems, helping agencies develop targeted strategies.

AI guides the modernization process, enabling agencies to reduce reliance on outdated technologies and free up resources for strategic investments.

Implementing AI and machine learning algorithms can predict the impact of modernization efforts on system performance, potentially improving digital transformation success rates from 30% to 80% (BCG, 2020).

Breaking Down Data Silos With AI-Powered Integration

AI automates the process of integrating and harmonizing data from disparate sources, creating a unified data foundation for insights and decision-making.

AI-powered data integration and management tools help agencies identify and resolve data inconsistencies, map data relationships across different systems, and create a centralized data repository for easy access and analysis. AI overcomes data silos and improves interoperability, unlocking the full potential of data assets for effective adoption of AI to address resource constraints and technical debt.

Employing natural language processing and knowledge graph technologies, agencies can automate data mapping and integration processes, with the potential to reduce the time required for data harmonization and improve data quality (Sedinkina, 2023).

Bridging Skill Gaps With AI-Powered Training and Collaboration

AI enables targeted training and fosters collaboration among agencies to bridge skill gaps and talent shortages. AI-powered learning platforms provide personalized training recommendations based on an individual's skills, roles, and learning preferences.

AI facilitates cross-agency collaboration and knowledge sharing by identifying experts, best practices, and successful AI projects across different departments. Leveraging AI to bridge skill gaps and promote collaboration helps organizations build the internal expertise needed to effectively adopt AI solutions for overcoming resource constraints and technical debt.

Enacting AI-driven skill assessment and recommendation systems could increase employee productivity by 15% to 20% ("Highly Skilled Workers," MIT Sloan, 2023) and reduce training costs by up to 30% through personalized, just-in-time learning pathways (Deloitte AI Institute, 2023).

The IT talent shortage and overreliance on contracting can be resolved with AI tools

AI can reduce the IT talent shortage and overreliance on contracting, enabling more effective management of resource constraints and technical debt

Canada faces significant resource challenges

The Government of Canada faces a significant deficit in technology professionals, with approximately 7,000 vacant positions. AI can help tackle this talent gap by streamlining hiring processes and identifying the most suitable candidates. AI-powered talent acquisition tools can analyze job requirements, screen resumes, and match candidates with the right skills and experience to fill vacant positions. AI can also assist in creating personalized retention strategies by identifying factors that contribute to employee satisfaction and predicting potential turnover risks.

AI-driven solutions can support the government's efforts to update its processes and deliver the level of services that citizens anticipate while also addressing the challenges posed by the talent gap.

Government contracting in the information technology domain is a significant expenditure. Out of the estimated $15 billion the Canadian government spent on contracting in 2021, $4.6 billion of that was allocated to IT contracts. The public sector's overreliance on outsourcing contributes to the IT skills gap, arising from management's lack of technological understanding and ineffective hiring processes. AI can help reduce this overreliance by providing insights into vendor performance, contract management, and cost optimization. AI-powered vendor management systems can continuously monitor vendor performance, identify potential risks, and provide recommendations for improving the quality and accountability of outsourced projects.

AI can support knowledge transfer and capability building within the public sector, reducing the need for external contractors. Multiple factors exacerbate the IT talent shortage in the public sector, including protracted hiring procedures, lower compensation, and stringent security clearance requirements. AI can help overcome these challenges by automating and streamlining hiring processes, developing competitive compensation packages, and creating more efficient security clearance processes, ultimately enhancing the appeal of public sector IT careers and bridging the talent gap.

Source: Policy Options, 2022

AI-driven solutions are needed to close the gaps caused by IT talent shortage

As the IT talent gap in the public sector continues to widen, the urgency for AI-led solutions has never been greater. Key drivers for AI adoption caused by personnel shortages include cost effectiveness, skill augmentation, resource optimization, speed and responsiveness, faster citizen services, quality and consistency of services, and operational efficiency.

Cost Effectiveness: AI can automate repetitive tasks and optimize resource allocation, reducing labor costs and enabling existing staff to focus on higher-value activities. Using RPA for routine IT tasks, agencies could reduce operational costs by 30% and redeploy staff to more strategic initiatives (CFO Dive, 2024).

Skill Augmentation: AI-powered tools can enhance the capabilities of existing IT personnel, enabling them to perform tasks that would otherwise require specialized expertise. Using AI-assisted coding tools and intelligent debugging systems can help users complete programming tasks 56% faster (Center for Data Innovation, 2024).

Resource Optimization: AI can help prioritize and allocate limited IT resources based on real-time demand and project criticality, ensuring optimal utilization of available talent. Machine learning algorithms can analyze historical project data and current workloads to predict resource needs with significant accuracy, improving overall IT resource utilization (AI Plus Info, 2022; "Potential Value," McKinsey & Company, 2023).

Speed and Responsiveness: AI-driven automation can accelerate processes and enable faster response times, even with a reduced IT workforce. Implementing AI-powered IT service management (ITSM) tools can reduce incident resolution times by up to 50% and increase first-contact resolution rates by 30% (BMC Software, 2024).

Faster Citizen Services: AI-powered chatbots and virtual assistants can handle routine inquiries and service requests, reducing the burden on IT staff and improving citizen satisfaction. NLP-enabled chatbots could resolve up to 80% of common citizen queries without human intervention, freeing up staff for more complex issues ("AI Chatbots," MoldStud, 2024).

Quality and Consistency of Services: AI can ensure consistent application of best practices and standards across IT operations, minimizing human error and maintaining service quality. Relying on AI for automated testing and quality assurance, agencies might reduce software defects by up to 90% (SoftWeb Solutions, 2023) and improve overall system reliability by 25% to 35% ("Automated Testing," MoldStud, 2024).

Operational Efficiency: AI can streamline IT workflows, eliminate bottlenecks, and enable proactive problem resolution, enhancing overall operational efficiency. Implementing AI-driven predictive maintenance can reduce system downtime by up to 50% (Mitsubishi Electric, 2024) and extend the lifespan of IT infrastructure (Sensemore, 2023).

Top Features:

• Robotic Process Automation
• Machine Learning Algorithms
• Workflow Automation
• Cybersecurity Automation
• Data Integration Tools
• Automated Reporting
• Natural Language Processing