Boost Solution Delivery Throughput With AI
Embed AI into the DNA of your solution delivery team.
Throughput is the core success factor for all solution delivery teams. Already expected to deliver continuously and quickly, exponential technologies such as AI are accelerating demands on your solution delivery teams. Stop your teams from falling behind: use this step-by-step research to strategically embed AI in your solution delivery process.
AI presents unique opportunities to boost solution delivery throughput such as code generation and automated testing, but it also introduces many challenges. Resources, skill gaps, and skepticism can reduce the potential efficacy of AI integration. Start small and ground your AI adoption in the root causes of your throughput inefficiency and plan the gradual and iterative embrace of AI across your solution delivery process.
1. Start by defining throughput for your organization.
Throughput is the delivery of high-value solutions, both at a speed and a level of quality that are accepted by users and key players. But the standards and expectations for solution value, quality, and delivery cadence will vary. Agreeing on acceptable throughput benchmarks from the get-go is essential for solution delivery success.
2. Test the waters before you dive into the AI deep end.
AI possibilities are endless. Choosing where to begin is critical but difficult. Start with quick-win opportunities that involve proven, out-of-the-box tools to quickly demonstrate the value and fit of AI in your solution delivery team. Use your successful implementation to both build the necessary foundations to support and generate the momentum for broader AI transformations.
3. Focus on AI value over hype.
Contrary to marketing hype, AI is not a silver bullet to all throughput challenges. Your team may be facing unique complications, risks, and uncertainties that AI is not designed to address. The rapid evolution and maturity of AI have addressed some of the concerns stopping organizations in the past, such as output accuracy, and it will only get better. See the benefits AI offers by adopting now but remain skeptical of the aggressive, hyped promises.
Use our comprehensive blueprint to optimize solution delivery throughput with AI.
Build AI and throughput-driven tactics and tools into your solution delivery team’s workflows. Use our step-by-step methodology, tools, and templates to:
Center your solution delivery throughput expectations on an agreeable throughput definition that balances value, quality, and speed.
Envision your solution delivery team with AI by pinpointing the root causes of your throughput challenges and addressing them with the appropriate AI and throughput-driven optimizations.
Build your optimization plan that maps your journey toward your high-throughput and AI-enabled target state.
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Boost Solution Delivery Throughput With AI
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Boost Solution Delivery Throughput With AI
Embed AI into the DNA of your solution delivery team.
Analyst perspective
Boost solution delivery throughput with AI
Throughput has been and will continue to be the success factor of all solution delivery teams. Teams are expected to deliver high-value and high-quality features, fixes, and updates quickly and continuously. However, there are new headwinds getting in their way. Exponential technologies, democratized IT, security vulnerabilities, and other disruptors have made yesterday’s status quo outdated. Enter AI as both the solution and the challenge.
AI presents unique opportunities to address solution quality, value, and delivery speed challenges. For example, code generation can increase productivity, synthetic data generation can produce usable test data, and scanning tools can identify issues before they occur. The only way to see AI’s full benefit is to embed AI into the DNA of your solution delivery team. Every step and decision your team makes is driven, enabled, or executed by AI.
Do not take the AI transition lightly. You need to overcome the many organizational fears, uncertainties, and doubts by attacking the critical delivery problems first and demonstrating positive changes that come with it. With minds at ease, scaling becomes much easier.
Andrew Kum-Seun
Research Director,
Application Delivery and Application Management
Info-Tech Research Group
Executive summary
| Your Challenge | Common Obstacles | Info-Tech’s Approach |
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Solution delivery teams are struggling to meet the increasing demand of the business. Scarce resources, manual processes, and technical debt are just some of the pressing issues that are impeding teams from delivering high-quality and valuable solutions at a consistent and frequent rate. AI presents unique opportunities to address these challenges like code generation and automated testing. However, teams are unsure how they should structure and prepare themselves so they can gain the most value from AI (and other automation solutions) and achieve their throughput objectives. |
The shift to an AI-enabled and high-throughput delivery model brings significant impediments and barriers that solution delivery teams struggle to overcome, including:
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Info-Tech Insight
AI is an inevitable part of solution delivery, but your throughput growth will hit a ceiling. Break through this ceiling by embedding AI into the DNA of your solution delivery team. Every delivery step and decision your team makes is driven, enabled, or executed by AI. Start with out-of-the-box and proven tools to evaluate AI’s impact and its integration into your team. Then, use the lessons learned to build the foundations to scale AI to the rest of your organization.Successful solution delivery hinges on the efficiency of each SDLC stage
Your solution delivery process can be viewed as an assembly line. Errors, omissions, and inefficiencies realized early in the delivery process can result in significant and negative results in the end solution’s value and quality in addition to missed delivery commitments. Complications are further compounded by delaying other requests in the project or product backlog.
Your delivery teams must be able to deliver solutions with good throughput
What is solution delivery throughput?
Solution delivery throughput is the speed at which valuable solution features, updates, and fixes are consistently and efficiently delivered with sufficient quality and acceptance from stakeholders, customers, and end users.
Info-Tech Insight
There is no objective standard for defining and measuring throughput across different SDLC methodologies or from one project to the next. Your throughput optimization should account for your team’s capacity to successfully deliver each ingredient of throughput: value, quality, and speed. An organizational consensus of throughput’s interpretation will also level set expectations as you judge throughput over time and across projects.
Your teams are continuously disrupted and distracted
What we are facing today is transforming the ways in which we work, live, and relate to one another. Solution delivery teams MUST change to meet this reality.
- Exponential technologies. Many modern technologies, such as generative AI, are evolving at an accelerated pace and are doubling their performance, use cases, and impact within shorter time frames. Users are adopting these technologies faster than organizations can react. ChatGPT, for example, took five days to reach one million users in 2022, and Threads took one hour in 2023 (Exploding Topics, 2024).
- Artificial intelligence (AI). The recent spike in AI maturity has turned AI into a viable organizational enabler, thanks to the many successful implementations across the industry. Organizations are doubling down on their AI investments to enable scaled adoption and expect teams to quickly accommodate it. In fact, 34% of respondents are actively using generative AI solutions in quality engineering and testing (Sogeti, 2024).
- Democratized IT. Users want the ability to build, configure, and extend their solutions with seamless access to key enterprise systems and unrestricted integrations with third-party services. Low-code/no-code and software as a service are two of the popular enablers. They looking to your teams for support.
- Security risks. IT is expected to keep up to date on the latest security trends and tactics, but the increased sophistication and volume of attack vectors are overwhelming. Data breach, business email compromise, and system compromise were the top three most frequently experienced incidents in the past two years (Splunk, 2024).
Solution delivery will only become more disruptive
Respondents identified the top factors that will likely disrupt business in 2025:
- Talent shortage
- Artificial intelligence
- Cybersecurity incidents
- Government policy or regulatory changes
- Changing customer behavior
Source: Tech Trends 2025, Info-Tech Research Group; n=695
Meeting high throughput expectations is an industry-wide challenge
Each step and role in the solution delivery process can indirectly impact the efficiency of the others, which can be misinterpreted as the team being unproductive. The reasons why a high-quality and valuable solution cannot be delivered on time can involve multiple small factors (e.g. a key resource being sick for a day) or a single large factor (e.g. unclear translation of business requirements to IT terminology).
What is challenging solution delivery teams?
Top major challenges for quality engineering adoption into the agile lifecycle:
- Not Seen as a Strategic Activity in Our Organization
- Quality Engineering Process Is Not Automated Enough
- Quality Engineers Lack the Skill Set to Support Agile Projects
- Quality Engineering Process Is Too Slow
- Quality Engineering Team Does Not Follow an Agile Approach
- Quality Engineering Processes Are Not Fit for Agile Methodology
Source: Sogeti, World Quality Report 2024-25; n=1,775
Top five areas of developer time loss according to developers:
- Technical Debt
- Insufficient Documentation
- Build Processes
- Lack of Time for Deep Work
- Lack of Clear Direction
Source: Atlassian, State of Developer Experience Report 2024; n=2,150
The inability to quickly deliver causes a negative view of your team
What are the reputational costs of leaving inefficiencies unaddressed?
- Perception of Inefficiency – Any delays in meeting delivery deadlines can be perceived by stakeholders as the team’s inefficiency or lack of skills, even if the cause of the delay was caused by external factors like an employee being sick.
- Eroded Confidence – Stakeholders will be hesitant to rely on teams who were unable to meet delivery commitments or who address problems slowly. They may shift their preferences to consultants or leave out the team from key delivery activities and decisions.
- Negative Ripple Effects – Teams often work interdependently where the delays in one team create delay in another: a domino effect. This can leave resentment and a broader perception of the team as a bottleneck.
- Minimal Stakeholder Engagement – Stakeholders will be reluctant to participate in delivery collaborations when they feel their concerns or needs are not being addressed properly.
- Heavily Scrutinized Practices – Inefficiencies can be attributed by communication gaps, bulky processes, and resource constraints, which can lead to the scrutiny of the team’s methods, philosophy, and structure. Micromanagement will become an attractive solution among stakeholders.
Teams must deliver value to gain stakeholder trust, but…
Teams misunderstand business goals
60% of CxOs stated at least some improvement is needed with IT understanding business goals.
Source: Info-Tech CEO-CIO Alignment Diagnostics, Aug. 2023 to July 2024; n=77
CxOs are frustrated with IT
86% of CxOs experienced at least minor pain involving business frustration with IT failure to deliver value.
Source: Info-Tech CEO-CIO Alignment Diagnostics, Aug. 2023 to July 2024; n=77
AI is no silver bullet, but it can help in key areas of your SDLC teams
Code Generation
Transform natural language, script, or legacy code into a targeted codebase.
Synthetic Data Generation
Create production-like data to improve testing accuracy.
Intelligent Continuous Integration & Deployment
Streamline CI/CD through self-healing, proactive mitigation of risks, and pipeline optimizations.
Automated Testing
Prioritize testing efforts on high-risk areas and orchestrate test suites to minimize bottlenecks and stoppages.
Code Assistance, Autocompletion & Refactoring
Ensure code abides to a specified coding framework and quality standard.
Assistant Chatbots
Provide on-demand, contextual suggestions for better code and design.
Test Case & Script Creation
Craft test cases and scripts for a broad range of sunny and rainy-day scenarios using historical patterns.
Requirements Capturing & Analysis
Draft requirement documents using natural language and analyze their completeness and achievability.
Learn more at AI Marketplace and SoftwareReviews
Throughput optimization begins with a strong solution delivery lifecycle (SDLC) foundation
Throughput optimization cannot start without a foundation. See Info-Tech’s Evolve Your Software Development Lifecycle Into a Solution Delivery Lifecycle blueprint to establish the basics of running a SDLC practice. This blueprint builds upon your lessons learned from your solution delivery pilots.
Solution DLC Playbook Template
Formalize your guide on a common framework for solution management, delivery, and operations. Use this as a starting point for your throughput optimization initiative.
Enhance your SDLC foundation with practices to improve throughput
Be Collaborative, Iterative, Quality- and Value-Driven
The delivery process focuses on fostering teamwork, continuous improvement, and delivering high-quality and valuable solutions aligned with stakeholder goals and non-functional standards.
Embrace Team Experience, Culture, Coaching, and Leadership
Teams are motivated to improve their productivity because the organization embraces an inclusive and satisfying work environment, leaders are inspiring and supporting, and guidance and upskilling is readily available.
Integrate and Manage Your Delivery Toolchain
Seamless ecosystems of tools that work together to improve the collaboration, efficiency, traceability, and overall quality across all SDLC roles and phases. Tools are inventoried, rationalized, and continuously improved.
Align Stakeholders and Manage Your Product Portfolio
Practices ensuring all stakeholders are on the same page regarding priorities, goals, and outcomes while managing a suite of solutions that maximize business value delivery.
Prepare your SDLC team for AI
Solution delivery team
The team is educated on AI, its use cases, and the tools that enable it. They have the skills and capacity to implement, create, and manage AI.
Solution delivery process and tools
The solution delivery process is documented, repeatable, and optimized to use AI effectively. Delivery tools are configured to enable, leverage, and manage AI assets to improve their performance and efficiency.
Solution delivery artifacts
Delivery artifacts (e.g. code, scripts, requirements) that will be used to train and be leveraged by AI are discoverable, accurate, complete, standardized, of sufficient quantity, optimized for AI use, and stored in an accessible shared central repository.
Governance
Policies, role definitions, guidelines, and processes that guide the implementation, development, operations, and management of AI are defined and enforced.
Vision and executive support
Clear alignment of AI direction, ambition, and objectives with broader business and IT priorities. Stakeholders support the AI initiative and allocate human and financial resources for its implementation within the solution delivery team.
Operational support
Capabilities are available to manage AI tools and ensure they support the growing needs of the solution delivery practice, such as security management, hosting infrastructure, risk and change management, and data and application integration.
Measure success with the right metrics
Track metrics throughout your optimization to keep stakeholders informed.
As your team gains more experience with high throughput delivery and AI:
- You will have better-aligned solution delivery and management capabilities with the broader organizational strategy.
- You will see greater confidence of stakeholders, customers, delivery teams, and other IT teams with the organization’s ability to deliver high-quality and valuable solutions in an acceptable timeframe.
- Teams will change the way they work and the tools they use to maximize the benefits from using AI.
- You will promote and facilitate cross-functional collaboration among AI and human roles cemented on transparency, sharing, and accountability. Your teams will be able to focus on high-impact, value-added, and cognitive-intensive initiatives.
| Outcome | Description | Examples of Metrics |
| Improved user satisfaction of delivered and managed solutions | The gratification, completeness, or enjoyment experienced when engaging the solutions delivered or managed by the team. |
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| Improved speed and frequency of delivery | The rate at which solution features, fixes and changes are delivered to production. |
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| Improved solution quality and alignment to industry standards | The degree at which the solution meets specified quality standards and complies with relevant industry regulations and policies. |
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| Improved satisfaction and reputation of the SDLC practice | The gratification, completeness, or enjoyment experienced when engaging the teams in the SDLC practice. |
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See Select and Use SDLC Metrics Effectively and How to Measure Throughput and Win the Business Trust.
Info-Tech’s methodology for boosting solution delivery throughput with AI
| 1. State Achievable Throughput Goals | 2. Assess Your Team’s Delivery Effectiveness and AI Readiness | 3. Design Your Future-State High-Throughput Team | 4. Plan Your Throughput Optimization | |
| Phase Steps | 1.1 State your throughput definition 1.2 List your throughput objectives and metrics 1.3 List your guiding principles |
2.1 Identify your team’s throughput challenges 2.2 Assess your team’s AI readiness |
3.1 List your throughput optimization solutions 3.2 Build your AI tool wish list 3.3 Prepare your team for AI 3.4 Design your future-state team |
4.1 Build your optimization roadmap |
| Phase Outcomes |
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Insight summary
| Overarching insight |
| AI is an inevitable part of solution delivery, but your throughput growth will hit a ceiling. Break through this ceiling by embedding AI into the DNA of your solution delivery team. Every delivery step and decision your team makes is driven, enabled, or executed by AI. Start with out-of-the-box and proven tools to evaluate AI’s impact and its integration into your team. Then, use the lessons learned to build the foundations to scale AI to the rest of your organization. |
| Phase 1 insight |
| Throughput is more than just delivering fast. It is delivering high-quality and valuable solutions consistently and efficiently. Agree on a common interpretation of throughput among your solution delivery teams and stakeholders. Ensure each ingredient of throughput (solution value, quality, and delivery speed) is broken down in your definition. |
| Phase 2 insight |
| The root causes of your throughput issues go beyond the tasks and projects assigned to your solution delivery teams. Evaluate delivery throughput through the eyes of your team. Social and cultural factors (e.g. empowerment, autonomy, and engagement) play critical roles in a team’s ability and motivation to deliver effectively and continuously improve. |
| Phase 3 insight |
| AI is no longer an experiment. However, its growth and value are stunted by the reluctance of the broader department to conform to AI-native practices. Don’t delay; adopt AI tools and practices now. Be aggressive in your transition to be AI-native to both demonstrate the value of AI and prepare your team for future AI initiatives. Otherwise, you will only put yourself further behind. |
| Phase 4 insight |
| Successful AI adoption begins with building the confidence and buy-in you need to scale. Start with the quick wins and the AI tools that require little effort to set up. Maximize your time to demonstrate AI’s acceptance in your team and validate the practices that exploit AI’s capabilities without getting caught up in the tool’s complexity. Be humble in what you can achieve. |
Blueprint deliverables
Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:
Solution Delivery Team Throughput Current-State Assessment and AI Readiness Tool
Assess the current state of your solution delivery teams and their readiness to adopt AI.
Key deliverable:
Solution Delivery Throughput Optimization Plan Template
Document your plan to optimize the throughput of your solution delivery team in the language your stakeholders understand. Tailor this document to fit your throughput objectives and organizational context.
Blueprint benefits
| Identify and Address The Root Causes of Your Delivery Throughput Challenges | Plan the Optimization Initiatives With Achievable Expectations |
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Notable Impacts
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Notable Impacts
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Info-Tech offers various levels of support to best suit your needs
| DIY Toolkit | Guided Implementation | Workshop | Executive & Technical Counseling | Consulting |
|---|---|---|---|---|
| "Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful." | "Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track." | "We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place." | "Our team and processes are maturing; however, to expedite the journey we’ll need a seasoned practitioner to coach and validate approaches, deliverables, and opportunities." | "Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project." |
Diagnostics and consistent frameworks are used throughout all five options.
Guided Implementation
What does a typical GI on this topic look like?
| Phase 1 | Phase 2 | Phase 3 | Phase 4 |
|---|---|---|---|
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Call #1: Come to a common definition of throughput. Call #2: State your throughput objectives and metrics. |
Call #3: Assess your team’s current state. Call #4: Determine your team’s AI readiness. |
Call #5: Brainstorm solutions to address your throughput challenges. Call #6: Envision your target-state team. |
Call #7: Prioritize your optimization initiatives. Call #8: Complete your throughput optimization plan. |
A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.
A typical GI is 6 to 8 calls over the course of 3 to 5 months.
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Boost Solution Delivery Throughput With AI
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Andrew
Kum-Seun
Research Director
About Info-Tech
Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.
We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
What Is a Blueprint?
A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.
Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.
You get:
- Solution Delivery Team Throughput Current State Assessment and AI Readiness Tool
- Solution Delivery Throughput Optimization Plan Template and Example
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Our analyst calls are focused on helping our members use the research we produce, and our experts will guide you to successful project completion.
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