Get Started With AI in Requirements Management
Leverage AI to improve your requirements practices, not replace them.
The first big challenge is how to get started. There are tools and vendors that offer significant benefits to productivity, but organizations don’t know how to use them to their advantage.
With things moving so quickly, organizations may throw a lot of time, money, and effort at AI to keep up with competitors. If they don’t begin by defining how they plan to use it or what needs they hope to address, these resources are ill-spent.
There is always the fear that AI will get rid of all jobs in any category that it moves into.
Our Advice
Critical Insight
Requirements management will always need the human element. AI creates an opportunity where business analysts (BAs) can focus on the activities that matter. If you learn how to leverage AI to automate low-value requirements management activities, you can free up capacity for higher-value work to be done.
Impact and Result
AI doesn’t mean automating everything or that BA roles disappear. Quite the opposite! To thrive, BAs will have to adapt and determine how and when to leverage AI to reduce time and effort spent on low-value tasks, freeing up capacity to focus on higher-value analysis and insights.
Your AI is only as good as the data used to train it. Embedding mature practices in the learning models ensures a high-value, high-quality result. Business analysis has a big role to play in this regard.
There's a right way to approach AI adoption. Charging in without knowing what problem you are trying to solve or the benefits you are looking to achieve wastes time and valuable resources. Embracing AI blindly is as effective as ignoring it altogether.
Member Testimonials
After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.
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Altaz was extremely knowledgeable on the subject matter and provided great insights into how we should approach building an AI-based offering for o... Read More
Workshop: Get Started With AI in Requirements Management
Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Pre-Work
The Purpose
- Set the context to assess the risk tolerance and readiness of the organization to integrate AI into their requirements management practices.
Key Benefits Achieved
- Have a baseline of how ready your organization is to leverage AI.
Activities
Outputs
Complete the AI risk assessment.
- A completed AI risk assessment
Complete the AI in requirements management readiness assessment.
- A completed AI readiness assessment
Module 2: Build the Case for AI
The Purpose
- Lay the foundation for AI usage, discussing the pros and cons, costs and benefits, and excitement and fears for this new way of working.
Key Benefits Achieved
- A review of the risk and readiness assessments
- An understanding of the current state of the organization from a people, process, and culture perspective
Activities
Outputs
Review your business context.
- An understanding of how AI aligns to organizational attitudes toward risk
Understand the impacts of AI in requirements management.
- Recognition of initial readiness of AI adoption and any significant gaps.
Discuss fears associated with new technologies.
Explore the risks associated with AI.
Discuss organizational readiness for AI.
Module 3: Define Your Future State
The Purpose
Support building the bridge from the current state to the future state.
Key Benefits Achieved
- Exploring AI use cases for requirements management
- Exploring tools to help solve problems or enable opportunities
Activities
Outputs
Discuss current gaps in your organization.
- A defined set of guiding principles for AI usage
Define your AI guiding principles.
- A list of AI use cases
Explore potential AI use cases.
- A list of potential AI tools
Prioritize AI use cases.
- A selected AI project
Discuss available tools.
Select your pilot project.
Module 4: Prepare for Your Pilot
The Purpose
Put the pieces in place for your team to prepare to run its first pilot project.
Key Benefits Achieved
A shared understanding of team needs and composition, timelines, and success criteria
Activities
Outputs
Assemble your executive communication deck.
- A completed executive communication deck
Discuss your project team composition.
- A pilot project timeline and success criteria
Define your pilot project timelines.
- A pilot project timeline and success criteria
Define your project success criteria and hypothesis.
- A pilot project timeline and success criteria
Planning your next steps.
- A pilot project timeline and success criteria
Module 5: Next Steps and Wrap-Up
The Purpose
Complete deliverables so that you are ready to run your first AI pilot project.
Key Benefits Achieved
A document to communicate with executives about the value and benefits of AI in requirements management
Activities
Outputs
Complete in-progress deliverables from previous four days.
- Completed executive communication deck and deliverables
Set up review time for workshop deliverables and to discuss next steps.
- AI roadmap for requirements management
Get Started With AI in Requirements Management
Leverage AI to improve your requirements practices, not replace them
Analyst’s Perspective
AI is here. Are you ready?
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AI isn’t coming, it’s here! Business analysts need to get ready so they can help their organizations do the same. AI will revolutionize the practice of requirements management, presenting opportunities for unprecedented efficiency and accuracy in the solution development lifecycle. By leveraging AI-powered tools and techniques, business analysts can better support their organizations through faster development cycles and improved product quality, with the ability to spend much-needed time on analysis. This can minimize the low-value, high-effort processes of eliciting and validating requirements. However, it is crucial that organizations approach AI implementation with a thoughtful and cautious strategy. Getting started the right way involves understanding the constraints and limitations of AI, ensuring data quality and diversity to avoid biased outcomes, and incorporating human oversight throughout the process. By embracing AI responsibly and adopting best practices, organizations can harness the full potential of AI in requirements management, driving innovation and achieving their business objectives more efficiently. |
|
Vincent Mirabelli |
Get Started With AI in Requirements Management
EXECUTIVE BRIEF
Executive Summary
|
Your Challenge |
Common Obstacles |
Info-Tech’s Approach |
|---|---|---|
|
The business analyst role is changing, and AI will accelerate that change. Business analysts are asked to do more with less, which is always challenging. It means missed deadlines, delayed value, and lower quality solutions. Today’s business analysts need more support than ever. The use of AI in requirements management is inevitable. The same holds true throughout the organization. The potential for increased productivity and accuracy cannot be ignored. Leaders expect AI to support their strategic objectives. It's top of mind, having captured everyone's imagination. They believe it can achieve their strategic objectives without necessarily recognizing the significant changes this would bring to the organization. |
The first big challenge is how to begin. There are tools and vendors that offer significant productivity benefits, but it is unclear how they can be used to the organization’s advantage. With things moving so quickly, organizations may throw a lot of time, money, and effort at AI to keep up with competitors. If they don’t begin by defining how they plan to use it or what needs they hope to address, such resources are ill-spent. There is always the fear that AI will get rid of all jobs in any category that it moves into. |
AI doesn’t mean automating everything. Business analysts remain vital, but they must determine how and when AI can help them reduce time and effort spent on low value tasks, freeing them to focus on irreplaceable analysis and insights. Your AI is only as good as the data used to train it. You must embed mature practices in the learning models to ensure a high value, quality result. Business analysis plays a big role in this regard. Approach AI adoption the right way. Charging in without knowing what problem you are trying to solve or the benefits you are looking to achieve wastes time and valuable resources. Doing that is as effective as ignoring it altogether. |
Info-Tech Insight
Requirements management will always need the human element. AI can allow business analysts to focus on the activities that matter most. If you learn how to leverage AI to automate low-value requirements management activities, you can free up capacity for higher-value work to be done.
Info-Tech’s methodology to getting started with AI in requirements management
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1. Make the Case for AI in Requirements Management |
2. Define Your Requirements AI Future State |
3. Build and Deploy a Requirements AI Pilot |
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|---|---|---|---|
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Phase steps |
1.1 Understand the risks and rewards of AI 1.2 Understand the impact of AI on requirements management |
2.1 Define the needs of effective AI 2.2 Define your guiding principles 2.3 Identify potential use cases 2.4 Assess the available tools 2.5 Communicate the opportunities to leadership |
3.1 Prepare for your pilot |
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Phase outcomes |
An assessment of organizational risk appetite for AI, and of your organizational readiness and timing for AI. An understanding of leveraging AI in your requirements management practices can impact your organization. |
Assurance that you have the right pieces in place to benefit from AI. A defined need and prioritized set of use cases that AI can support. Executive support and oversight to proceed with your AI initiatives. |
Your requirements management practices benefiting from successfully deploying AI. Now you can decide next steps and which initiative to tackle next. |
Insight summary
Requirements management will always need the human element.
AI can allow business analysts to focus on the activities that matter most. If you learn how to leverage AI to automate low-value requirements management activities, you can free up capacity for higher-value work to be done.
Your business analysis team can and should lead the way in helping you start the AI movement in your organization.
AI won't replace the business analyst, but an analyst who knows how to leverage AI will replace one who doesn’t.
We’re still at an early stage of AI in requirements management. Use this time as a learning opportunity, so you don’t get left behind by your colleagues and competition.
Don't fall victim to the over-hype.
It's easy to get swept up when you don't know where to start, or what the value is.
Don’t swing for the fences during your first at-bat.
Keep the scope and timelines of your initial AI project manageable. As the focus is on quick wins to get started, avoid the big, onerous projects that span years.
AI is becoming the new human/computer interface.
AI’s progression as a human/computer interface promises to redefine our relationship with technology. This will further empower us, breaking down barriers and making our interactions with the digital world become seamless, effortless, and natural.
AI brings a shift in how decisions are made.
When decisions are based on probabilities, a shift is required from deterministic and binary thinking (yes/no) to probabilistic and less certain. For example, what does it mean that the likelihood of something is 95% or 82%? How would that translate into action?
Leaders must be ready to operate with this new way of thinking and decision making.
Don’t be fooled by the “sell”
Many vendors have jumped on generative AI (Gen AI) as the latest marketing buzzword. When vendors proclaim to offer Gen AI functionality, pin down what exactly is generative about it. The solution must be able to induce new outputs from inputted data via self-supervision – not trained to produce certain outputs based on certain inputs.
AI will not solve your people and process problems. It will expose and amplify them.
Don’t use AI simply because you can. Explore options to improve people and process before exploring technology, and how AI can enable improved outcomes.
Ensure policies, processes, and standards add value.
When defining your AI policies, processes, and standards, ensure they are relevant, serve a purpose, and/or support the risk management framework and the use of AI in the organization. Commit to reviewing them periodically as the technology evolves/expands.
Start small. Select strategic targets.
Focus only where AI has the potential to deliver significant business value.
Blueprint deliverables
Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:
Accelerator Workbook
Supporting tools and templates that help you assess your current state and build the case for leveraging AI in requirements management
Key deliverable:
Executive Communication Deck
A practical template for communicating with your leadership and executives, articulating the value and AI use cases applicable to requirements management.
Despite the growth in supporting AI technologies, organizations are still struggling to adopt them
The struggle with AI is real
Despite the many promises of AI, organizations are struggling to fully realize its potential, as they would with any other new technology.
Forty-three percent of businesses are concerned that they will become too reliant on this new technology, with an additional 35% considering whether they have the technical skills and know-how to effectively leverage AI in the first place (Forbes Advisor, 2023).
The reasons often boil down to a lack of understanding of when these technologies should and shouldn’t be used, including a fear of the unknown. There are reports of AI replacing many jobs, and these fears are rational as we have yet to learn how this technology will impact the current job landscape. However, fears like this accompany all revolutionary technologies.
A better understanding of how best to work with the changes will help everyone through this revolution.
Are you ready for AI?
Business Analysis Team
The team is educated on AI, the use cases, and the tools that enable it. They have the skills and capacity to implement, create, and manage AI in a live environment.
Process & Tools
Your processes are documented, repeatable, and optimized to use AI effectively. Delivery tools are configured to enable, leverage, and manage assets to improve their performance and efficiency.
Solution Delivery Artifacts
Delivery artifacts (e.g. code, scripts, documents) that will be used to train and will be leveraged by AI tools are discoverable, accurate, complete, standardized, of sufficient quantity, optimized for use, and stored in an accessible shared central repository.
Governance
There are defined policies, role definitions, guidelines, and processes that guide the implementation, development, operations, and management of AI.
Vision & 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 team.
Operational Support
The capabilities to manage AI tools in operating areas. AI supports the growing needs of the requirements management practice, including security management, infrastructure, risk and change management, and data and application integration.
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.
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Speak With An Analyst
Get the help you need in this 3-phase advisory process. You'll receive 8 touchpoints with our researchers, all included in your membership.
Guided Implementation 1: Make the case for AI in requirements management
- Call 1: Scope requirements, objectives, and your specific challenges.
- Call 2: Discuss current attitudes toward risk with AI.
- Call 3: Discuss your AI readiness.
Guided Implementation 2: Define your requirements management AI future state
- Call 1: Identify AI gaps in data, governance, executive support, team capabilities, and alignment to strategy.
- Call 2: Discuss your AI guiding principles and usage policies.
Guided Implementation 3: Build and deploy a requirements management AI pilot plan
- Call 1: Discuss and prioritize use cases.
- Call 2: Select and plan your AI pilot project, and define success criteria.
- Call 3: Summarize results and plan next steps.
Contributors
- Emal Bariali, Business Architect & Business Analyst, Bariali Consulting
- AJ Hawley, Founder, Trendsparency
- Fabricio Laguna, Professional Speaker, Consultant, and Trainer, TheBrazilianBA.com
- Christina Lovelock, Business Analysis Leader/Author/Speaker/Coach
- 5 anonymous contributors
- 19 anonymous survey respondents
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Get Started With AI in Requirements Management
