Reinventing Business Analysis with AI and Human Expertise

Gathering requirements can still take weeks, even on teams with excellent tools. The holdup is the interviews: scheduling them, running them one at a time, and connecting what people said. An AI chatbot that speeds up documentation doesn't touch any of that.

The fix is a new division of labor. AI runs the interviews and first drafts. Senior analysts own the judgment calls.

SummitPath delivers both as one service. Our senior human analysts are part of it, so you don't need a business analyst of your own. If you already have one, we work hand-in-hand with them.

Why faster documentation doesn't fix the interview problem

Business analysts already use AI. IIBA's summary of its 2026 Global State of Business Analysis report says the vast majority of respondents use AI tools.^[1] The most common uses are drafting and formatting (28%), communication and documentation (25%), and idea generation or problem-solving (22%).

Those uses are valuable, but the process around them stays the same. A human analyst still runs interviews one at a time, coordinates calendars for weeks, and pieces the findings together afterward.

Then there's the delay between conversations. When interviews are spread over weeks, a conflict found in the last one can't change the questions asked in the first. Going back takes another meeting on another calendar. AI removes that problem, because the interviews can all happen within a few days.

What AI does well in requirements work

Research shows AI can run interviews, ask good follow-ups, and check work against clear criteria.

• AI can run the interview. In LLMREI, a chatbot ran requirements interviews with stakeholders. AI fully captured up to about 60% of requirements and partly captured more.^[2]
• AI asks good follow-ups. In two controlled experiments, AI's follow-up questions were as clear, relevant, and informative as human-written ones. When guided by common interviewer mistakes, they beat the human questions.^[3]
• AI stays on point. In a 2026 pilot on help-seeking interviews, AI and human interviewers scored equally on relevance.^[4]
• AI checks quality. A study of 10 AI models found they could reliably judge the quality of user stories when given clear criteria.^[5]

A big advantage is availability. An AI interviewer has no calendar, so every stakeholder can talk to it within a few days.

Where human analysts make the difference

Human analysts turn fast AI output into requirements a team can trust, which is why senior analysts are part of the SummitPath service. In the study of 10 models, AI-written user stories matched human ones on coverage and style, but showed less creativity and met acceptance criteria less often.^[5] Generative AI can also state false things with confidence, a risk NIST calls confabulation.^[6]

Three kinds of judgment belong with people:

• Reading between the lines. When a stakeholder says "we need this to be flexible," they might mean "we're planning future enhancements" or "the last vendor locked us into their system." Each meaning leads to different requirements.
• Organizational context. One team's request can conflict with another team's priorities, even when nobody says so. Spotting that takes knowledge of the business and the right follow-up questions.
• Strategic implications. Someone has to decide whether a requirement will cause problems the organization regrets later, or whether a solution solves the business problem at all.

How to divide requirements work between AI and human analysts

Give AI the work that rewards volume and consistency. Give people the work where a mistake is costly. Here's the split we follow and recommend:

One conflict, from interview to decision

1. Interviews. Say sales tells the AI that customers need next-day delivery, and operations says orders take three days to process.
2. AI synthesis. The AI flags the conflict and asks each side a follow-up: which customers need next-day delivery, and what would it take to ship faster?
3. Analyst judgment. A senior analyst reads both answers and sees that the need is limited to a few large accounts.
4. Decision. SummitPath's analyst brings sales and operations together to agree on delivery targets for those accounts.
5. Documentation. The AI updates the draft requirement. The analyst confirms that it records the target, the reason, and who agreed.

How the SummitPath hybrid approach works

SummitPath pairs an AI business analyst, a voice bot named Thomas, with our senior human analyst team. The work follows five phases. For scheduling and handoff details, see how SummitPath integrates into your team workflow.

1. Define Project & Stakeholders

It starts with a kickoff conversation between Thomas and your project lead: what you're building and why, who the key stakeholders are, what's in scope, and what success looks like.

2. Collect & Analyze Requirements

Thomas introduces himself to each stakeholder, and SummitPath is upfront that he's an AI. Each person picks a time for a conversation, usually 20 to 45 minutes. All of them can happen within a few days, so earlier insights inform later interviews right away.

SummitPath's AI looks for patterns, dependencies, conflicts, and potential concerns, while our senior analysts check for gaps and clarify ambiguities. Finding disagreements this early also helps with cross-functional alignment.

Our senior analysts focus on the things that need human judgment:

• Whether the requirements serve the strategy behind the project
• Unresolved disagreements between teams
• Industry context, such as regulatory and security considerations
• Fit with your team's tools and working processes
• Anything stakeholders didn't mention but the project needs

3. Generate Draft Deliverables

SummitPath's AI turns the requirements into draft user stories, specs, process flows, and more. Our senior analysts then review the draft deliverables for:

• Quality: ready for your team to act on
• Accuracy: true to what stakeholders said
• Strategic alignment: tied to the project's goals

4. Review & Refine

Reviewing the drafts is easy for your team, and it goes as deep as you want. Give quick feedback or work through every detail. Thomas handles minor changes. Our senior analysts guide major ones, with targeted stakeholder follow-ups where needed.

Review continues until everything aligns with your vision.

5. Deliverables

You get polished deliverables your team can act on immediately, in the format that works for you.

Weeks of business analysis, done in days

AI interviews plus expert review change what a requirements project looks like:

• No calendar chase. Stakeholders talk when it suits them, and every interview can happen within a few days.
• No business analyst required. Senior analysts come with the service. If you have a business analyst, we work hand-in-hand with them.
• Conflicts surface early. Disagreements show up while people still remember the conversation, before anyone starts building.
• Expert review on every deliverable. AI brings the speed, and senior analysts ensure quality, accuracy, and strategic alignment.
• No hiring or retainers. You get senior business analysis without salary, overhead, or long-term contracts.

The Future We're Building

AI is fundamentally changing what's possible in business analysis. Not by replacing human judgment, but by removing the constraints that have always limited how quickly and effectively requirements can be gathered.

The most valuable business analysts have always been the ones who can recognize patterns across domains, navigate organizational complexity, and translate business strategy into technical reality. The hybrid approach makes this expertise more accessible and more impactful.

That's the future we're building at SummitPath. Not human or AI. Human and AI. Each doing what they do best.