This is what an AI agent reads. Same page, second kind of user.

1---
2title: "AI Use-Case Prioritization & Feasibility | AppStream Studio"
3description: "Rank where AI can create measurable value in your business. Quick feasibility tests against your real data and workflows, ending in a sequenced roadmap."
4url: https://appstream.studio/solutions/agent-strategy
5markdown_url: https://appstream.studio/solutions/agent-strategy.md
6---
7 
81. [Solutions](https://appstream.studio/solutions.md)
92. [Advise](https://appstream.studio/solutions/advise.md)
103. Agent Strategy
11 
12Agent Strategy
13 
14# Know which workflows AI should take on first, before you fund the build.
15 
16Most teams can name ten places AI might help and can’t rank them. We test candidate workflows against your real data and systems, and tell you which to build, which to defer, and which to drop.
17 
18[Talk to an AI engineer](https://appstream.studio/schedule-a-discovery-call.md) · [Explore Advise](https://appstream.studio/solutions/advise.md)
19 
20[Part of 01 Advise Know where to apply AI. Use-case prioritization](https://appstream.studio/solutions/advise.md)
21 
22Where this sits in the lifecycle
23 
241. [01 Advise You are here](https://appstream.studio/solutions/advise.md)
252. [02 Engineer](https://appstream.studio/solutions/engineer.md)
263. [03 Operate](https://appstream.studio/solutions/operate.md)
27[Govern Runs across all three](https://appstream.studio/solutions/govern.md)
28 
29The problem
30 
31## AI projects usually fail before the first line of code: someone picks a technology, builds a demo, then goes looking for a workflow to justify it.
32 
33- No shared view of where AI changes the economics of the work
34- Demos that impress in a meeting and connect to nothing
35- Budget going to whatever is newest, not what pays back
36- Cloud bills arriving before anyone has asked what it’s for
37 
38How we work
39 
40## Four steps. One team the whole way.
41 
421. 01
43### Map the work
44Sit with the teams who own the workflows. Find where time, cost, and error actually concentrate, not where the loudest idea is.
452. 02
46### Match capability to work
47For each candidate, decide what today’s AI can genuinely carry: full automation, assistance, or nothing yet.
483. 03
49### Test against your data
50Lightweight prototypes on your real data and systems. If it doesn’t hold up on your data, it doesn’t go on the roadmap.
514. 04
52### Sequence the roadmap
53What to build first, what to defer, and what to drop, ordered so the first build funds the next.
54 
55What’s included
56 
57## What agent strategy covers. In practice.
58 
59- ### Use-case discovery
60Structured sessions and data review that surface where AI moves an operating metric, not a brainstorm.
61- ### Feasibility testing
62Quick prototypes against your real data, so “possible” means possible here.
63- ### Risk assessment
64Data readiness, integration complexity, compliance exposure, and what could go wrong.
65- ### Cost & return modeling
66Expected build and run costs against the value, so leadership can make a real decision.
67- ### Sequenced roadmap
68Phased and prioritized, written for the team that has to execute it.
69- ### Build-ready handoff
70Each first build is scoped well enough for engineering to start the following week.
71 
72What you can hold us to
73 
74## Commitments. Not marketing ranges.
75 
76Sprint length from engagements we have run; the rest is what the engagement commits to.
77 
78to a roadmap
79 
802–4 wks
81 
82Typical sprint from kickoff to a ranked, sequenced plan
83 
84not a sandbox
85 
86Your data
87 
88Candidates are tested against your real systems before they’re recommended
89 
90with reasons
91 
92Ranked
93 
94Every use case comes back with value, feasibility, and risk written down
95 
96Go deeper
97 
98## More under Advise, and beyond.
99 
100- [Advise Know where to apply AI. Find where emerging AI capabilities can create measurable business value, and build the roadmap to get there.](https://appstream.studio/solutions/advise.md)
101- [Agent Engineering Agents that do the work inside your systems, not beside them.](https://appstream.studio/solutions/agent-engineering.md)
102- [Agent Knowledge Layer AI is only as good as what it knows about your business.](https://appstream.studio/solutions/agent-knowledge-layer.md)
103- [Agent Operations The demo worked. Now it has to run every day.](https://appstream.studio/solutions/agent-operations.md)
104- [Forward-deployed engineers However you start, our engineers embed with your team: your Slack, your repo, your standups.](https://appstream.studio/forward-deployed-engineers.md)
105 
106## Bring us your shortlist. We’ll rank it.
107 
108Give us the candidate workflows and access to the real data. We’ll tell you which ones today’s AI can carry, and which to drop.
109 
110[Talk to an AI engineer](https://appstream.studio/schedule-a-discovery-call.md) · [See our work](https://appstream.studio/case-studies.md)
111 
112---
113 
114## AppStream Studio
115 
116AppStream turns frontier AI capabilities into production systems that perform real work. Talk to an AI engineer: https://appstream.studio/schedule-a-discovery-call · Email: contact@appstream.studio
117 
118- [Home](https://appstream.studio/index.md)
119- [Solutions](https://appstream.studio/solutions.md)
120- [Advise](https://appstream.studio/solutions/advise.md)
121- [Engineer](https://appstream.studio/solutions/engineer.md)
122- [Operate](https://appstream.studio/solutions/operate.md)
123- [Govern](https://appstream.studio/solutions/govern.md)
124- [How we work](https://appstream.studio/how-we-work.md)
125- [Work (case studies)](https://appstream.studio/case-studies.md)
126- [Industries](https://appstream.studio/industries.md)
127- [Insights](https://appstream.studio/blog.md)
128- [Partners](https://appstream.studio/partners.md)
129- [About](https://appstream.studio/about-us.md)
130- [Contact](https://appstream.studio/contact.md)
131