When the Ground Shifts: Designing for What Comes Next

Designing for What Comes Next

The core is built—cleaner data, connected systems. The next play:

Workflow design. It's the architecture of how you draw the lines between people, data, and decisions. Neglect it, and AI becomes a tool for doing the same things faster, which is decidedly different than doing them better.

Three foundation layers go a long way in determining if AI can have an actual impact:

1. Data Layer - Clean information pathways between tools and teams 

2. Logic Layer - Defined processes for turning insights into actions 

3. Vision Layer - Clear alignment on what AI should ultimately unlock

When these three layers are connected, real transformation becomes possible. You can think of it as an assembly line: if the parts aren’t labeled, processes aren’t clearly defined, and the finished product is left to interpretation instead of intention, the line can never operate at its best. 

Until the parts, process, and vision lock together, you’re creating noise instead of results.

Key Realities

1. AI is an enhancer - not an architect
   AI is only as smart as the systems beneath it. To max its potential, you need a connected, intentional framework it can build on.

2. Automation without design leads to waste
   AI needs structure to make automation useful. With defined rules and decision points, automation becomes direction—not disorder.

3. Messy collaboration kills momentum
   The companies that have the most success are just as serious about integrating connectivity across teams as they are about integrating systems. Alignment is infrastructure.

4. Workflow friction will surface fast
   If your systems can’t connect cleanly, or if team handoffs require explanation, your early AI projects will stall—no matter how smart the tool or tools you’re using are.

Signal Checks

Three quick gut check questions to see if your organization is setup for AI success:

• Are your workflows clearly mapped, or undocumented knowledge?
  If the system still depends on asking your team’s Slack channel where things live, you’re not ready.

• Does your AI tool help someone make a decision today?
  Insights are only useful if they’re actionable to your teams.

• Are your handoffs clean?
  The more manual or clunky your transitions are, the less AI can help.

The Practical Application

Athletics
Sharing information across departments is a mess. If recruiting, performance, and compliance teams all use different systems and naming conventions, AI can’t stitch the picture together.

Healthcare
Scheduling automation sounds easy until it runs into real-world constraints. If room availability, provider calendars, and intake systems aren’t aligned, your assistant can't reliably take anything off your plate.

Startups
You want to leverage AI to help you prioritize product features, but if user feedback is scattered across Slack channels, customer calls, and unanalyzed app store reviews, your AI will offer a muddled picture, leading to misinformed roadmap decisions.

Next Up - Designing with Vision

Now more than ever, your long-term vision matters. Everything you design today should bend toward the future you want—smarter decisions, sharper signals, and better ways to work.

Part 3 will help you put a clear North Star on paper, so every change you make moves in the same direction.