From being found to helping a choice.

How is AI changing the way customers find and choose businesses?

Understand how AI can affect discovery, comparison, and action—and choose one practical improvement without assuming search or human judgment disappears.

Does SEO still matter when customers use AI search?

Learn where SEO still matters in AI-assisted discovery, which fundamentals to review, and why access and useful decision support solve different problems.

What is the Decision Economy?

Understand the Decision Economy: consequential decision support, the tools and services behind it, and the infrastructure that keeps the help useful.

Why isn’t being found enough to be chosen?

Explore Found → Understood → Considered → Trusted → Chosen → Used, and identify a concrete gap between visibility and useful customer action.

How can I help AI systems understand and consider my business?

Make your offer, fit, evidence, and next step clearer to AI-assisted customers. Separate practical improvements from promises of recommendation.

What is the consideration set, and what does 10 → 3 → 1 illustrate?

Understand the consideration set and the 10 → 3 → 1 illustration. Learn why being available or mentioned is different from being seriously weighed.

What does Better Choices mean if the outcome is uncertain?

A Better Choice means being better equipped to decide. Learn how relevant information, uncertainty, and trade-offs matter without guaranteeing the outcome.

How can I compare offers when their websites leave out different facts?

Compare offers fairly when information is incomplete. Separate requirements, preferences, confirmed facts, and unknowns before choosing a next step.

What business information should I make clear for AI-assisted customers?

Build a useful offer fact sheet covering audience, scope, conditions, evidence, and next steps, with ownership for keeping consequential facts current.

What evidence helps customers evaluate a business’s claims?

Match business claims to evidence customers can inspect. Learn how scope, source, dates, and uncertainty determine what a claim can responsibly say.

Can I trust an AI product or business recommendation?

Check an AI recommendation for fit, evidence, current terms, and action consequences. Know why a useful suggestion is different from verified suitability.

Can anyone guarantee that AI will recommend my business?

Evaluate AI recommendation promises by their scope, evidence, and concrete deliverables. Know what an improvement can establish and what it cannot guarantee.

What is a Decision Support Asset?

Learn what makes a Decision Support Asset useful, how expert logic guides a choice, and where to start. Try the free Decision Economy Readiness Assessment.

How does a DSA help without making the decision for me?

Discover how a DSA can clarify a choice while you retain judgment. Keep advice, evidence, consent, and delegated authority separate.

Can a website be easy for AI to access but still be unhelpful?

A reachable website or API can still be unhelpful. Learn to test access and decision usefulness separately and choose the improvement that is missing.

How do I choose the first decision-support tool to build?

Choose a first decision-support tool around a recurring customer choice. Define the inputs, expert logic, result, limits, ownership, and checks before building.

What should I do with my three assessment actions?

Turn three assessment priorities into assigned work with clear completion checks. Choose self-help, deeper checking, or implementation support deliberately.

Where should a small business start preparing for AI-assisted customers?

Start with one offer and customer decision. Clarify facts, repair evidence gaps, improve a useful next step, and choose technical work for a real need.

What does making a business machine-readable actually involve?

Understand structured business facts, schemas, APIs, and tool contracts. Make information explicit without confusing technical access with useful help.

What are the Four Doors to a decision-support capability?

Explore human UI, REST API, Remote MCP, and WebMCP routes to one governed capability, including the Institute’s current availability boundaries.

What are an API, OpenAPI, and MCP—and which does my business need?

Understand the difference between an API, an OpenAPI description, and MCP. Choose an integration around a real consumer, useful task, and tested contract.

What is WebMCP, and should my business use it yet?

Learn what WebMCP proposes, which browser and task conditions to check, and why implemented code is different from validated public availability.

What changes when AI joins the customer—or is sent ahead?

Distinguish AI helping a customer compare from an agent carrying out a bounded task. Clarify the role, information, permissions, and completion state.

Can an AI agent buy or book something for a customer?

Some AI integrations can buy or book. Learn to check capability, current terms, user authority, and the difference between submitted and confirmed actions.

What permissions and limits should an AI agent have?

Give AI agents a clear task, necessary access, meaningful limits, and approval points. Keep recommendations separate from permission to act.

What does the Decision Economy Readiness Assessment tell me?

DERA gives a BY YOUR ACCOUNT profile across seven dimensions and exactly three starting actions. Understand its value, output, and verification limits.

What does BY YOUR ACCOUNT mean, and what would stronger evidence add?

Understand self-report, public observation, technical tests, and behavioral records—and why stronger claims need the right kind of scoped evidence.

What are the seven dimensions of Decision Economy readiness?

Explore DERA’s seven readiness dimensions, four descriptive statuses, and three starting actions without an overall score or recommendation prediction.

How can I tell whether AI visibility is leading to useful customer action?

Separate AI mentions, referrals, tool starts, completions, and decision-help feedback. Use privacy-safe observations without overstating causation or value.

How do I keep business answers and decision tools accurate over time?

Maintain accurate claims, sources, decision rules, and access paths. Assign owners and review triggers so useful answers remain current after launch.