Agentic Commerce Readiness. Prepare Your B2B Company for AI-Assisted Buying, Selling and Procurement
Agentic commerce is an emerging model in which AI systems support or perform selected commercial activities on behalf of buyers, suppliers and organisations.
An AI agent may help a buyer:
- identify a purchasing requirement;
- search for relevant suppliers;
- discover suitable products;
- compare technical specifications;
- check commercial conditions;
- request missing information;
- prepare a shortlist;
- generate a request for quotation;
- collect supplier responses;
- recommend a purchasing decision.
A supplier-side agent may help a company:
- identify relevant enquiries;
- qualify incoming requirements;
- match a requirement with the correct product;
- request missing buyer information;
- provide approved product data;
- prepare a quotation draft;
- route the opportunity to the right employee;
- monitor deadlines and next actions.
Agentic Commerce Readiness is the ability of a company to support these processes with reliable information, clearly defined workflows and controlled business rules.
It requires more than adding a chatbot to a website.
A company must prepare its:
- identity data;
- product data;
- capability data;
- technical qualification rules;
- commercial conditions;
- documentation;
- RFQ process;
- permissions;
- human approval procedures;
- transaction limits;
- escalation paths.
Direct RFQ helps B2B companies assess and develop this readiness step by step.
Primary CTA: Request an Agentic Commerce Readiness Assessment
Secondary CTA: Explore A2O Optimization
From Digital Presence to Agentic Participation
Most B2B websites were designed for a traditional process.
A human buyer visits a page, reads a description, downloads a catalogue and contacts a sales representative.
Agentic commerce changes the structure of this journey.
An AI system may interact with the information before a human visits the website.
It may need to determine:
- whether the company is a real and relevant supplier;
- whether the supplier serves the required market;
- whether the product fits the application;
- which model or configuration is appropriate;
- whether the product is currently available;
- what the minimum order quantity is;
- how the price is calculated;
- which delivery conditions apply;
- whether installation is required;
- which documents are available;
- whether the agent is authorised to perform the next action.
A company may be visible in search results but still be unprepared for this process.
Agentic Commerce Readiness closes the gap between online visibility and operational participation.
What Is Agentic Commerce?
Agentic commerce describes commercial processes in which AI agents perform or coordinate activities within a defined mandate.
These activities may include:
- product discovery;
- supplier discovery;
- requirement analysis;
- technical matching;
- offer comparison;
- document collection;
- RFQ preparation;
- quotation support;
- scheduling;
- negotiation preparation;
- purchasing recommendations;
- transaction initiation;
- order monitoring.
The level of autonomy can vary significantly.
In some cases, the AI only recommends an action.
In other cases, it may prepare the action and wait for human approval.
In more advanced environments, it may perform selected actions automatically within predefined limits.
Agentic commerce should therefore not be treated as one universal operating model.
It can be divided into several practical levels of responsibility and autonomy.
Levels of Agentic Commerce
Assisted Commerce
The AI supports a human user but does not independently perform commercial actions.
It may:
- summarize product information;
- suggest suppliers;
- compare specifications;
- identify missing data;
- prepare a draft enquiry.
The human remains responsible for every decision and action.
Operational Agentic Commerce
The AI coordinates parts of the commercial process.
It may:
- gather information from several sources;
- ask qualification questions;
- structure a purchasing requirement;
- create an RFQ draft;
- route the request to selected suppliers;
- organize supplier responses.
Important decisions still require human approval.
Transactional Agentic Commerce
The AI may perform selected commercial actions within an approved mandate.
It may:
- submit an RFQ;
- request documents;
- confirm availability;
- reserve stock;
- accept a predefined condition;
- initiate an order below a specified value.
The permitted scope, financial limits and approval rules must be clearly defined.
Autonomous Agentic Commerce
The AI can coordinate a larger part of the buying or selling process with limited human intervention.
This may include:
- supplier discovery;
- qualification;
- negotiation within predefined boundaries;
- transaction initiation;
- fulfilment monitoring;
- exception handling.
This level requires mature data, security, governance, auditability and escalation procedures.
Most industrial B2B companies do not need to begin at this level.
A structured, human-supervised model is usually the more practical starting point.
What Does Agentic Commerce Readiness Mean?
Agentic Commerce Readiness means that a company’s digital and operational environment can support AI-assisted business processes without creating unacceptable ambiguity, risk or loss of control.
A ready company should be able to answer six fundamental questions.
Can the agent find the correct information?
The system must be able to locate the company, product, capability, document, commercial rule and action path.
Can the agent understand the offer?
The system must correctly interpret names, categories, specifications, variants, applications, limitations and business relationships.
Can the agent compare relevant alternatives?
The system must have access to consistent technical and commercial criteria.
Can the agent verify important claims?
The system must be able to identify the source, owner, validity and evidence behind important information.
Can the agent perform an approved action?
The system must know which actions are possible and which inputs are required.
Can the action be governed?
Permissions, transaction limits, human approval, logging and escalation must be clearly defined.
Direct RFQ evaluates these areas through the FUCTEG framework:
- Findable;
- Understandable;
- Comparable;
- Trustworthy;
- Executable;
- Governable.
Why Industrial B2B Requires a Different Approach
Agentic commerce in industrial markets is more complex than a simple consumer purchase.
A buyer may not be selecting a standard product with a fixed price.
The purchasing decision may depend on:
- product dimensions;
- material properties;
- required performance;
- production speed;
- operating conditions;
- electrical or pneumatic supply;
- compatibility with existing equipment;
- installation requirements;
- regulatory documentation;
- service coverage;
- delivery location;
- project schedule;
- custom engineering;
- technical acceptance.
A product may have several configurations.
The public price may not include:
- transport;
- installation;
- commissioning;
- training;
- optional equipment;
- tooling;
- testing;
- documentation;
- service.
An AI agent cannot reliably support the transaction unless these dependencies are clearly represented.
Agentic Commerce Readiness for industrial B2B must therefore combine:
- product information;
- capability information;
- technical qualification;
- commercial rules;
- evidence;
- workflow design;
- governance.
The Main Components of Agentic Commerce Readiness
1. Business Identity Readiness
The agent must understand who the company is and what commercial role it performs.
This may require clear information about:
- legal company name;
- trading names;
- registration details;
- tax identifiers;
- headquarters;
- operational locations;
- company ownership;
- markets served;
- languages;
- contact points;
- responsible departments.
The website should clearly distinguish whether the company is a:
- manufacturer;
- distributor;
- wholesaler;
- importer;
- integrator;
- authorised representative;
- service provider;
- contract manufacturer;
- rental provider;
- marketplace;
- software provider;
- agent operator.
Typical Problems
- the brand is visible, but the legal entity is unclear;
- several companies operate under one website;
- the company is mistaken for a manufacturer;
- service responsibility is not defined;
- geographic coverage is missing;
- contact ownership is unclear.
Readiness Output
A structured A2A Business Card can provide the company identity and commercial context required by buyer agents.
2. Product Data Readiness
The agent must be able to identify and evaluate individual products.
Product data may include:
- product name;
- manufacturer;
- brand;
- model;
- SKU;
- category;
- variant;
- configuration;
- technical parameters;
- units;
- applications;
- limitations;
- compatibility;
- optional features;
- replacement models;
- related products.
Typical Problems
- one page describes several materially different products;
- product names are inconsistent;
- specification tables use different units;
- optional features are presented as standard;
- outdated models remain active;
- no stable product identifiers exist;
- technical limitations are missing.
Readiness Output
An A2A Product Card can transform product information into a structured, qualifiable and RFQ-ready asset.
3. Capability Data Readiness
Many B2B suppliers sell capabilities rather than fixed products.
The agent may need to understand whether the supplier can:
- manufacture;
- process;
- convert;
- integrate;
- install;
- repair;
- test;
- customise;
- store;
- fulfil;
- maintain.
Capability data may include:
- process;
- technology;
- equipment;
- supported materials;
- input requirements;
- output format;
- dimensional range;
- tolerances;
- capacity;
- minimum project size;
- maximum volume;
- quality procedures;
- required files;
- tooling;
- validation;
- lead time;
- exclusions.
Typical Problems
- the website says “custom solutions” without defining capabilities;
- production limits are not stated;
- required input files are unclear;
- minimum project size is missing;
- the supplier’s machinery is listed without explaining possible outcomes;
- capability claims are unsupported.
Readiness Output
An A2A Capability Card can describe what the supplier can actually deliver.
4. Commercial Data Readiness
An AI system needs to understand the commercial conditions surrounding the offer.
Commercial data may include:
- price;
- pricing method;
- currency;
- price validity;
- tax basis;
- minimum order quantity;
- order increments;
- stock status;
- production lead time;
- delivery time;
- delivery area;
- transport cost;
- Incoterms;
- payment terms;
- warranty;
- service;
- installation;
- commissioning;
- training;
- spare parts.
Not every exact value must be public.
Where a fixed price cannot be published, the company should explain:
- how the price is calculated;
- which variables affect it;
- what information the buyer must provide;
- what is included in the quotation;
- how long the quotation remains valid.
Typical Problems
- prices have no validity date;
- delivery cost is not explained;
- MOQ is missing;
- availability is described as “fast” without a defined period;
- standard and optional scope are mixed;
- net and gross prices are not distinguished;
- payment conditions are omitted.
Readiness Output
Commercial fields should be incorporated into Product Cards, Capability Cards and Direct RFQ workflows.
5. Technical Qualification Readiness
The agent must be able to determine whether an offer is suitable for a specific requirement.
This requires explicit qualification logic.
Qualification fields may include:
- application;
- product dimensions;
- weight;
- material;
- production speed;
- operating temperature;
- environmental conditions;
- electrical supply;
- pneumatic supply;
- required capacity;
- annual demand;
- delivery destination;
- expected commissioning date;
- integration requirements;
- required certificates.
Typical Problems
- the page does not explain what information is required;
- the same product is recommended for incompatible applications;
- critical operating limits are missing;
- no distinction exists between mandatory and optional buyer data;
- qualification depends entirely on a salesperson’s knowledge.
Readiness Output
The company should define:
- mandatory buyer inputs;
- optional buyer inputs;
- suitability rules;
- exclusion rules;
- alternative recommendations;
- human review triggers.
6. Documentation and Evidence Readiness
AI systems and procurement teams may require supporting evidence before qualifying a supplier or product.
Relevant documents may include:
- technical datasheets;
- manuals;
- declarations;
- certificates;
- test reports;
- safety information;
- drawings;
- quality documents;
- compliance documents;
- warranty terms;
- manufacturer authorisations;
- case studies.
Each document should be associated with:
- the correct company or product;
- the document owner;
- the issue date;
- the version;
- the validity status;
- the language;
- the applicable market.
Typical Problems
- documents are available but not linked to specific products;
- expired certificates remain published;
- document versions are unclear;
- manufacturer and distributor declarations are mixed;
- technical files are accessible only after manual contact;
- claims cannot be traced to evidence.
Readiness Output
A structured evidence layer should connect each important claim with an identifiable source.
7. RFQ Readiness
A company is not agentic-commerce ready if the only available action is a generic contact form.
A structured RFQ process should explain:
- what information the buyer must provide;
- which fields are mandatory;
- which fields are optional;
- which documents may be attached;
- how the request will be evaluated;
- who receives the request;
- what happens next;
- when a response can be expected.
A Direct RFQ may include:
- RFQ identifier;
- buyer identity;
- product or capability required;
- quantity;
- technical specifications;
- required delivery date;
- delivery location;
- documentation requirements;
- installation requirements;
- commercial expectations;
- response deadline.
Typical Problems
- enquiries contain only a name and email address;
- no product identifier is passed to sales;
- buyers omit critical dimensions;
- the supplier must repeatedly request missing data;
- supplier quotations use incompatible structures;
- RFQ ownership is unclear.
Readiness Output
A Direct RFQ Card can create a complete and reusable request structure.
8. Workflow Readiness
Agentic commerce requires defined processes after an action is initiated.
The company should determine:
- which system receives the request;
- who owns the opportunity;
- how missing data is requested;
- when technical review is required;
- when pricing can be generated;
- when human approval is mandatory;
- how documents are shared;
- how the quotation is recorded;
- how follow-up is managed.
Example Workflow
- An agent identifies a relevant product.
- The agent submits application and quantity data.
- The system validates mandatory fields.
- Missing technical information is requested.
- The request is routed to the appropriate department.
- A human or approved system confirms suitability.
- A quotation is prepared.
- The buyer receives the quotation and evidence package.
- Further action requires authorised approval.
Typical Problems
- no owner exists for agent-generated enquiries;
- technical and commercial teams use different data;
- no validation occurs before the RFQ reaches sales;
- response times are undefined;
- agent actions are not recorded;
- exceptions have no escalation path.
9. Action Readiness
The company should define which actions an AI agent may perform.
Possible actions include:
- search products;
- compare products;
- request technical information;
- request documentation;
- check availability;
- submit an RFQ;
- request a sample;
- arrange testing;
- schedule a consultation;
- prepare an order;
- reserve stock;
- initiate a transaction.
For each action, the company should define:
- required inputs;
- permitted users or agents;
- authentication requirements;
- response format;
- response time;
- approval status;
- transaction limit;
- escalation procedure.
The ability to perform an action does not mean that every action should be automated.
The appropriate level depends on the product, commercial risk and organisational maturity.
10. Governance Readiness
Governance defines the boundaries within which AI systems can operate.
It should cover:
- data ownership;
- publication responsibility;
- update responsibility;
- permissions;
- authentication;
- commercial limits;
- human approval;
- confidentiality;
- security;
- logging;
- monitoring;
- escalation;
- archival procedures.
Important Governance Questions
- Who is responsible for product data?
- Which prices may be published?
- How long is a price valid?
- Can the agent confirm stock?
- Can the agent submit an RFQ?
- Can it reserve a product?
- Can it place an order?
- What is the maximum transaction value?
- When is human approval required?
- How are actions recorded?
- What happens when the agent is uncertain?
- Who handles a dispute or error?
Without governance, agentic commerce may create operational and commercial risk.
The Agentic Commerce Readiness Model
Direct RFQ uses a progressive readiness model.
A company can begin with foundational improvements and expand over time.
Level 1: Digitally Visible
The company and its core offers are available on crawlable web pages.
Basic information can be discovered through search engines and AI systems.
Typical Characteristics
- company website;
- product pages;
- contact details;
- basic technical descriptions;
- searchable content.
Main Limitation
The information may still be incomplete, inconsistent or difficult to qualify.
Level 2: Structured
Company, product and capability information is organised into consistent fields and page structures.
Typical Characteristics
- clear product names;
- stable identifiers;
- standard specification tables;
- consistent units;
- structured company information;
- clear categories.
Main Benefit
AI systems can interpret the information with less ambiguity.
Level 3: Comparable
Products and offers contain consistent criteria that allow meaningful comparison.
Typical Characteristics
- technical attributes;
- variant comparisons;
- pricing scope;
- MOQ;
- lead time;
- availability;
- delivery conditions;
- warranty information.
Main Benefit
The agent can compare relevant alternatives using business-relevant criteria.
Level 4: Qualifiable
The company publishes the conditions required to determine suitability.
Typical Characteristics
- qualification questions;
- application requirements;
- limitations;
- required buyer inputs;
- exclusions;
- alternative options;
- evidence.
Main Benefit
The agent can determine whether the product or supplier is relevant before contacting sales.
Level 5: RFQ-Ready
The buyer or agent can submit a structured and sufficiently complete request for quotation.
Typical Characteristics
- Direct RFQ fields;
- mandatory inputs;
- product identifiers;
- document requirements;
- delivery requirements;
- response expectations.
Main Benefit
The company receives better-quality enquiries and can respond more efficiently.
Level 6: Operationally Executable
Selected actions can be initiated through digital workflows.
Typical Characteristics
- product-specific forms;
- document requests;
- availability requests;
- test booking;
- RFQ routing;
- workflow validation;
- structured responses.
Main Benefit
The buying and selling process becomes more efficient and partially automatable.
Level 7: Agent Connected
The company provides machine-readable resources or interfaces that support agent interaction.
Typical Characteristics
- structured JSON;
- product feeds;
- capability feeds;
- RFQ feeds;
- APIs;
- authenticated resources;
- agent endpoints.
Main Benefit
External or internal agents can exchange business information more directly.
Level 8: Governed Transactional Readiness
Agents may perform selected commercial actions within predefined limits.
Typical Characteristics
- permissions;
- authentication;
- financial limits;
- approval workflows;
- audit logs;
- human escalation;
- transaction monitoring.
Main Benefit
The company can support controlled agent-assisted transactions without losing governance.
A company does not need to reach Level 8 immediately.
For many B2B organisations, achieving Levels 4 to 6 can already provide substantial commercial value.
Buyer Agent Readiness
A buyer agent acts on behalf of the purchasing organisation or user.
It may need to:
- interpret demand;
- define requirements;
- discover suppliers;
- compare offers;
- verify evidence;
- prepare an RFQ;
- collect responses;
- recommend a decision.
To support buyer agents, the supplier should publish:
- clear company identity;
- complete product data;
- commercial scope;
- qualification rules;
- delivery conditions;
- evidence;
- structured actions.
The buyer agent should be able to understand not only what the supplier sells, but also:
- when the offer is suitable;
- when human consultation is required;
- what information is still missing;
- what the supplier cannot provide.
Supplier Agent Readiness
A supplier agent represents or supports the selling organisation.
It may:
- respond to product questions;
- identify the correct product;
- qualify an enquiry;
- request missing information;
- provide approved documents;
- prepare a quotation draft;
- route the enquiry;
- monitor response deadlines.
Supplier agent readiness requires:
- verified product data;
- approved commercial rules;
- current availability information;
- document ownership;
- escalation rules;
- authority boundaries;
- logging.
The supplier agent should not be allowed to invent:
- technical parameters;
- availability;
- prices;
- delivery commitments;
- regulatory claims;
- warranty conditions.
When information is unavailable or uncertain, the agent should escalate the request to a responsible person.
Human-in-the-Loop Commerce
Agentic commerce does not require removing people from the commercial process.
In many B2B environments, the most reliable model is human-in-the-loop commerce.
The AI may:
- collect information;
- identify missing fields;
- structure the RFQ;
- compare standard data;
- prepare a draft response.
A human may remain responsible for:
- technical approval;
- final pricing;
- contractual acceptance;
- credit decisions;
- custom engineering;
- safety-critical recommendations;
- regulatory confirmation;
- transaction approval.
The objective is not complete automation at any cost.
The objective is to automate repeatable work while preserving human control where expertise, responsibility or judgement is required.
Agentic Commerce and Direct RFQ
Direct RFQ provides the demand and response structure required for agent-assisted B2B transactions.
A buyer agent may create a Direct RFQ Card containing:
- the required product or capability;
- technical requirements;
- quantity;
- delivery location;
- required date;
- documentation needs;
- response deadline;
- evaluation criteria.
A supplier agent may then:
- identify a relevant Product Card or Capability Card;
- evaluate initial suitability;
- identify missing information;
- request clarification;
- prepare a structured response;
- escalate the opportunity for approval.
This creates a more consistent exchange between demand and supply.
Agentic Commerce and A2A Cards
A2A Cards provide the information layer supporting agentic commerce.
A2A Business Card
Explains who the supplier is.
A2A Product Card
Explains what the supplier sells.
A2A Capability Card
Explains what the supplier can perform.
Direct RFQ Card
Explains what the buyer needs.
A2A Agent Card
Explains what a functioning agent can do and how another system may interact with it.
Together, these cards create a structured relationship between:
- buyer;
- supplier;
- product;
- capability;
- request;
- agent;
- action.
Agentic Commerce and A2O
A2O, or Agent-to-Agent Optimization, is the process of preparing information and workflows for use by AI agents.
Agentic Commerce Readiness is the broader operational state that results from combining:
- structured data;
- A2O;
- A2A Cards;
- qualification logic;
- action design;
- workflow integration;
- governance.
A2O focuses on optimization.
Agentic Commerce Readiness focuses on whether the organisation can reliably participate.
Agentic Commerce Readiness Assessment
A Direct RFQ readiness assessment examines the company’s current ability to support AI-assisted buying and selling.
The assessment may cover the following areas.
Company and Entity Assessment
We review:
- legal identity;
- trading names;
- company roles;
- locations;
- markets;
- brands;
- ownership relationships;
- contact points;
- trust signals.
Website and Content Assessment
We review:
- page architecture;
- crawlability;
- product pages;
- capability pages;
- internal linking;
- technical content;
- FAQs;
- document access;
- calls to action.
Product Data Assessment
We review:
- naming;
- identifiers;
- categories;
- specifications;
- units;
- variants;
- applications;
- limitations;
- compatibility;
- commercial data.
Capability Assessment
We review:
- processes;
- technologies;
- equipment;
- capacity;
- materials;
- dimensions;
- tolerances;
- service scope;
- qualification conditions.
Commercial Readiness Assessment
We review:
- price structure;
- currency;
- validity;
- MOQ;
- availability;
- lead time;
- delivery;
- payment;
- warranty;
- installation;
- service.
Documentation Assessment
We review:
- datasheets;
- declarations;
- certificates;
- manuals;
- tests;
- drawings;
- quality records;
- version control;
- document ownership.
RFQ Assessment
We review:
- current contact forms;
- qualification questions;
- required buyer inputs;
- RFQ routing;
- response format;
- expected response times;
- escalation.
Workflow Assessment
We review:
- process ownership;
- validation;
- technical review;
- pricing approval;
- document delivery;
- quotation preparation;
- follow-up;
- exception management.
Governance Assessment
We review:
- data ownership;
- permissions;
- approval rules;
- transaction limits;
- security;
- authentication;
- auditability;
- escalation;
- archival procedures.
The Agentic Commerce Readiness Process
1. Define the Business Use Case
We identify where agentic commerce can create practical value.
Possible use cases include:
- product discovery;
- supplier discovery;
- RFQ generation;
- technical qualification;
- document requests;
- quotation preparation;
- product recommendation;
- order preparation;
- service booking.
The project should begin with a defined business objective rather than general automation.
2. Identify the Relevant Entities
We map:
- companies;
- brands;
- products;
- models;
- capabilities;
- documents;
- locations;
- contacts;
- systems;
- agents;
- workflows.
This reduces ambiguity and creates a clear data structure.
3. Audit Existing Information
We review:
- websites;
- catalogues;
- product databases;
- ERP data;
- CRM data;
- PIM data;
- spreadsheets;
- technical files;
- price lists;
- forms;
- internal procedures.
The purpose is to identify what can already be reused and what must be improved.
4. Conduct a FUCTEG Assessment
The current environment is evaluated as:
- Findable;
- Understandable;
- Comparable;
- Trustworthy;
- Executable;
- Governable.
The assessment identifies the most important readiness gaps.
5. Structure the Information
We define:
- entity identifiers;
- product attributes;
- capability attributes;
- commercial fields;
- evidence fields;
- qualification rules;
- actions;
- governance fields.
6. Develop A2A Cards
Where appropriate, we prepare:
- A2A Business Cards;
- A2A Product Cards;
- A2A Capability Cards;
- Direct RFQ Cards;
- agent business context.
7. Design Qualification Logic
We define:
- required buyer inputs;
- optional inputs;
- decision rules;
- unsuitable conditions;
- alternative recommendations;
- human review triggers.
8. Design Agent Actions
We define which actions are possible.
For each action, we determine:
- input requirements;
- permission requirements;
- output structure;
- responsible department;
- approval requirements;
- escalation procedure.
9. Prepare the Machine-Readable Layer
Depending on the project, this may include recommendations for:
- schema markup;
- JSON-LD;
- public JSON files;
- product feeds;
- capability feeds;
- RFQ feeds;
- API fields;
- agent-accessible resources.
10. Define Governance
We establish:
- data ownership;
- update responsibility;
- validity periods;
- permissions;
- transaction limits;
- human approval;
- audit requirements;
- escalation;
- maintenance schedule.
11. Launch a Pilot
A pilot may include:
- one company profile;
- one flagship product;
- one capability;
- one RFQ workflow;
- one defined agent action.
The pilot can be tested before expansion.
12. Scale Across the Organisation
After validating the model, it can be extended to:
- additional products;
- categories;
- capabilities;
- markets;
- languages;
- departments;
- systems;
- agent workflows.
Typical Deliverables
A typical Agentic Commerce Readiness project may include:
- readiness assessment;
- FUCTEG scorecard;
- entity map;
- product data gap analysis;
- capability data gap analysis;
- commercial data review;
- documentation register recommendations;
- A2A Card architecture;
- Direct RFQ structure;
- buyer input requirements;
- qualification logic;
- action map;
- workflow map;
- permissions matrix;
- human approval rules;
- escalation model;
- governance framework;
- machine-readable data recommendations;
- implementation roadmap;
- pilot project proposal.
Example Readiness Packages
Company Readiness Package
Designed for companies that need to clarify their digital identity and supplier role.
May include:
- entity analysis;
- A2A Business Card;
- company role classification;
- market coverage;
- trust structure;
- contact routing;
- governance fields.
Product Readiness Package
Designed for a flagship product or product family.
May include:
- A2A Product Card;
- technical attributes;
- commercial fields;
- qualification logic;
- evidence layer;
- Direct RFQ fields;
- action design.
Capability Readiness Package
Designed for manufacturers, service providers and contract suppliers.
May include:
- A2A Capability Card;
- process structure;
- capacity data;
- qualification conditions;
- evidence;
- RFQ requirements;
- workflow recommendations.
RFQ Readiness Package
Designed for companies that want to receive or publish better purchasing requests.
May include:
- RFQ field architecture;
- mandatory and optional inputs;
- response structure;
- supplier qualification fields;
- document requirements;
- enquiry routing;
- escalation.
Agentic Commerce Pilot
Designed for companies that want to test one practical use case.
The pilot may focus on:
- product qualification;
- quotation preparation;
- document requests;
- supplier matching;
- buyer-agent enquiries;
- sales-agent routing.
Benefits of Agentic Commerce Readiness
Better Discoverability
AI systems can more easily locate the correct company, product and capability.
Better Understanding
Clear identities, attributes, units and relationships reduce ambiguity.
Better Product Matching
Qualification logic improves the match between buyer requirements and supplier offers.
Better Supplier Selection
Structured business and capability data help buyer agents identify relevant suppliers.
Better RFQs
Buyers and agents submit more complete and useful enquiries.
Better Sales Efficiency
Sales teams spend less time collecting basic information and correcting incomplete requests.
Better Data Reuse
Verified data can support:
- websites;
- product catalogues;
- sales teams;
- AI assistants;
- procurement platforms;
- feeds;
- partner portals;
- agent workflows.
Better Control
Permissions, approval rules and transaction limits prevent uncontrolled automation.
Better Auditability
Structured actions and ownership make it easier to review how a decision or transaction was prepared.
Risks of Entering Agentic Commerce Without Preparation
Agentic commerce can create value, but poorly prepared implementation can create risk.
Potential problems include:
- incorrect product recommendations;
- outdated prices;
- false availability;
- incomplete technical qualification;
- unauthorised commitments;
- inconsistent documentation;
- data leakage;
- unclear responsibility;
- missing human approval;
- unrecorded actions;
- reputational damage.
Readiness should therefore be developed before high-autonomy actions are introduced.
The company should begin with:
- verified data;
- limited use cases;
- clear ownership;
- human supervision;
- measurable actions;
- defined boundaries.
What Agentic Commerce Readiness Does Not Guarantee
Agentic Commerce Readiness improves a company’s ability to participate in AI-assisted commercial processes.
It does not guarantee:
- selection by every buyer agent;
- inclusion in every AI answer;
- a specific search ranking;
- automatic sales growth;
- compatibility with every platform;
- successful technical qualification;
- completion of a transaction;
- legal or regulatory compliance.
Readiness cannot replace:
- accurate product data;
- real availability;
- reliable service;
- technical expertise;
- commercial responsibility;
- contractual review;
- security assessment;
- regulatory verification.
AI agents should operate on approved information and within defined authority.
Frequently Asked Questions
What is Agentic Commerce Readiness?
Agentic Commerce Readiness is the ability of a company to support AI-assisted product discovery, supplier qualification, RFQ preparation and controlled commercial actions.
What is agentic commerce?
Agentic commerce is a model in which AI agents support or perform selected buying and selling activities within a defined mandate.
Is agentic commerce fully autonomous?
Not necessarily.
Agentic commerce may range from AI-assisted recommendations to controlled transactional actions.
Many B2B implementations will continue to require human approval.
Does Agentic Commerce Readiness require an AI agent?
No.
A company can begin by preparing its information, qualification logic, RFQ process and governance before deploying an agent.
Does it require an API?
No.
The first stage may use structured HTML pages, clear forms, A2A Cards and well-defined workflows.
APIs and agent endpoints can be added later.
Is a chatbot enough?
No.
A chatbot interface does not automatically provide reliable product data, qualification logic, commercial rules, permissions or governance.
What is the difference between A2O and Agentic Commerce Readiness?
A2O is the process of optimizing information and workflows for AI agents.
Agentic Commerce Readiness is the broader state in which the company can support agent-assisted commercial processes reliably.
What is the role of A2A Cards?
A2A Cards provide structured information about companies, products, capabilities, agents and purchasing requirements.
They can form the information layer for agentic commerce.
What is a buyer agent?
A buyer agent acts on behalf of a buyer or procurement team.
It may search, compare, qualify and prepare purchasing actions.
What is a supplier agent?
A supplier agent supports the selling organisation.
It may answer questions, qualify enquiries, provide approved information and prepare quotation drafts.
Can an agent place an order?
Only when the company has explicitly authorised that action and defined the applicable limits, approval rules and security requirements.
Should prices be public?
Not always.
Where fixed pricing is not possible, the company should publish the pricing method and the inputs required for a quotation.
Can confidential information remain private?
Yes.
Public pages should contain only approved information.
Sensitive data may remain in authenticated systems and be shared according to permissions.
How should uncertain information be handled?
The agent should clearly state that the information requires confirmation and escalate the matter to a responsible person.
It should not invent specifications, prices, availability or commercial commitments.
Which industries benefit most?
Agentic Commerce Readiness is especially relevant for:
- manufacturing;
- industrial machinery;
- packaging;
- components;
- chemicals;
- raw materials;
- contract manufacturing;
- engineering;
- maintenance;
- logistics;
- wholesale and distribution.
Is Agentic Commerce Readiness a certification?
No.
Direct RFQ provides an independent working framework and assessment methodology.
It is not an ISO, IEC, CEN or government certification.
Can readiness be developed gradually?
Yes.
A company can begin with one product, one capability or one RFQ process and expand after testing the model.
Start with a Controlled Pilot
A company does not need to automate its entire commercial process.
A practical pilot may include:
- one clearly defined business use case;
- one flagship product;
- one A2A Product Card;
- one structured RFQ process;
- one agent-assisted action;
- one human approval point;
- one responsible team.
For example, a pilot may allow an AI system to:
- identify the correct product;
- collect technical requirements;
- verify mandatory RFQ fields;
- prepare an enquiry;
- route it to a salesperson;
- wait for human approval.
This provides measurable value without giving the system uncontrolled transactional authority.
The pilot can then be evaluated using:
- enquiry completeness;
- qualification accuracy;
- response time;
- sales workload;
- conversion quality;
- error rate;
- escalation frequency.
Prepare Your Company for the Agentic Market
Move from Visibility to Controlled Commercial Participation
The next stage of B2B digital commerce will not be based only on whether a company appears in search results.
It will also depend on whether AI systems can understand the offer, verify its conditions, qualify its suitability and initiate an approved business process.
Agentic Commerce Readiness helps your company prepare:
- reliable business data;
- structured product information;
- qualification logic;
- Direct RFQ workflows;
- actions;
- permissions;
- human approval;
- governance.
Begin with one practical use case and develop a repeatable model for future agent-assisted commerce.
Primary CTA: Request an Agentic Commerce Readiness Assessment
Secondary CTA: Start an Agentic Commerce Pilot
Additional CTA: Explore A2O Optimization
Start a Direct RFQ Project
Opening
Prepare your company, product, capability or purchasing workflow for AI-assisted B2B discovery and agentic commerce.
Project types
You can contact Direct RFQ about:
- an A2A Product Card;
- an A2A Business Card;
- an A2A Capability Card;
- a Direct RFQ Card;
- an A2O readiness review;
- an agentic commerce assessment;
- a structured data or card library project.