AI is giving branded merchandise companies more capacity to create, analyze and respond. The next advantage depends on what business leaders do with that capacity.
A proposal prepared in minutes still needs accurate pricing, available products and dependable delivery. A faster customer response creates value when it helps resolve the problem. The larger opportunity comes when these improvements connect across the business and its partners.
In our industry, customer outcomes depend on the combined expertise of distributors, suppliers, manufacturers and business services firms. AI can help these partners apply their expertise and coordinate the work.
In PPAI Research’s supplier report over the summer, 98% of PPAI 100 suppliers responding to the AI adoption question reported using or testing AI, ranging from informal employee use to formal company strategy.
That raises a question for leadership: What can the business now deliver that it couldn’t deliver as effectively before?
Let Customer Needs Set The Direction
Customer expectations provide the clearest starting point.
Among end buyers participating in PPAI Research’s most recent consumer study, 49% selected better strategic ideas as something that would make a distributor or vendor partner more valuable. That gives AI investment a specific purpose: strengthen the advice customers receive.
Alok Bhat
Director of Research & Public Affairs, PPAI
A customer may arrive with an AI-generated concept or product list already prepared. Our opportunity is to help determine which ideas are suitable and achievable.
That requires understanding the audience, brand, budget and intended outcome. It also requires product knowledge. An attractive image can’t establish physical quality, apparel fit, decoration suitability or delivery feasibility.
AI can help employees explore alternatives and prepare for the conversation. The business creates value by turning that preparation into sound advice and a result the customer can trust.
Build A Connected Business
PPAI Research’s distributor report over the summer highlighted where leaders should look next.
Among PPAI 100 distributors responding to the question about AI applications, 88% reported using AI for sales emails, proposals or presentations, compared with 16% for order entry, purchase order processing or order management. These figures describe reported use rather than effectiveness, but they give leaders a reason to examine how selling connects with fulfillment.
- A proposal may be ready while availability still needs confirmation.
- An order may reach a supplier without essential artwork.
- A service team may need to reconcile conflicting updates from several systems.
The customer experiences the consequences of those handoffs.
Taking an enterprise approach means evaluating how AI supports the whole business. This applies to smaller firms as well as large organizations. The aim is to help teams use dependable information and pass work between systems and partners with fewer gaps.
The information itself needs attention. An inventory connection is useful only when a team knows how current the information is and whether the stock can be committed to the proposed order.
Distributors can keep customer requirements clear from discovery through delivery. Suppliers can make dependable product and production information easier to use. Business services firms can improve information quality and simplify coordination across systems.
AI readiness increasingly depends on how well business partners work together. Those connections could also make expertise more accessible and help companies deliver personalized services that previously required too much manual coordination.
Prepare For AI That Can Act
Agentic AI extends the opportunity from preparing information to carrying out permitted work. An AI agent can pursue a defined goal by planning steps and using tools or business systems to execute them.
For example, an agent could review an incoming request, identify missing specifications, prepare questions and route the completed information to the appropriate team. With suitable connections and authority, it could also monitor an order and flag an emerging delivery problem.
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These applications need testing against the demands of the work. Reliable execution depends on current information, dependable connections and clear responsibilities. NIST’s AI Agent Standards Initiative identifies security and the ability to work across systems as important conditions for wider adoption.
For leaders, the central issue is authority.
A system that prepares an order change has different responsibilities from one that submits it. An agent comparing alternatives should receive only the access and permissions appropriate to its task.
Companies need to define what AI may access, share and execute. Approval limits, records of actions and ways to pause or stop a workflow should be part of the design.
An employee preparing an unreleased launch should know which tools may handle confidential artwork. A team managing orders should know who investigates an exception and approves the response.
Make People & Value Part Of The Design
The industry’s experience is an asset for building better AI capabilities.
Product specialists understand materials and decoration constraints. Sales professionals recognize when a recommendation misses the customer’s objective. Operations teams know which missing details repeatedly cause delays. Their expertise should shape the instructions, checks and exceptions within AI-supported workflows.
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Training should involve actual work. Employees need opportunities to review extracted order details, challenge recommendations and practice escalation decisions. As responsibilities change, leaders should explain what employees will be expected to do and how they will develop those capabilities.
The same clarity is needed around productivity.
Suppose AI reduces quote preparation from 30 minutes to 15 minutes.
- Across 100 quotes, that releases 25 hours of potential capacity.
Its value depends on what follows. Did customers receive quotes sooner? Did employees use the time for better follow-up or additional requests? How much review and correction was necessary?
McKinsey’s 2026 global AI survey highlights the gap between individual productivity gains and broader financial impact. It also identifies workflow redesign as a distinguishing practice among organizations reporting the strongest results.
Leaders need to decide how the business will use the capacity created. A credible assessment includes integration, training, human review, maintenance and ongoing AI costs. It distinguishes available employee time from cash savings and additional revenue.
The measure of progress is what the business achieves with the capacity created.
Give The Next Investment A Clear Purpose
As leaders plan for 2027, AI should earn its place alongside other investments in growth, service and operating performance.
Five steps can make that decision concrete:
- Choose a meaningful outcome. Identify a recurring customer or operating problem. Establish current performance, the desired improvement and the person accountable for the result.
- Connect the necessary work. Follow the process across teams and relevant partners. Establish reliable inputs, shared definitions and clear handoffs before expanding automation.
- Equip the people involved. Bring experienced employees into the design. Provide approved tools, practice relevant to their roles and opportunities to assess output quality.
- Govern information and actions. Define permissions, approval limits and accountability. Establish how problems will be detected and addressed.
- Prove value and expand. Set outcome measures, include the full costs and agree on a review date. Use the evidence to decide what should scale, change or stop.
A distributor could begin with more complete quote requests. A supplier could address missing order information. A business services firm could help partners share dependable status updates. Each can start with a manageable improvement while developing a broader capability.
For branded merchandise, the opportunity is to make expertise easier to apply and customer commitments more dependable. The next investment should answer a clear leadership question:
What will this investment enable us to deliver better and what evidence will show that it worked?
Bhat is director of research and public affairs at PPAI.
