For most of commercial history, every transaction in Pakistan, as everywhere else, had a human at each end. A shopkeeper in Raja Bazaar haggled with a customer, a buyer in Karachi compared quotes by phone, and a supplier in Faisalabad closed a deal over chai. Even as Daraz, Foodpanda, and mobile wallets such as JazzCash and Easypaisa moved commerce online, software only assisted people, who still made the final decision. That assumption is now breaking down. AI agents are beginning to buy, sell, negotiate, and settle with other AI agents, often with no human watching the exchange.
Until recently, AI was an instrument. A recommendation engine suggested product, a chatbot answered customer queries, and an algorithm adjusted prices. Agentic AI changes this relationship. A personal agent can be told, “Find me the best flight from Islamabad to Dubai under Rs. 150,000 and book it.” On the other side, an airline’s or travel portal’s agent has its own goals: fill seats, protect margins, and manage inventory. The two systems negotiate terms, check constraints, and complete the purchase. This is machine-to-machine commerce, in which software acts as a genuine counterparty rather than a tool.
Early versions already exist. Algorithmic trading has long had bots trading against bots, and online ad auctions settle in milliseconds between automated bidders. What is new is breadth and flexibility. Language-capable agents can handle open-ended work like procurement, scheduling, contract drafting, and customer disputes, not just narrow, predefined tasks.
The benefits are easy to see, especially for a country like Pakistan with a large base of small businesses. Negotiations that take humans days of calls and WhatsApp messages can finish in seconds. A small garment exporter in Sialkot or a wholesaler in Lahore’s Azam Market could handle deals that were never worth the time before, since the cost of each deal falls sharply. A human buyer compares a handful of suppliers, while an agent can compare thousands, so the buyer ends up with a better match. An agent that knows your budget and preferences can also filter the market for you, which shifts some bargaining power toward consumers, who in Pakistan often face uneven pricing and limited transparency. Micro-transactions that were impractical for humans, such as paying a few rupees for a data query or a few seconds of computing power, become viable when software handles both sides. With the growth of digital wallets and Raast instant payments, the payment rails for this kind of commerce are gradually falling into place.
The risks are just as real. Research on pricing algorithms has shown that independent systems can learn to keep prices high without any explicit agreement. If AI sellers observe and respond to each other at machine speed, tacit collusion could emerge without any human deciding to fix prices. Pakistan already struggles with cartel behavior in sectors like sugar, cement, and flour, and the Competition Commission of Pakistan relies on evidence of human coordination. Proving collusion between algorithms is a far harder task. Interacting agents can also amplify each other’s mistakes, creating sudden price swings or cascading failures, and such effects could appear in retail, logistics, and credit where markets were once slow and stable.
Manipulation is another concern. An AI agent can be deceived. A dishonest seller’s agent might embed hidden instructions in a product listing to steer a buyer’s agent into a bad deal, so security becomes as important as price. Accountability is equally unclear. If your agent agrees to terms you would never have accepted, who is liable: the user, the developer, or the platform? Pakistani contract law, like most legal systems, assumes a person who gives consent, and that assumption becomes uncertain when software acts on someone’s behalf with real autonomy. There is also the question of power. A company controlling the dominant agent platform could quietly favor partners who pay for placement, so consumers would believe their agent works for them while its recommendations are shaped elsewhere. For a market where consumer protection is still developing, this deserves attention.
For anyone studying marketing and consumer behavior, the most disruptive shift may be in how brands persuade. Marketing has always aimed at human psychology: emotion, family influence, brand loyalty, celebrity endorsement, and festive promotions around Ramadan and Eid. An AI buyer has no childhood memories of a brand and does not respond to a cricket star’s endorsement or a flashy billboard. If agents increasingly make purchase decisions, Pakistani brands will need to persuade machines as well as people. That means clean structured data, verifiable reviews, transparent pricing, and measurable reliability. The competitive edge moves from grabbing attention to being easy for an agent to evaluate and trust. Brand still matters, because humans choose which agent to delegate to and what rules to give it, but the battleground moves upstream. Consumer behavior will change too. People will delegate more routine decisions, such as grocery orders, utility payments, and travel bookings, and the psychology of trust will extend to software: how much autonomy are we willing to grant our agents, and what makes us comfortable doing so? In a society where trust is traditionally built through personal relationships and word of mouth, this is a significant cultural shift.
Several foundations are needed before this world works well. Agents need verifiable identity and clear authorization showing who they represent and what they may commit to, which could be tied to systems like NADRA-verified identity and the State Bank’s digital payment framework. The law must define who is responsible when an agent errs or is manipulated. Transactions between agents should be logged and explainable so disputes can be resolved. Regulators such as the Competition Commission and the State Bank need tools to detect algorithmic collusion and platform self-preferencing. Users should also be able to set spending limits, require approval above certain amounts, and review what their agents have done.
AI doing business with AI is the next step in a long trend of automating commerce, bringing real efficiency gains and real new dangers. The question is not whether machines will transact with each other, since they already do. It is whether Pakistan builds the rules, safeguards, and transparency that keep these systems working for people. The businesses, regulators, and consumers who adapt early will shape that outcome, while those who treat it as a distant possibility may find the market has already moved on without them.