The diligence process will be partially automated, with an AI agent on the buyer's side generating follow-up questions that are then proactively answered by an agent on the seller's side. This will dramatically speed up information exchange and reduce manual work for deal teams.

A single AI agent cannot solve a complex enterprise task like procurement. True automation requires a multi-agent system where specialized agents (e.g., for contracts, inventory, negotiation) coordinate and share information, mirroring how human departments collaborate to get a job done.

Leading data science at ad-tech firm AppNexus revealed that buy-side and sell-side teams were inadvertently sabotaging each other. The solution was a "marketplace czar" role focused on optimizing the entire ecosystem, for instance, by creating a unified revenue forecast that recognized the deep coupling between both sides.

The current human-to-agent interaction is a transition phase. The future involves companies deploying buyer agents that interact with seller agents to research, negotiate, and even commit to purchases, removing humans from most of the process.

The sales process will evolve from human-to-human or human-to-agent interactions to a world where company 'buyer agents' and 'seller agents' negotiate directly. Humans will only step in for the 'final mile' to provide the ultimate sign-off after the AI has conducted the research and presented the optimal solution.

A significant portion of B2B contracts will soon be negotiated and executed by autonomous AI agents. This shift will create an entirely new class of disputes when agents err, necessitating automated, potentially on-chain, systems to resolve conflicts efficiently without human intervention.

A key fear of machine-to-machine commerce is that it will optimize solely for the lowest price. However, the 'human in the loop' model ensures the agent acts as a curator, presenting options for a final human decision. This preserves the importance of brand, aesthetics, and subjective value beyond pure cost.

Enterprises often don't negotiate invoices below a certain threshold (e.g., $50K) because they lack the human capacity. AI agents can autonomously handle these negotiations at scale, capturing savings that were previously left on the table. The risk is low because the alternative was zero negotiation.

Ditch hostage negotiation tactics. Instead, transparently state the four levers that earn discounts: volume commitments, faster payment, longer contracts, and predictable deal timing. This transforms negotiation from a battle into a collaborative trade, building trust and creating more valuable, predictable deals.