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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.

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AI isn't necessarily leading PE funds to do more deals. Instead, it compresses the initial, time-consuming phase of diligence from weeks to a single day, allowing teams to reallocate their energy toward deeper debate on core value creation drivers.

AI diligence has replaced cybersecurity as the modern, high-stakes technical hurdle in M&A. Buyers now focus on a company's AI defensibility and roadmap. A lack of a clear AI strategy or a perceived vulnerability to AI disruption can be an existential risk that either kills the deal or severely impacts the valuation.

Instead of delivering static, one-off research reports, use Autoresearch to create dynamic "living memos" for investors and acquirers. An agent constantly chews through new documents and filings, providing clients with an always-current brief via a subscription model.

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.

As consumers use AI to analyze contracts and diagnose problems, sellers will deploy their own AI counter-tools. This will escalate negotiations from a battle between people to a battle between bots, potentially requiring third-party AI arbitrators to resolve disputes.

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.

M&A leaders can feed diligence findings and past deal notes into an enterprise AI tool to quickly generate risk logs and identify key focus areas. This saves significant time that can be reinvested into crucial, high-touch stakeholder alignment and communication.

Auren Hoffman predicts that by late 2026, the initial VC screening process will be automated. A VC's AI agent will "meet" a founder's AI agent to exchange information and assess fit, making the process more efficient before any human interaction occurs.

Actively AI provides each sales account with its own persistent AI agent. This agent maintains context throughout the account's lifecycle, proactively guiding the human seller on next steps and even executing tasks. The core belief is that this model will lead to a sales world where AI agents vastly outnumber human sellers.