Prompt-first dealmaking and semantic search are streamlining due diligence, allowing M&A professionals to focus on strategic value rather than dredging through documents.
Historically, data room search has been highly dependent on keyword searches and institutional knowledge built over years. If a PE sponsor was looking for specific change-of-control clauses in a €2 million add-on acquisition, an advisor or founder had to manually comb through hundreds of pages. “Whether it is an acquisition, capital raise, IPO or procurement process, success has often come down to how effectively teams can work through large volumes of documentation under time pressure,” explains Ansarada MD Justin Smith.
Although virtual data rooms improved security, organisation and document sharing, the fundamental nature of the task remained unchanged. Deal teams continued to dedicate endless hours to manually searching through folders, examining documents individually, and piecing together information across thousands of files.
Read also: AI data room vs traditional data room: what's the difference in 2026?
In Belgium’s M&A industry, independent entrepreneurs and family-owned businesses – which still make up the majority of the local market – are often caught off guard by the sheer administrative burden of a modern transaction. “A single transaction can generate thousands of contracts, financial statements, compliance records, operational reports and supporting documents, all of which need to be reviewed and understood within increasingly compressed timelines,” Justin notes.
As regulatory requirements and stakeholder expectations increase, so does the pressure to process more information with the same level of rigour. “...but even the best teams can only move so fast across thousands of documents spread over multiple workstreams,” Justin points out.
However, generative artificial intelligence is shifting this paradigm.
From processors to purpose drivers
Through semantic search, AI is turning the notoriously gruelling due diligence process into a much faster and more manageable phase of the transaction. “This is the move towards prompt-first dealmaking; the ability to interrogate an entire document set in natural language and get instant, sourced answers, and it is reshaping how teams move through every stage of a transaction,” Justin reveals. Rather than simply hunting for exact words, the AI understands the intent and meaning behind a buyer's question.
He stresses that the impact extends far beyond speed:
“Less time is spent finding information and more time is spent understanding it, testing assumptions, digging into risk and focusing on the decisions that ultimately shape outcomes. In that sense, AI does not just help deal teams work faster; it helps them operate at a higher level.”
The growing adoption of Ansarada’s AI assistant, Ask AiDA, is evidence of this. Educated on more than 60,000 transactions, AiDA enables users to interact with an entire document set using natural language, helping them surface relevant information, summarise complex materials and identify potential issues without manually reviewing every document themselves. “The most successful transactions will still rely on human judgement, commercial understanding and strategic thinking,” Justin elaborates. “What AI can do is reduce the friction that has traditionally existed between professionals and the information they need to make those judgements.”
Humans still hold the heavyweight
Trust has always been the foundation of a successful transaction, and it will be just as fundamental when working with AI. “A single decision can carry serious commercial, legal and reputational weight, which is why transparency and governance cannot be treated as an afterthought,” Justin emphasises.
He cautions that every answer an AI generates should trace back to its source documentation and that it must still operate within the same security, permission, and compliance frameworks that govern the deal itself. “An answer no one can verify is of no use in a transaction.”
As such, human expertise will remain detrimental in every deal, as negotiation, experience and judgement cannot be automated.
