By Jerome Pottier, EMEA Chief Revenue Officer Datasite
For decades, M&A trained junior talent through repetition. Analysts learned by building the materials, scrubbing the documents and working through the first pass on the detail. AI is improving that experience by taking more of the repetitive admin and drudgery off junior teams’ plates, from document review and search to summarisation and first-draft analysis.
That change does more than save time. It gives junior professionals more room to focus on higher-value work earlier in their careers. They still need rigour, speed and sound judgement, but they can spend more of their time developing those strengths instead of getting stuck in manual administrative tasks.
The Data Is Already Clear
The labour market already points in this direction. A 2026 Institute of Student Employers survey shows that 87 per cent of employers expect AI to reshape graduate and apprentice roles within three years, while 43 per cent said those roles have already changed even though formal job descriptions have not. The same survey found growing demand for critical thinking, AI literacy, communication and adaptability.
That pattern maps directly onto dealmaking. As AI takes on more of the routine tasks that have long absorbed junior bankers, lawyers and analysts, firms can create more space for early-career talent to build judgement, communication skills, commercial reasoning and the ability to verify output under pressure.
What This Means for M&A
M&A has always rewarded precision under pressure. AI does not change that. It changes how teams get there. The clearest impact has emerged in due diligence, where AI now helps organise files, surface anomalies, accelerate search and summarisation, and automate labour-intensive tasks such as redaction and translation.
The next shift is infrastructural. In April 2026, Datasite launched an MCP server that lets AI assistants such as Claude, ChatGPT and Copilot work directly on live deal content inside the VDR, without exporting documents into external tools. Permissions, audit trails and governance controls remain intact throughout the workflow.
That matters because it moves AI from the edge of the workflow into the centre of execution. It removes the long-standing trade-off between using AI and maintaining control of confidential documents. Once AI works inside the governed environment, firms can start treating it as part of the deal stack rather than a side tool.
How will this impact M&A deals
Until recently, firms faced an obvious constraint. To use AI on deal documents, teams often had to export sensitive materials from the secure deal environment into external tools. That created uncontrolled copies, weakened auditability and introduced a level of exposure that serious deal teams could not accept.
Direct integration changes that model. AI assistants can now analyse authorised content in place, compare versions, surface clauses, draft diligence summaries and help answer buyer questions while staying inside the same governed environment. That is more than a convenience feature. It is the condition that makes AI usable in live deal work.
Governance remains non-negotiable in M&A. Clients, counterparties and regulators all expect confidential information to be handled with discipline. Any AI capability that weakens that standard is unusable in practice. The platforms that will win in dealmaking are the ones that combine speed with auditability, secure permissions and clear accountability.
The operational case is already compelling. AI cutting weeks of manual file preparation down to minutes, reducing redaction time by around 80 per cent and helping teams answer hundreds of diligence questions in minutes rather than hours. Those gains matter because drawn-out diligence raises both cost and execution risk. Other industry research also shows that prolonged diligence routinely adds months to deal timelines and increases advisory costs.
This is where AI stops sitting alongside M&A work and becomes embedded within it. Once that happens, junior roles can become more rewarding. Firms can expect early-career professionals to spend less time on administration and more time on analysis, judgement and learning how deals really work.
What Junior Professionals Should Do
Junior professionals should expect AI-generated output to become a normal part of day-to-day work. That is a positive development. It means they can spend less time on repetitive groundwork and more time learning how to interpret information, test assumptions and contribute to better decisions. In dealmaking, that judgement is as important as technical fluency.
The practical priority is to learn how leading models behave, how prompts shape results, and how governance frameworks determine where those tools can be used safely. Just as important, juniors should understand where humans still lead: investment thesis, valuation judgement, negotiation, cultural assessment and final go or no-go decisions. AI accelerates analysis. It does not replace accountability.
The strongest junior professionals will combine AI fluency with sound judgement, commercial awareness and disciplined handling of sensitive information. That combination will help them contribute more meaningfully earlier in their careers.
