M&A activity has returned at scale, but it has not returned in its old form.
Artificial intelligence is now influencing both sides of the transaction. It is changing what organisations want to acquire, from specialist talent and proprietary data to cyber capability and AI infrastructure. At the same time, it is changing how buyers identify targets, conduct due diligence, model value and prepare for integration.
The latest figures show how quickly the market is moving. PwC expects global M&A value to reach approximately $4 trillion in 2026, around 13% higher than in 2025. Yet projected deal volume is moving in the opposite direction, down 13% to approximately 42,000 transactions. Deals worth more than $5 billion now account for 48% of global deal value, compared with 26% in 2024.
BCG reports that global deal value reached approximately $1.6 trillion in the first half of 2026, up 28% year on year. There were 31 transactions valued at $10 billion or more during the period, compared with 17 in the first half of 2025.
The headline is not simply that M&A is growing. It is that capital is becoming more concentrated, deal theses are becoming more technology-led and the cost of getting integration wrong is increasing.
AI is becoming part of the acquisition thesis
For many buyers, AI is no longer an optional feature within a target. It is part of the strategic rationale for the deal.
Businesses are using M&A to access capabilities that may be difficult or too slow to build organically. These include proprietary datasets, specialist engineering talent, automation platforms, AI-enabled products, cloud infrastructure and cybersecurity capability.
The shift is particularly visible in technology. Bain found that almost half of technology deals in 2025 had an AI component, up from approximately one in four in 2024. The value of AI-related deals during the first three quarters of 2025 had already more than doubled the total recorded across the whole of 2024.
This demand is also spreading beyond the technology sector. Industrial, financial services, healthcare and consumer businesses are all looking at acquisitions that can accelerate automation, improve decision-making or strengthen access to data and digital talent.
However, buying an AI capability is not the same as being ready to use it.
An acquisition may look strategically compelling, but its value can depend on questions that are easy to underestimate during a fast-moving transaction:
- Is the target’s data accurate, accessible and legally usable?
- Is its intellectual property genuinely differentiated and defensible?
- How dependent is the product on third-party models, platforms or cloud providers?
- Are security, privacy and regulatory controls mature enough to support scale?
- Does the value sit in the technology, the workflows or a small group of key people?
- Can the buyer’s existing architecture absorb the capability without slowing it down?
These are not questions to leave until after close. They directly affect valuation, risk and the credibility of the value creation plan.
AI is also changing how deals get done
AI is not only a reason for transactions. It is increasingly part of the M&A process itself.
Bain’s survey of more than 300 M&A executives found that 45% used AI tools in M&A during 2025, more than double the level recorded a year earlier. Around one-third said they were using AI systematically or redesigning their M&A processes around it, while more than half expected AI to have a significant impact on how deals are completed.
Used well, AI can help teams:
- screen a larger market of potential targets;
- analyse virtual data rooms and management information more quickly;
- identify patterns across contracts, customer data and cost bases;
- test valuation and synergy assumptions against different scenarios;
- surface technology, cyber and operational risks earlier;
- create a more complete record of decisions and lessons from previous deals; and
- prepare Day 1 and integration plans with better information.
This can improve both speed and depth. In one example reported by Bain, AI-enabled analytics helped two merging organisations develop an optimised procurement and product model in around two months, rather than the more than 12 months expected through a sequential manual approach.
But speed is only useful when the output can be trusted. In a live transaction, a confident but unsupported answer can create more risk than a slower manual process.
That means AI-enabled dealmaking still requires clear data controls, traceable sources, secure environments and experienced human review. The strongest approach is not to replace judgement, but to give decision-makers better evidence earlier.
The integration challenge is getting harder, not easier
AI can accelerate analysis, but it does not remove the operational complexity of bringing two organisations together.
Every transaction still creates decisions around applications, infrastructure, identity, cyber controls, data ownership, vendors, operating models and people. When AI is part of the deal thesis, those decisions become even more interconnected.
For example, a buyer may acquire a business for its data and machine-learning capability, only to discover that the data is fragmented, permissions are unclear or the product relies on infrastructure that cannot be integrated into the buyer’s target architecture. A platform may perform well at its current scale but become uneconomical once model and cloud costs increase. Key technical knowledge may sit with a small team whose retention was not treated as a Day 1 priority.
The risk is a gap between the investment case and the delivery reality.
This is why technology integration cannot sit behind the transaction as a later workstream. It needs to inform the deal thesis, diligence priorities and integration roadmap from the beginning.
Five questions leaders should answer before close
1. What capability are we actually buying?
Be specific about where the value sits. Is it the product, data, intellectual property, talent, customer access or operating model? Different sources of value require different diligence and integration choices.
2. What could AI disrupt in the target’s current business model?
AI may strengthen the target, but it may also erode parts of its proposition, pricing or competitive advantage. Scenario planning should test whether the investment case remains credible as model performance, customer expectations and delivery economics change.
3. Is the integration thesis connected to the deal thesis?
The integration plan should show how the acquired capability will create value, not simply how systems will be combined. It should make clear what needs to be integrated, what should remain separate and where transformation should happen in parallel.
4. Are data, cyber and governance foundations ready?
AI value depends on trusted data and resilient technology. Data lineage, access controls, privacy obligations, model governance and cyber risk should be assessed before they become post-close blockers.
5. Do we have the specialist capability to deliver?
Integration programmes place intense pressure on internal teams at the same time as the organisation is expected to maintain business-as-usual delivery. Leaders need an honest view of capacity across cloud, data, cyber, enterprise applications, architecture and programme delivery.
From transaction speed to delivery confidence
The next phase of M&A will reward organisations that can connect strategy, technology and execution.
AI can help buyers see more, move faster and test assumptions in greater depth. It can also introduce new dependencies, new forms of risk and a higher bar for post-close delivery. The organisations that create value will be those that treat technology readiness and integration capability as part of the investment decision, not as an operational detail to resolve afterwards.
At Synnovate, we help organisations strengthen the technology foundations behind mergers, acquisitions and carve-outs. Our project services and specialist talent network provide capability across cloud, data and AI, cyber, enterprise applications and digital transformation, helping teams move from deal intent to measurable delivery.
Speak to Synnovate about strengthening your M&A technology and integration programme.