How Dealmakers Can Lead Through M&A’s GenAI Divide

MIT report concludes AI partnerships — not DIY builds — are delivering the most ROI.

The DIY illusion

At first glance, standing up your own AI development team may seem like the smart move. But the data tells a different story. MIT found that most in-house efforts falter due to limited scale, inadequate learning capabilities and poor integration — weighed down by high costs, talent shortages and mounting technical debt.

Hiring AI engineers and MLOps specialists in today’s hyper-competitive market comes at a premium — and that’s just the beginning. (According to reports, leading AI researchers are being offered compensation packages worth as much as USD 300 million over four years to join Meta — with some earning more than USD 100 million in their first year alone.) Training and maintaining models demands significant compute power and constant oversight. Add to that the challenge of patching together disconnected tools, and it’s easy to see why so many internal efforts struggle to deliver value.

According to MIT, only 33 percent of internally built AI initiatives reach full deployment, while external partnerships with learning-capable, customized tools succeed about 67 percent of the time. And even when companies combine approaches, pilots built via strategic partnerships are twice as likely to reach full deployment as those built internally.

Why partnerships win

Organizations that have crossed the GenAI divide share a common strategy: they buy, customize and co-develop with trusted partners. These buyers focus on business outcomes rather than technical benchmarks, prioritize workflow integration and contextual learning, and hold vendors accountable for delivering measurable results.

As MIT concludes, “The most successful buyers understand that crossing the divide requires partnership, not just purchase.” The right partners bring industry knowledge, continuous feedback loops and integration discipline that internal teams rarely achieve at scale. Rather than struggling to build internal AI teams, top performers work with vendors who specialize in secure, learning-capable systems that evolve alongside their business.

What executives want — and how SS&C Intralinks delivers

MIT’s findings don’t just validate the partnership approach — they describe the path Intralinks has taken. For years, we’ve been building the infrastructure and intelligence that enable real business results for our clients. DealCentre AI^TM, our AI-powered dealmaking platform, represents the culmination of that work — bringing automation, insight and security together across every stage of the transaction lifecycle.

Powered by Link, our proprietary AI engine, DealCentre AI streamlines due diligence and delivers actionable intelligence that helps teams work faster and smarter — all within a single, secure ecosystem. Recognizing the benefits an ecosystem of AI tools can deliver to our customers, we’ve focused Link on areas where it would be difficult to offload work to a third-party AI, e.g., deal-prep document collection and due diligence Q&A. It’s a focused approach that mirrors what MIT found among leading organizations: success comes from knowing where AI truly creates an advantage.

MIT’s survey of enterprise leaders identified six priorities that define successful AI partnerships. Each aligns directly with how Intralinks helps clients unlock value.

A trusted vendor
Executives prefer proven partners over untested startups. For three decades, Intralinks has earned that trust — helping global financial institutions and corporations execute secure, compliant transactions. Our AI capabilities are built on that same foundation of reliability and governance.
Deep understanding of their workflow
StandaloneI tools can’t grasp the nuances of complex financial workflows. DealCentre AI is purpose-built around the realities of dealmaking. It’s not AI bolted onto a process — it’s AI built to make every step faster, smarter and more effective.
Minimal disruption
DealCentre AI enhances established workflows by increasing efficiency and accuracy. Link extracts key diligence information and presents it in familiar formats like tables, graphs and charts — delivering deeper insights with less manual work.
Clear data boundaries
Data security and privacy are at the core of everything we do. Intralinks’ AI operates within ringfenced environments — that means no cross-customer training, data sharing or external exposure. You maintain total control of your data within our trusted, compliant environments.
The ability to improve over time
With DealCentre AI, each transaction reveals new opportunities for strategic and operational improvements as your knowledge base grows. Our AI helps you learn from your own deal data and identify ways to move faster, reduce risk and optimize workflows.
Flexibility as business demands change
Built on a modular architecture with configurable workflows, DealCentre AI adapts to the unique demands of every deal. We’re always listening to our customers’ feedback, enabling teams to scale seamlessly and stay ahead in a changing market.

The cost of waiting

MIT warns that the window to cross the GenAI divide is closing. As enterprises lock in AI partners and establish feedback loops, the advantages of learning systems begin to compound and become harder to replicate. Every quarter of hesitation widens the gap between companies that are scaling AI securely and those still experimenting on the sidelines.

As those relationships deepen, their AI systems learn, scale and deliver competitive advantages that can’t easily be replicated. For dealmakers, AI isn’t a future conversation — it’s a present-day imperative while the window to build a smarter, more connected deal process remains open.

Ready to cross the GenAI divide? Visit our DealCentre AI page to learn more about how Link can help your team work faster and smarter.