What Dealmakers Should Consider for 2026 (Part 2 of 2)
Several sectors deserve particular attention as 2026 unfolds. AI infrastructure remains white-hot, with demand for data centers, specialized chips, and compute capacity driving valuations to levels that seemed absurd two years ago. The fundamentals support it. Without compute, companies can’t deploy AI at scale.
Robotics and autonomous systems are moving from experimental to operational across logistics, manufacturing, and transportation. The economics increasingly favor automation, and companies with proven systems at scale command premium valuations.
Space connectivity and space defense represent genuine opportunities beyond tourism hype. Connectivity infrastructure and defense applications are attracting serious capital and strategic interest from both corporates and governments.
Media and short-form content platforms continue consolidating. Attention is scarce, and platforms that capture it effectively are valuable even when traditional metrics look challenging. The advertising market follows attention, and dealmakers are betting on where attention concentrates.
Data-intensive operations across healthcare, logistics, financial services, and manufacturing become more valuable as AI adoption accelerates. Companies sitting on proprietary datasets that AI can turn into insights are acquisition targets for larger players lacking that data advantage.
Autonomous Workflows and Agentic AI
The next wave of AI isn’t just answering questions or generating content. Agentic AI executes multi-step tasks autonomously, reshaping cost structures, productivity benchmarks, and M&A integration risk profiles. These systems can manage complex workflows without constant human oversight, which fundamentally changes operational leverage.
As automation handles more routine execution, human judgment, storytelling, and relationship management become more valuable, not less. The skills that can’t be automated are the ones driving premium compensation and competitive advantage. Dealmakers who understand this are building teams around uniquely human capabilities while aggressively automating everything else.
Autonomous vehicles provide a concrete example. Waymo and Apollo GO have demonstrated safer, time-saving operational models that are already reshaping logistics and transportation economics. The pattern repeats across sectors: autonomous systems handling routine work while humans focus on exceptions, strategy, and relationships.
AI as an Operational Advantage
The AI conversation needs to shift from adoption to impact. Every company claims they're using AI. The question is whether it's actually improving operations. In 2026, the gap between companies with measurable AI impact and those still running pilots will widen dramatically.
Data readiness drives everything. High-performing organizations are experiencing substantial productivity gains as employees using AI report an average 40% productivity boost, with frequent users saving over 9 hours per week. Financial services firms are seeing 20% average productivity gains across the sector. But these results require purpose-built AI as well as clean data, well-structured workflows, and automation-enabled processes. Companies without proper data infrastructure are stuck spending money on AI tools that can't deliver results because the underlying foundation isn’t ready.
Target AI integration that solves real bottlenecks. Automating processes that were already efficient wastes resources. Focus AI deployment on areas where manual work creates delays, errors consume resources, or complexity prevents scaling. That's where ROI actually materializes.
Competitive edge doesn't come from adopting AI. It comes from integrating AI into operations so thoroughly that it changes what's possible. Companies achieving this are operating at speeds competitors can't match, which translates directly into market share gains and margin expansion.
AI Deal Sourcing Software Changes the Game
Traditional deal sourcing relied on networks, inbound pitches, and manual research. That model still works, but it’s too slow for 2026’s pace. AI deal sourcing platforms can scan millions of companies, identify patterns humans miss, and surface acquisition targets before they hit anyone else’s radar.
The best deal origination software combines proprietary data with AI that understands context beyond keyword matching. Purpose-built AI platforms like Cyndx demonstrate what’s possible when AI is designed specifically for dealmaking rather than generic business intelligence. Cyndx’s suite includes tools built for every stage of the M&A process:
- Finder uses natural language processing to surface companies based on what they actually do, not just how they describe themselves. Search by concept rather than keywords, identifying targets in emerging categories that don’t have standard industry classifications yet.
- Acquirer identifies acquisition targets based on strategic fit and compatibility, with predictive analytics flagging companies actively seeking funding or partnership discussions. Know which targets are receptive before you reach out.
- Raiser pinpoints investors based on actual check-writing history in comparable deals, not just stated investment criteria. Focus outreach on investors who have demonstrated interest through action.
- Valer performs sophisticated valuations with adjustable models, comparable company analysis, and precedent transactions, delivering credible starting points without weeks of manual modeling.
- Scholar generates comprehensive research reports using proprietary data on over 31 million companies plus external sources, complete with citations. Complex due diligence that would take weeks happens in minutes with professional-grade output.
These M&A products are built specifically for how deals actually get done. And this matters when you’re competing against firms that have moved beyond manual research to AI-powered deal origination.
What Victory Looks Like in 2026
Success in 2026 requires operational modernization, AI-enabled execution, and disciplined capital allocation. Companies that spent recent years building genuine operational capabilities will capture disproportionate value. Those that coasted on cheap capital and growth narratives will struggle as investors demand proof of sustainable business models.
For dealmakers specifically, victory means having the infrastructure to identify opportunities before competitors, the analytical capabilities to evaluate them thoroughly and quickly, and the execution speed to close transactions in compressed timeframes. Generic approaches won’t cut it.
You will need purpose-built AI deal sourcing platforms, M&A due diligence software that actually works, and company valuation tools that provide defensible analysis.
The gap between firms using cutting-edge deal origination software and those relying on traditional methods will become obvious in win rates and portfolio performance. AI isn’t making dealmaking obsolete. It’s making dealmakers who use AI effectively far more productive than those who don’t. As one of our clients has said, “No one can compete with me when I’m using Cyndx’s platform.”
The year ahead rewards the early adopters. If you’re still figuring out your AI strategy, evaluating deal sourcing platforms, or debating whether to invest in purpose-built M&A software, you’re already behind. The firms winning deals right now made those decisions 18 months ago.
The tools exist. The capital is available. The opportunities are real. What separates winners from everyone else is execution speed and the willingness to adopt AI-powered deal origination before it becomes obvious to everyone that it’s mandatory. By the time something is obvious, the advantage is gone.
Ask us how to build your capabilities now. The year ahead won’t wait for you to catch up.