For the private markets, this means thinking about more AI, all the time. That said, I do think next year the rubber is going to meet the road for AI startups and giants alike. High compute costs, compressed margins, and soaring valuations and expectations will inevitably collide with reality. And for some, this will mean even more acquisitions and more acquihires than perhaps we’ve seen so far in the AI boom. 

I started asking around: Which startups would make smart acquisition targets for a tech giant in 2026?

“To unlock ‘real world’ AI like robotics, autonomous vehicles, smart factories, spatial computing, and embodied AI, tech giants need models that can reason about the real world in real time,” said Aidan Madigan-Curtis, Eclipse Ventures partner, via text. “Startups like Wayve, Physical Intelligence, WorldLabs, Bedrock Robotics, The Bot Company and GenesisAI, are already building simulation engines, sensor fusion stacks, and world models that learn from physical interaction—capabilities that would take incumbents years to replicate internally.” (Eclipse is an investor in Wayve.)

Madigan-Curtis gets at an essential question: In AI, when does it make more sense to acquire rather than build? Shensi Ding, CEO and cofounder at AI integration infrastructure startup Merge, points out an unconventional idea around finance (a widely touted AI use case): “Large AI players should acquire boutique investment banks and use historical financial models to train them. This work is highly specialized and requires domain expertise to really break through and build trust.”

Meanwhile, Morgan Blumberg, M13 principal, thinks that large foundation model companies will look to gobble up application layer companies with proven product-market fit. The obvious targets: coding tools, one of enterprise AI’s great 2025 success stories.

“In 2025, we saw Windsurf in the coding space attract strong interest,” said Blumberg via text. “While some like Cursor might choose to stay independent, I predict there will be attractive prices for assets like Factory, Codegen, Wrap, and others.”

Zach Lloyd, CEO and founder of agentic coding startup Warp, reinforced that developers are a key customer base: “AI giants should acquire an observability platform like Datadog or Sentry,” he said via email. “These tools sit where code meets reality (logs, errors, traces, and production failures) which is exactly the context AI needs to be genuinely useful to developers.”

This push to get enterprise right transcends foundation-model mainstays like OpenAI or Anthropic, and for some large companies, it might make perfect sense to buy a unicorn outright, said Jake Stauch, CEO and founder of Serval, which builds AI agents for IT. “They could look to acquire enterprise AI solutions in customer support or enterprise search, such as Sierra or Glean respectively,” he said. 

It’s worth saying: Pretty much any deals of this ilk coming to pass would be, well, a big deal. That said, any potential deal target deserves serious scrutiny. So much capital has flowed into so many of these AI businesses. And last time I checked, even in the most abundant situations, there are inevitably a finite number of generational public companies. 

This is the last Term Sheet of 2025, and when we’re back on January 5, it’ll be with our much-loved Crystal Ball prediction series. So, I’ll leave you with one prediction of my own: Next year, we’ll enter a period where the haze of flowing capital and buzzy rhetoric will clear just a little, and we’ll start to see who can actually go the distance. 

See you in 2026, 

Allie Garfinkle
X: @agarfinks
Email: alexandra.garfinkle@fortune.com
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Below are CFOs’ predictions for 2026:

Gina Mastantuono, president and CFO, ServiceNow: “In 2026, AI will be judged less on promise and more on proof. Enterprises will continue to expect measurable gains in speed, resilience, and decision quality, not pilots and prototypes. The real shift will be enterprise-wide, with AI embedded into how companies plan and allocate capital, operate, serve customers, and manage risk. That level of impact requires trusted data, clear accountability, and leaders willing to redesign how decisions get made. AI will not replace human experience or judgment, but it will quickly expose where it’s missing and reward organizations that connect vision to AI-powered execution at scale.” 

Marie Myers, EVP and CFO, Hewlett Packard Enterprise: “AI isn’t on the horizon; it’s here. In 2026, AI will move beyond experimentation to become a core enabler of finance operations. For HPE, that means our intelligent agents will automate quarterly close, forecasting, and analysis, delivering real-time insights and actionable predictions. Success will hinge on strong governance, human oversight, ROI discipline, and building digital acumen that empowers talent and upskills their expertise in this AI era. In 2026, CFOs need to shift from financial gatekeepers to transformational architects who drive strategy and shape decisions.”

Zane Rowe, CFO, Workday: “There has never been a more exciting time to be a CFO with AI unlocking new opportunities for value creation through unprecedented data and insights. Most of the focus has been on experimentation and discovering the art of the possible, but this year, leaders will shift from ‘What can AI do?’ to ‘How do we build the foundation for scale?’. They will manage a more nuanced AI portfolio that balances launching pilots with rolling out proven solutions, and they will prioritize the unglamorous but critical work of data governance, process redesign, and maintenance of new technologies. Success in 2026 will be defined by how we mature our AI strategy to ensure it is both agile, durable, and enterprise-grade.”

Mandy Fields, CFO, e.l.f. Beauty: “From where a CFO sits, AI simultaneously helps broaden our view to get a better macro picture and can help put a sharper focus on very specific points of interest. e.l.f. Beauty is growing globally, and AI has visibility across it all. Going into next year, we’ll continue to explore how we best leverage AI in finance to lean into its strengths. It’s a pretty similar approach to our high-performance teamwork culture in which we encourage the team to pursue and thrive in the areas where they have expertise, learn continuously and move at e.l.f. speed.”

Scott Grossman, CFO, Ensono, a managed IT services company: “Historically, AI struggled with the complexity of financial data, but 2026 will mark a turning point. Advances in generative AI and predictive analytics will enable finance teams to move beyond automation toward real-time insights and scenario modeling. AI will help CFOs anticipate risks, optimize capital allocation, and improve decision-making with unprecedented speed and accuracy. The future of finance is not just about crunching numbers, but rather about transforming data into strategic foresight.” 

Joy Mbanugo, CFO, CXApp Inc., an AI-powered enterprise workplace experience platform: “At full potential, AI enables finance teams to run hundreds or thousands of M&A scenarios before the first board discussion; predict customer churn before it impacts revenue; stress-test capital allocation decisions across dozens of macroeconomic environments; and identify the small subset of R&D investments most likely to generate the majority of returns. The real unlock is moving finance from reporting what happened to shaping what happens next. The hard truth: if AI is only being used to do the same work faster, its value is being underutilized. The real power comes from doing different work, strategic work that drives outcomes, not just efficiency. AI in finance isn’t just about speed. It’s about transformation.”

Mike Weiner, CFO, Genpact, a business services and technology company: “In 2026, AI won’t be a future concept for finance; it will be a business necessity. Leaders will need to move beyond pilots and start treating AI and agentic systems as real team members that take on work and drive outcomes. At Genpact, we’re already seeing this shift. Our agentic accounts payable solutions are enabling more accurate, autonomous data capture, greater touchless processing, better cash visibility, and stronger supplier relationships, while reducing costs for both our clients and ourselves as Client Zero. Success will require continuing to rethink processes, data, talent, and ways of working.”

Michael Bourque, CFO, Convera, a B2B cross-border payments company: “AI will shape finance in 2026 more by helping leaders operate in a higher-cost, higher-volatility world. As cheap capital remains off the table, CFOs will lean on AI to optimize liquidity, manage debt, and prioritize spending with tighter margins. With currency volatility becoming the baseline through early 2026, AI-driven models will be critical for monitoring FX exposure and adjusting strategies in real time. As growth is increasingly driven by government spending rather than consumers, finance teams will use AI to assess policy impacts and sector-specific risk. Most importantly, AI will support scenario planning, enabling CFOs to run multiple forecasts and stay flexible amid uncertainty.”

Evan Goldstein, CFO, Seismic, a sales and revenue AI-powered platform: “AI will continue to force finance leaders to enact more discipline around how technology investments are evaluated and measured. Simply put, the era of buying AI for AI’s sake is over. CFOs will remain willing to invest in AI but will require clarity on how it’s tied to business outcomes like improved efficiency, productivity, or sustainable growth. There’s no universal metric for AI ROI, as success depends on the function and problem being solved. Whether it’s reducing front office administrative time or improving sales conversion rates, finance leaders will increasingly demand clear, operational proof of value before expanding AI spend.”

Jason Godley, CFO at Xactly, an intelligence revenue platform: “2026 will be the year when the lines around disparate software applications truly blur. Traditionally, software systems have generally served a single leader, like a CFO or CMO, instead of a broader set of business stakeholders. Since a CFO’s mission is to help run a business—not just a budget – the core finance and accounting systems will enter a phase of end-to-end connectivity, visibility, flexibility, and interconnectedness with all business applications across departments, like marketing, sales, and supply chain. The orchestration of these systems, data, and workflows through the use of generative AI will serve to augment end-to-end visibility and cross-functional scenario analysis, planning, and reporting.”

John Schwab, CFO, Vertex Inc., an indirect tax software provider:”In 2026, AI will move finance from retrospective reporting to real-time decision making. Embedded in ERP, agentic AI will accelerate the close, sharpen forecasting and cash visibility, and automate controls and compliance, cutting manual work while improving auditability. The real differentiator is governed data and operating models that keep humans in the loop and tie AI to measurable outcomes and risk standards. CFOs who modernize architecture and skills will convert pilots into durable productivity, faster cycle times, and stronger margins.”

Kevin Rhodes, CFO, Extreme Networks, an AI-powered cloud networking: “For CFOs and finance leaders, it’s going to become absolutely critical to have some level of AI literacy and an ability to identify use cases to improve productivity in your organization. It’s not just a matter of knowing how to use it, but understanding how to evaluate potential investments in AI platforms, lead and guide your teams in adoption, and assess which areas will be impacted by AI deployments. We’re advancing toward a future where nearly every business decision will involve AI, and having that background will be key for success at all levels, but particularly for leaders. It’s likely that, given our projected AI-powered future, AI-illiterate leaders will disappear in the next few years.”

Conor Tieney, CFO, AEye, Inc., a provider of lidar and intelligent perception software: “Right now, many CFOs are holding off on broad AI adoption because the market is saturated with overlapping tools and unclear value propositions. Consolidation needs to happen before widespread implementation. In 2026, AI will continue to disrupt low-value, transactional activities, freeing teams to focus on higher-value strategic work. But success depends on fixing foundational systems; layering AI over broken processes won’t deliver results. Predictive analytics and competitive benchmarking will become essential, enabling CFOs to anticipate market shifts and optimize decisions with speed and precision. Those who embrace streamlined, integrated AI solutions will gain a clear competitive edge.”