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Source document· December 24, 2025

In 2026, CFOs predict AI transformation, not just efficiency gains

View original at finance.yahoo.com
In 2026, CFOs predict AI transformation, not just efficiency gains Artificial intelligence was certainly top of mind for chief financial officers this year…
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  • Predictive analytics and competitive benchmarking will become essential, enabling CFOs to anticipate market shifts and optimize decisions with speed and precision

    80% confidence
  • In 2026, AI will continue to disrupt low-value, transactional activities, freeing teams to focus on higher-value strategic work

    80% confidence
  • It's going to become absolutely critical for CFOs and finance leaders to have some level of AI literacy and an ability to identify use cases to improve productivity

    80% confidence
  • Leaders will manage a more nuanced AI portfolio that balances launching pilots with rolling out proven solutions, and will prioritize data governance, process redesign, and maintenance

    80% confidence
  • AI-illiterate leaders will disappear in the next few years

    80% confidence
  • The orchestration of 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

    80% confidence
  • 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

    80% confidence
  • In 2026, AI will be judged less on promise and more on proof, with enterprises expecting measurable gains in speed, resilience, and decision quality

    80% confidence
  • In 2026, AI won't be a future concept for finance; it will be a business necessity

    80% confidence
  • 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

    80% confidence
  • 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

    80% confidence
  • Success depends on fixing foundational systems; layering AI over broken processes won't deliver results

    80% confidence
  • Consolidation needs to happen before widespread AI implementation

    80% confidence
  • 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

    80% confidence
  • CFOs who modernize architecture and skills will convert pilots into durable productivity, faster cycle times, and stronger margins

    80% confidence
  • AI will help CFOs anticipate risks, optimize capital allocation, and improve decision-making with unprecedented speed and accuracy

    80% confidence
  • In 2026, AI will move finance from retrospective reporting to real-time decision making

    80% confidence
  • AI will continue to force finance leaders to enact more discipline around how technology investments are evaluated and measured

    80% confidence
  • HPE's intelligent agents will automate quarterly close, forecasting, and analysis, delivering real-time insights and actionable predictions

    80% confidence
  • The real unlock is moving finance from reporting what happened to shaping what happens next

    80% confidence
  • Genpact's agentic accounts payable solutions are enabling more accurate, autonomous data capture, greater touchless processing, better cash visibility, and stronger supplier relationships, while reducing costs

    80% confidence
  • At full potential, AI enables finance teams to run hundreds or thousands of M&A scenarios before the first board discussion and predict customer churn before it impacts revenue

    80% confidence
  • There's no universal metric for AI ROI, as success depends on the function and problem being solved

    80% confidence
  • AI will shape finance in 2026 more by helping leaders operate in a higher-cost, higher-volatility world

    80% confidence
  • 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

    80% confidence
  • In 2026, leaders will shift from 'What can AI do?' to 'How do we build the foundation for scale?'

    80% confidence
  • Success in 2026 will be defined by how we mature our AI strategy to ensure it is both agile, durable, and enterprise-grade

    80% confidence
  • Core finance and accounting systems will enter a phase of end-to-end connectivity, visibility, flexibility, and interconnectedness with all business applications across departments

    80% confidence
  • e.l.f. Beauty will continue to explore how to best leverage AI in finance to lean into its strengths

    80% confidence
  • We're advancing toward a future where nearly every business decision will involve AI

    80% confidence

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What we're seeing
AI Capital Surge Meets Investor Caution: Record Funding Rounds and Government Contracts Amid Valuation Skepticism
A single-week cluster of large AI/fintech funding rounds (Socure, Stability AI, Emerald AI, Generalist AI, Instinct, Gatik, Regent Craft) shows venture capital still pouring into AI infrastructure, identity, and autonomy plays, while Palantir's Army TITAN contract win coincided with a 6% stock drop — signaling that even flagship AI-defense revenue isn't immune to market reassessment of AI valuations. Efficiency-focused innovations like Multiverse Computing's model compression suggest the sector is also pivoting toward cost/inference economics as capital intensity draws scrutiny.
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Signals we're tracking
EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
Morgan Stanley & Co. LLC
The same metric (eps) for the same entity (Morgan Stanley & Co. LLC) reported for the identical fiscal period (Q1 2026) and observation date (2026-03-31) has two conflicting values: 3.43 USD_per_share vs 3.08 USD. This is not a temporal change — both observations claim to measure the same point in time. The ~10% discrepancy (0.35 USD difference) is material for a financial metric.
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