We just released insights from Forrester’s State Of AI Survey, 2025, with data from over 1,400 global AI decision-makers. The AI decision-makers we surveyed represent organizations actively deploying AI technologies — both generative and predictive — across various functions, so our base was shifted to the right (more advanced) in terms of the adoption bell curve. This gave us insights about adoption trends, governance practices, security concerns, ROI expectations, and financial impact measurements for firms actually investing in AI. Our study revealed that despite rapid early investment, governance, security, and long-term value are lagging.

This leads me to three questions that will demand answers in the coming year.

Can Business Leaders Tie AI To Real Financial Outcomes?

AI is still stuck in “efficiency mode.” In many organizations, a technology organization leads AI efforts and is treated as a cost center. Those CIOs are incentivized to optimize for efficiency, not growth. The result is predictable: Tech-led AI strategies deliver productivity improvements, but not transformation. Equally concerning is that technology and AI executives tell us their business partners can’t articulate what they want from AI beyond saving money.

That leadership gap bleeds over into the measurement of AI value. While most agree that AI boosts productivity, only 13% report positive EBITDA impact, and fewer than a third link AI contributions to P&L. Without financial accountability, AI becomes an endless pilot treadmill — producing activity without outcomes. To shift AI from incremental savings to strategic advantage, business leaders must step in, define value in P&L terms, and own the linkage between AI-driven productivity and financial performance.

Can AI Leaders Think Beyond Quick Wins — And Bring Their People Along?

Short-term ROI obsession is sabotaging strategic bets. Nearly half of decision-makers expect payback within a year while only 14% commit to three-year horizons. That pressure from boards and investors is real — but transformation takes time and demands organizational reinvention, not just tech deployment.

Our survey reveals a troubling disconnect: 48% of firms have already cut headcount due to AI, yet change management and employee experience rank among the least prioritized areas for 2026. Employees feel unsupported, and that fear slows adoption. Unless firms put humans at the center of their AI strategy, they’ll see only marginal gains.

Can Governance And Security Evolve To Sustain AI Adoption?

Rapid AI deployment without robust guardrails leaves firms exposed to risk and erodes trust — and trust is the biggest obstacle between AI and value. For example, our survey showed that while nearly three-quarters of organizations have documented AI policies, most cover only basics such as data use or copyright compliance. Few mandate responsible AI training or provide clear guidance for employees seeking help.

At the same time, 40% of decision-makers cite security and risk as their top concern, yet the pressure to go fast often trumps safeguards. To protect data, reputation, and innovation, firms must embed AI governance and risk management into their business operating model. Good governance and security foundations are the platform of trust upon which tomorrow’s leaders will thrive.

What’s Next?

2026 promises to be a down-to-business year, as generative AI becomes a gangly junior high-schooler with pimples and firms figure out just how far they can push agents to automate tasks. Join us at our webinar on March 6 to hear more about this survey and what it means for your AI investment plan in the coming year.