Seven in 10 Companies Could Slash AI Budgets as ROI Disappoints, Report Finds

A new global survey shows that nearly 70% of companies are prepared to scale back AI budgets this year if projects fail to deliver measurable business results. This signals growing frustration with underperforming enterprise AI investments after two years of aggressive spending and experimentation.

The findings, published in the 2026 AI at Work Report from G-P (Globalization Partners), suggest that many organisations are beginning to reassess whether expensive AI deployments are producing the transformational productivity gains promised during the generative AI boom.

The report surveyed 2,850 business leaders across six global markets and found that while AI usage among executives is now effectively universal, enthusiasm around aggressive AI expansion is beginning to cool. The key findings from the survey show that:

• Nearly 70% of executives are prepared to reduce AI spending if business goals are not achieved this year.
• 73% reported at least some AI investments failed to meet expectations over the past 12 months
• The number of executives describing their organisations as “aggressively” using AI to innovate fell from 60% to 42%

The findings arrive as companies worldwide continue pouring billions into generative AI systems from providers including OpenAI, Microsoft and Google amid mounting pressure from boards and investors to demonstrate measurable returns.

The report reflects a broader shift underway across the enterprise AI market: companies are increasingly moving away from hype-driven experimentation and toward financially accountable AI deployment.

Earlier Fair Play Talks reports on CEO AI accountability pressures found that many executives now believe failed AI strategies could threaten their leadership positions, highlighting how quickly AI has evolved from a competitive opportunity into a boardroom liability.

AI IMPACT AT WORK

At the same time, a recent Fair Play Talks report on global CEO AI investment trends found that many companies still plan to increase AI spending despite growing concerns around ROI, governance, and operational complexity, highlighting the contradictory pressures shaping the enterprise AI market.

Key findings from the latest G-P report show that:

• Nearly 70% of executives said they will cut AI budgets if ROI targets are missed.
• 73% say some AI investments failed to meet expectations
• Aggressive enterprise AI adoption dropped sharply year over year
• 88% fear employees may be using AI to simulate productivity
• AI oversight and governance workloads are rising across organizations
• Companies are becoming less tolerant of AI experimentation without measurable business outcomes

AI & ROI

The report suggests enterprise AI is entering a more disciplined “pressure testing” phase as organisations increasingly evaluate whether AI systems can produce tangible operational and financial value. The findings contrast sharply with the optimism that dominated enterprise AI adoption in 2024 and 2025, when companies aggressively accelerated AI deployments out of fear of falling behind competitors.

Now, executives appear far more focused on proving ROI, operational efficiency, and measurable productivity gains. “To get AI right, you have to move past the hype and focus on where it actually moves the needle,” said G-P’s Chief Operating Officer, Nat Natarajan. “A smart strategy isn’t about doing everything at once, it’s about identifying high-impact use cases and preparing your team before you start. That foundation is what separates companies stuck in a loop of endless pilots from those that actually achieve real, transformative results.”

The findings align with a broader trend emerging across the enterprise technology market, where companies are increasingly prioritizing measurable AI outcomes over experimentation alone.

A recent FairPlayTalks report on enterprise AI investment trends found that CEOs still plan to increase AI spending despite growing concerns surrounding governance, ROI, and operational oversight. The increasing focus on AI accountability also mirrors broader boardroom concerns previously explored in FairPlayTalks coverage of corporate board priorities, which highlighted how AI governance and workforce transformation are becoming central strategic issues for business leaders.

AI ADOPTION & CHALLENGES

One of the G-P report’s most striking findings is growing executive concern that employees may be using AI tools to create the appearance of productivity without generating meaningful business value. According to the survey:

• 88% of executives worry employees are using AI to “perform productivity”
• 47% said they are very or extremely concerned this is already happening

The findings suggest many organisations are now confronting a hidden challenge inside enterprise AI adoption: distinguishing real productivity gains from superficial AI usage metrics. The report points to a growing disconnect between AI activity and measurable business outcomes as companies increasingly pressure workers to integrate AI tools into daily workflows.

The study also raises broader concerns around workplace accountability, employee evaluation, and the unintended consequences of aggressive AI adoption mandates. Earlier  reports on AI and workforce transformation highlighted how companies are increasingly linking employee performance expectations directly to AI usage and productivity targets.

Additional reports on workplace AI risks found many organisations are still failing to adequately educate employees about the operational and ethical risks associated with generative AI systems.

HIDDEN AI OVERSIGHT TAX AND AI SLOP

The reserach also reveals that companies market AI tools as productivity accelerators, but many organisations are now spending more time monitoring, reviewing and correcting AI-generated work, reinforcing findings of other studies. According to the G-P survey 69% of executives said employee time spent reviewing or updating AI-generated work increased over the past year  The findings suggest AI may be creating new operational burdens even as companies pursue automation and efficiency gains.

Many enterprises are discovering that deploying AI at scale requires new layers of governance, verification, compliance, employee training, and quality control, creating what some executives increasingly view as an “AI oversight tax”, also described by others as AI slop.That growing oversight burden is becoming a major issue across enterprise AI deployments, particularly as organisations struggle with hallucinations, explainability problems, legal exposure and quality assurance.

Recent  research on responsible AI governance highlights increasing efforts by companies to establish governance frameworks capable of managing AI accountability, transparency and operational risk. Other analyses on responsible AI business practices found that organisations are increasingly under pressure to move beyond AI experimentation and implement stronger operational safeguards and governance structures.

AI RESHAPING GLOBAL WORKFORCES

Despite concerns over ROI and oversight, companies continue aggressively competing for AI talent. According to the G-P report, 82% of executives are hiring workers in countries where they currently have no employees to secure AI talent.

The findings suggest AI capability is becoming a major driver of global hiring strategy and workforce transformation. At the same time, executives appear increasingly conflicted about AI’s impact on human workers. According to the survey 82% of executives admitted AI has lowered the value they place on human employees.

G-P warned that trend could ultimately undermine the human creativity and expertise organisations still need to deploy AI effectively. Pete Tiliakos, Principal Analyst and Strategic Advisor at GxT Advisors, said the next phase of enterprise AI will depend heavily on governance and operational discipline. “AI is increasingly being measured by trust, accountability and business impact,” said Tiliakos. “The future belongs to companies that pair AI with the right expertise, governance and operational discipline to turn opportunity into real business outcomes.”

WHY THE FINDINGS MATTER: MEASURABLE RESULTS

The survey suggests enterprise AI is entering a more mature and financially accountable phase. For much of the past two years, companies won praise simply for adopting AI tools and signalling innovation momentum to investors and boards. Now, organisations must prove AI can deliver measurable business outcomes safely, efficiently, and at scale.

Several major themes are now emerging across the enterprise AI market:

• Companies are becoming less tolerant of expensive AI experimentation without measurable ROI
• AI governance and oversight are becoming operational priorities
• Executives are increasingly focused on productivity outcomes rather than AI adoption metrics alone.
• Workforce strategies are shifting as companies race to secure AI talent globally
• AI accountability is becoming a board-level issue

The findings also suggest the market may be moving away from peak AI hype towards a more disciplined phase. This time focusing on operational efficiency, profitability, governance and long-term strategic value.

AI ENTERS ITS RECKONING PHASE

The G-P report reflects a broader transformation underway across the corporate AI landscape. After years dominated by rapid experimentation and competitive pressure to adopt generative AI technologies, companies are increasingly asking harder questions:

• Is AI actually improving productivity?
• Are the efficiency gains real?
• Can organisations govern AI safely?
• Is the return on investment sustainable?

The enterprise AI race will not be won by the companies deploying AI fastest. It will be won by those that can prove AI delivers measurable value under growing financial, operational and regulatory pressure.

Download the full report here.

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