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GenAI Delivering Strong ROI

Google Cloud says Among those with GenAI in production, 86% of those report an increase in revenue, estimating growth of 6%+

The majority of executives (61%) are harnessing the power of generative AI, with at least one application in production, and among these early adopters, 86% of those reported an increase in revenue, estimated at more than 6%, according to new  global research from Google Cloud.

The survey found that GenAI initiatives that are in production are driving benefits in four primary areas:

Productivity: Almost half (45%) of executives who reported improved productivity indicated that employee productivity has at least doubled as a result of GenAI rollouts at their organizations.

Security: 56% of executives reported that GenAI has bolstered their organization's security posture, with 82% of those execs citing improved ability to identify threats and 71% reporting a reduction in time to resolve a security issue.

Business growth: 77% of execs reporting business growth said they have improved leads and customer acquisition as a result of GenAI solutions.

User experience: 85% of executives reporting an improved user experience indicated specifically that user engagement has increased from GenAI, and nearly the same number reported improved user satisfaction (80%).

"Generative AI is not just a technological innovation; it's a strategic differentiator," said Oliver Parker, VP, Global Generative AI Go-To-Market, Google Cloud. "Our research shows that early adopters of GenAI are reaping significant rewards, from increased revenue, to better customer service, to improved productivity. Organizations investing in GenAI today are the ones that will be best positioned to succeed in the coming decade."

C-Suite Champions Key to Closing GenAI Adoption Gap

The speed by which organizations move from piloting GenAI to full-scale production is a strong indicator of its success, according to the research. Of the executives surveyed that are currently leveraging GenAI in production, 84% say their organizations were able to move from pilot to production in under six months.

However, a significant adoption gap remains: 39% of enterprises overall have still yet to implement the technology in production, with 21% actively testing, 12% evaluating use-cases, and 5% not started. This lag is particularly pronounced in regulated industries like financial services and manufacturing. In the EMEA region, organizations are significantly less likely to have been leveraging GenAI in production for more than one year.

C-Suite champions are key to GenAI success as 91% of respondents with robust C-level support of GenAI at their organization also report increased revenue estimates of 6% or more.

Additionally, "GenAI Leaders" — organizations that extensively utilize and invest in generative AI — exhibit key characteristics that set them apart:

Strategic alignment: 76% of leaders effectively aligned their AI strategies with broader business goals, compared to the global average of 69%.

Dedicated teams: 54% of leaders invested in dedicated generative AI teams, 13% more than their counterparts.

Significant investment: A staggering 86% of leaders plan to allocate at least half of their future AI budgets to generative AI, a stark contrast to the 67% average.

"Our data underscores the importance of executive-level support and strategic alignment for maximizing the potential of generative AI," said Carrie Tharp, VP, Strategic Industries, Google Cloud. "By connecting financial business drivers with technology drivers, organizations can ensure that AI strategies are not just innovative but also tightly intertwined with core business goals. This strategic alignment is the key to escaping the dreaded 'pilot purgatory,' and accelerating towards tangible business impact, leveraging AI to transform operations, enhance customer experiences, and unlock new avenues for growth."

An Emerging GenAI Reinvestment Cycle: Technology, Talent and Data

The early success of GenAI is sparking a reinvestment cycle that's driving further innovation and growth. Nearly half of respondents surveyed (49%) plan to reinvest the gains from GenAI to further improve operating profit margins. Specifically, the topic three areas for investment are:

Technology: 47% plan to invest in aligning business and technology to support change management for user adoption of AI.

Talent: 46% plan to invest in upskilling their workforce and attracting new talent with AI expertise.

Data quality: 43% said they plan to invest in data quality and knowledge management to ensure their GenAI applications are built on a solid foundation of accurate and reliable data

"The most successful organizations aren't just implementing GenAI. They're fostering a culture of innovation through experimentation," Parker added. "By reinvesting early gains in technology, talent, and data, these companies are building a sustainable AI ecosystem, creating a flywheel of innovation that will continue to drive growth and competitive advantage in the years to come."

Methodology: The report is based on a survey of 2,508 senior leaders of global enterprises ($10M+ revenue), conducted by Google Cloud and National Research Group from February 23-April 5. The survey respondents represent organizations from North America, Latin America, EMEA, and APAC, and across key industries including Financial Services, Manufacturing & Automotive, Retail & Consumer Packaged Goods, Telecommunications, Healthcare & Life Sciences, and Media & Entertainment.

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GenAI Delivering Strong ROI

Google Cloud says Among those with GenAI in production, 86% of those report an increase in revenue, estimating growth of 6%+

The majority of executives (61%) are harnessing the power of generative AI, with at least one application in production, and among these early adopters, 86% of those reported an increase in revenue, estimated at more than 6%, according to new  global research from Google Cloud.

The survey found that GenAI initiatives that are in production are driving benefits in four primary areas:

Productivity: Almost half (45%) of executives who reported improved productivity indicated that employee productivity has at least doubled as a result of GenAI rollouts at their organizations.

Security: 56% of executives reported that GenAI has bolstered their organization's security posture, with 82% of those execs citing improved ability to identify threats and 71% reporting a reduction in time to resolve a security issue.

Business growth: 77% of execs reporting business growth said they have improved leads and customer acquisition as a result of GenAI solutions.

User experience: 85% of executives reporting an improved user experience indicated specifically that user engagement has increased from GenAI, and nearly the same number reported improved user satisfaction (80%).

"Generative AI is not just a technological innovation; it's a strategic differentiator," said Oliver Parker, VP, Global Generative AI Go-To-Market, Google Cloud. "Our research shows that early adopters of GenAI are reaping significant rewards, from increased revenue, to better customer service, to improved productivity. Organizations investing in GenAI today are the ones that will be best positioned to succeed in the coming decade."

C-Suite Champions Key to Closing GenAI Adoption Gap

The speed by which organizations move from piloting GenAI to full-scale production is a strong indicator of its success, according to the research. Of the executives surveyed that are currently leveraging GenAI in production, 84% say their organizations were able to move from pilot to production in under six months.

However, a significant adoption gap remains: 39% of enterprises overall have still yet to implement the technology in production, with 21% actively testing, 12% evaluating use-cases, and 5% not started. This lag is particularly pronounced in regulated industries like financial services and manufacturing. In the EMEA region, organizations are significantly less likely to have been leveraging GenAI in production for more than one year.

C-Suite champions are key to GenAI success as 91% of respondents with robust C-level support of GenAI at their organization also report increased revenue estimates of 6% or more.

Additionally, "GenAI Leaders" — organizations that extensively utilize and invest in generative AI — exhibit key characteristics that set them apart:

Strategic alignment: 76% of leaders effectively aligned their AI strategies with broader business goals, compared to the global average of 69%.

Dedicated teams: 54% of leaders invested in dedicated generative AI teams, 13% more than their counterparts.

Significant investment: A staggering 86% of leaders plan to allocate at least half of their future AI budgets to generative AI, a stark contrast to the 67% average.

"Our data underscores the importance of executive-level support and strategic alignment for maximizing the potential of generative AI," said Carrie Tharp, VP, Strategic Industries, Google Cloud. "By connecting financial business drivers with technology drivers, organizations can ensure that AI strategies are not just innovative but also tightly intertwined with core business goals. This strategic alignment is the key to escaping the dreaded 'pilot purgatory,' and accelerating towards tangible business impact, leveraging AI to transform operations, enhance customer experiences, and unlock new avenues for growth."

An Emerging GenAI Reinvestment Cycle: Technology, Talent and Data

The early success of GenAI is sparking a reinvestment cycle that's driving further innovation and growth. Nearly half of respondents surveyed (49%) plan to reinvest the gains from GenAI to further improve operating profit margins. Specifically, the topic three areas for investment are:

Technology: 47% plan to invest in aligning business and technology to support change management for user adoption of AI.

Talent: 46% plan to invest in upskilling their workforce and attracting new talent with AI expertise.

Data quality: 43% said they plan to invest in data quality and knowledge management to ensure their GenAI applications are built on a solid foundation of accurate and reliable data

"The most successful organizations aren't just implementing GenAI. They're fostering a culture of innovation through experimentation," Parker added. "By reinvesting early gains in technology, talent, and data, these companies are building a sustainable AI ecosystem, creating a flywheel of innovation that will continue to drive growth and competitive advantage in the years to come."

Methodology: The report is based on a survey of 2,508 senior leaders of global enterprises ($10M+ revenue), conducted by Google Cloud and National Research Group from February 23-April 5. The survey respondents represent organizations from North America, Latin America, EMEA, and APAC, and across key industries including Financial Services, Manufacturing & Automotive, Retail & Consumer Packaged Goods, Telecommunications, Healthcare & Life Sciences, and Media & Entertainment.

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The Latest

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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