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AI-Powered Search Could Yield Staggering Productivity Returns

Nearly all (99%) global IT decision makers, regardless of region or industry, recognize generative AI's (GenAI) transformative potential to influence change within their organizations, according to The Elastic Generative AI Report.

However, early adoption continues to be slowed by chaotic data estates, search challenges, and fears around privacy and security, regulation, and internal skills gaps.

Despite these headwinds, the report found most IT decision makers (88%) are eyeing increased investments in GenAI in 2024 and beyond. This points to optimism that these technologies are poised to drive operational efficiencies and productivity, accelerate decision-making, improve customer engagement, and bolster security postures.

"In a little more than 12 months, the disruptive potential of GenAI has shifted from reverie to reality, capturing the imaginations and budgets of IT and data leaders," said Matt Riley, GVP & GM of Search at Elastic. "While data may fuel this technology, search is the engine that powers its effectiveness. Unsurprisingly, businesses that adopt search-powered GenAI quickest — grounded by business context — will lead and uncover the insights needed to securely innovate, build more efficient businesses, and pioneer new customer experiences."

"Generative AI is still an emerging technology, but it already promises to disrupt how organizations operate and engage with customers and employees," said Jason Bloomberg, Managing Director of analyst firm Intellyx. "In particular, GenAI is transforming the data management, security, and search challenges many businesses continue to face. Thoughtful application of this new technology will help them better anticipate customer needs and differentiate themselves from their competition."

Key Concerns

There's high enthusiasm for GenAI across regions and industries, but key concerns stifle operationalization strategies.

Across verticals, GenAI is poised to deliver tangible benefits for organizations. More than half of respondents (57%) anticipate it will improve resource (i.e., staff time, better costs) and operational efficiency and productivity, improve customer experience (50%), and lead to more accurate decision-making (48%).

However, despite early interest and planned investment, internal and external roadblocks threaten to slow GenAI adoption. Nearly 9 of 10 organizations anticipate budgets for GenAI will increase over the next three years, despite nearly all respondents reporting adoption is being slowed, primarily by fears around the security and privacy of the technologies (40%), regulation issues (37%), and the skills gap to implement the technologies in house (36%)

While a skills gap may continue to slow GenAI adoption, 4 of 10 respondents believe it will eventually help upskill and educate employees

Siloed Data Ecosystems

Siloed data ecosystems continue to expand in size and complexity, complicating security, visibility, and real-time analysi.

Most organizations continue to struggle to get relevant insights from their data, which leads to sluggish decision-making. Unsurprisingly, 3 of 4 (75%) respondents report the ability to view data across their entire environment is a key challenge for their organizations, while 7 of 10 (68%) report critical decisions are stalled by slow analysis of their organization's data.

While search powered GenAI is recognized as a key to unlocking transformative insights, effective search capabilities remain stunted. Nearly all respondents (97%) believe a conversational search experience would make their organizations more productive, and nearly half (44%) believe their organizations could save an average of two days or more per week per employee.

The majority of organizations (94%) face data search challenges driven by a struggle to use search results effectively (45%), the inability to cover multiple sources of information (44%), and the inability to obtain responses quickly enough (42%).

Security and Observability

Despite evolving IT infrastructures and data estates, there's optimism GenAI will illuminate security and observability blindspots.

IT security environments and threat landscapes have never been more complex, but there's confidence GenAI will alleviate many challenges. Nearly all organizations (97%) face IT security challenges, from the ability to detect and respond to threats quickly to maintaining current and relevant security practices, but nearly all respondents anticipate GenAI will bolster security postures, such as improving automated threat detection systems (53%), generating training exercises (50%), and automating responses to common security problems (49%).

Holistic observability remains a significant operational pain point, but GenAI offers hope. Nearly all organizations (95%) report observability challenges, from data silos to more complex applications, but nearly all respondents are confident GenAI would benefit their observability postures, specifically to enhance missing data handling (48%), improve data masking and privacy (43%), and to conduct rigorous and regular data quality assessments with synthetic data (43%).

Methodology: The report was produced in conjunction with independent market research specialist Vanson Bourne, and solicited 3,200 IT decision makers and decision influencers across the US, Europe, and Asia-Pacific from more than a dozen sectors, including telecommunications, public service, retail, and financial services.

Hot Topics

The Latest

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 ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

AI-Powered Search Could Yield Staggering Productivity Returns

Nearly all (99%) global IT decision makers, regardless of region or industry, recognize generative AI's (GenAI) transformative potential to influence change within their organizations, according to The Elastic Generative AI Report.

However, early adoption continues to be slowed by chaotic data estates, search challenges, and fears around privacy and security, regulation, and internal skills gaps.

Despite these headwinds, the report found most IT decision makers (88%) are eyeing increased investments in GenAI in 2024 and beyond. This points to optimism that these technologies are poised to drive operational efficiencies and productivity, accelerate decision-making, improve customer engagement, and bolster security postures.

"In a little more than 12 months, the disruptive potential of GenAI has shifted from reverie to reality, capturing the imaginations and budgets of IT and data leaders," said Matt Riley, GVP & GM of Search at Elastic. "While data may fuel this technology, search is the engine that powers its effectiveness. Unsurprisingly, businesses that adopt search-powered GenAI quickest — grounded by business context — will lead and uncover the insights needed to securely innovate, build more efficient businesses, and pioneer new customer experiences."

"Generative AI is still an emerging technology, but it already promises to disrupt how organizations operate and engage with customers and employees," said Jason Bloomberg, Managing Director of analyst firm Intellyx. "In particular, GenAI is transforming the data management, security, and search challenges many businesses continue to face. Thoughtful application of this new technology will help them better anticipate customer needs and differentiate themselves from their competition."

Key Concerns

There's high enthusiasm for GenAI across regions and industries, but key concerns stifle operationalization strategies.

Across verticals, GenAI is poised to deliver tangible benefits for organizations. More than half of respondents (57%) anticipate it will improve resource (i.e., staff time, better costs) and operational efficiency and productivity, improve customer experience (50%), and lead to more accurate decision-making (48%).

However, despite early interest and planned investment, internal and external roadblocks threaten to slow GenAI adoption. Nearly 9 of 10 organizations anticipate budgets for GenAI will increase over the next three years, despite nearly all respondents reporting adoption is being slowed, primarily by fears around the security and privacy of the technologies (40%), regulation issues (37%), and the skills gap to implement the technologies in house (36%)

While a skills gap may continue to slow GenAI adoption, 4 of 10 respondents believe it will eventually help upskill and educate employees

Siloed Data Ecosystems

Siloed data ecosystems continue to expand in size and complexity, complicating security, visibility, and real-time analysi.

Most organizations continue to struggle to get relevant insights from their data, which leads to sluggish decision-making. Unsurprisingly, 3 of 4 (75%) respondents report the ability to view data across their entire environment is a key challenge for their organizations, while 7 of 10 (68%) report critical decisions are stalled by slow analysis of their organization's data.

While search powered GenAI is recognized as a key to unlocking transformative insights, effective search capabilities remain stunted. Nearly all respondents (97%) believe a conversational search experience would make their organizations more productive, and nearly half (44%) believe their organizations could save an average of two days or more per week per employee.

The majority of organizations (94%) face data search challenges driven by a struggle to use search results effectively (45%), the inability to cover multiple sources of information (44%), and the inability to obtain responses quickly enough (42%).

Security and Observability

Despite evolving IT infrastructures and data estates, there's optimism GenAI will illuminate security and observability blindspots.

IT security environments and threat landscapes have never been more complex, but there's confidence GenAI will alleviate many challenges. Nearly all organizations (97%) face IT security challenges, from the ability to detect and respond to threats quickly to maintaining current and relevant security practices, but nearly all respondents anticipate GenAI will bolster security postures, such as improving automated threat detection systems (53%), generating training exercises (50%), and automating responses to common security problems (49%).

Holistic observability remains a significant operational pain point, but GenAI offers hope. Nearly all organizations (95%) report observability challenges, from data silos to more complex applications, but nearly all respondents are confident GenAI would benefit their observability postures, specifically to enhance missing data handling (48%), improve data masking and privacy (43%), and to conduct rigorous and regular data quality assessments with synthetic data (43%).

Methodology: The report was produced in conjunction with independent market research specialist Vanson Bourne, and solicited 3,200 IT decision makers and decision influencers across the US, Europe, and Asia-Pacific from more than a dozen sectors, including telecommunications, public service, retail, and financial services.

Hot Topics

The Latest

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 ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...