Gartner: Emergent AI Will Have a Profound Impact on Business and Society

"The popularity of many new AI techniques will have a profound impact on business and society," said Arun Chandrasekaran, Distinguished VP Analyst at Gartner. "The massive pretraining and scale of AI foundation models, viral adoption of conversational agents and the proliferation of generative AI applications are heralding a new wave of workforce productivity and machine creativity."

Generative artificial intelligence (AI) is positioned on the Peak of Inflated Expectations on the Gartner, Inc. Hype Cycle for Emerging Technologies, 2023, projected to reach transformational benefit within two to five years.

Generative AI is encompassed within the broader theme of emergent AI, a key trend on this Hype Cycle that is creating new opportunities for innovation.

"While all eyes are on AI right now, CIOs and CTOs must also turn their attention to other emerging technologies with transformational potential," said Melissa Davis, VP Analyst at Gartner. "This includes technologies that are enhancing developer experience, driving innovation through the pervasive cloud and delivering human-centric security and privacy."

"As the technologies in this Hype Cycle are still at an early stage, there is significant uncertainty about how they will evolve," added Davis. "Such embryonic technologies present greater risks for deployment, but potentially greater benefits for early adopters."

Four Themes of Emerging Technology Trends

Emergent AI: In addition to generative AI, several other emerging AI techniques offer immense potential for enhancing digital customer experiences, making better business decisions and building sustainable competitive differentiation.

These technologies include:

■ AI simulation

■ Causal AI

■ Federated machine learning

■ Graph data science

■ Neuro-symbolic AI

■ Reinforcement learning

Developer experience (DevX): DevX refers to all aspects of interactions between developers and the tools, platforms, processes and people they work with to develop and deliver software products and services. Enhancing DevX is critical for most enterprises' digital initiative success. It is also vital for attracting and retaining top engineering talent, keeping team morale high and ensuring that work is motivating and rewarding.

Key technologies that are enhancing DevX include:

■ AI-augmented software engineering

■ API-centric SaaS

■ GitOps

■ Internal developer portals

■ Open-source program office

■ Value stream management platforms.

Pervasive cloud: Over the next 10 years, cloud computing will evolve from a technology innovation platform to become pervasive and an essential driver of business innovation. To enable this pervasive adoption, cloud computing is becoming more distributed and will be focused on vertical industries. Maximizing value from cloud investments will require automated operational scaling, access to cloud-native platform tools and adequate governance.

Key technologies enabling the pervasive cloud include:

■ Augmented FinOps

■ Cloud development environments

■ Cloud sustainability

■ Cloud-native

■ Cloud-out to edge

■ Industry cloud platforms

■ WebAssembly (Wasm)

Human-centric security and privacy: Humans remain the chief cause of security incidents and data breaches. Organizations can become resilient by implementing a human-centric security and privacy program, which weaves a security and privacy fabric into the organization's digital design. Numerous emerging technologies are enabling enterprises to create a culture of mutual trust and awareness of shared risks in decision making between many teams.

Key technologies supporting the expansion of human-centric security and privacy include:

■ AI TRISM

■ Cybersecurity mesh architecture

■ Generative cybersecurity AI

■ Homomorphic encryption

■ Postquantum cryptography

The Hype Cycle for Emerging Technologies is unique among Gartner Hype Cycles because it distills key insights from more than 2,000 technologies and applied frameworks that Gartner profiles each year into a succinct set of "must-know" emerging technologies. These technologies have potential to deliver transformational benefits over the next two to 10 years.

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Gartner: Emergent AI Will Have a Profound Impact on Business and Society

"The popularity of many new AI techniques will have a profound impact on business and society," said Arun Chandrasekaran, Distinguished VP Analyst at Gartner. "The massive pretraining and scale of AI foundation models, viral adoption of conversational agents and the proliferation of generative AI applications are heralding a new wave of workforce productivity and machine creativity."

Generative artificial intelligence (AI) is positioned on the Peak of Inflated Expectations on the Gartner, Inc. Hype Cycle for Emerging Technologies, 2023, projected to reach transformational benefit within two to five years.

Generative AI is encompassed within the broader theme of emergent AI, a key trend on this Hype Cycle that is creating new opportunities for innovation.

"While all eyes are on AI right now, CIOs and CTOs must also turn their attention to other emerging technologies with transformational potential," said Melissa Davis, VP Analyst at Gartner. "This includes technologies that are enhancing developer experience, driving innovation through the pervasive cloud and delivering human-centric security and privacy."

"As the technologies in this Hype Cycle are still at an early stage, there is significant uncertainty about how they will evolve," added Davis. "Such embryonic technologies present greater risks for deployment, but potentially greater benefits for early adopters."

Four Themes of Emerging Technology Trends

Emergent AI: In addition to generative AI, several other emerging AI techniques offer immense potential for enhancing digital customer experiences, making better business decisions and building sustainable competitive differentiation.

These technologies include:

■ AI simulation

■ Causal AI

■ Federated machine learning

■ Graph data science

■ Neuro-symbolic AI

■ Reinforcement learning

Developer experience (DevX): DevX refers to all aspects of interactions between developers and the tools, platforms, processes and people they work with to develop and deliver software products and services. Enhancing DevX is critical for most enterprises' digital initiative success. It is also vital for attracting and retaining top engineering talent, keeping team morale high and ensuring that work is motivating and rewarding.

Key technologies that are enhancing DevX include:

■ AI-augmented software engineering

■ API-centric SaaS

■ GitOps

■ Internal developer portals

■ Open-source program office

■ Value stream management platforms.

Pervasive cloud: Over the next 10 years, cloud computing will evolve from a technology innovation platform to become pervasive and an essential driver of business innovation. To enable this pervasive adoption, cloud computing is becoming more distributed and will be focused on vertical industries. Maximizing value from cloud investments will require automated operational scaling, access to cloud-native platform tools and adequate governance.

Key technologies enabling the pervasive cloud include:

■ Augmented FinOps

■ Cloud development environments

■ Cloud sustainability

■ Cloud-native

■ Cloud-out to edge

■ Industry cloud platforms

■ WebAssembly (Wasm)

Human-centric security and privacy: Humans remain the chief cause of security incidents and data breaches. Organizations can become resilient by implementing a human-centric security and privacy program, which weaves a security and privacy fabric into the organization's digital design. Numerous emerging technologies are enabling enterprises to create a culture of mutual trust and awareness of shared risks in decision making between many teams.

Key technologies supporting the expansion of human-centric security and privacy include:

■ AI TRISM

■ Cybersecurity mesh architecture

■ Generative cybersecurity AI

■ Homomorphic encryption

■ Postquantum cryptography

The Hype Cycle for Emerging Technologies is unique among Gartner Hype Cycles because it distills key insights from more than 2,000 technologies and applied frameworks that Gartner profiles each year into a succinct set of "must-know" emerging technologies. These technologies have potential to deliver transformational benefits over the next two to 10 years.

Hot Topics

The Latest

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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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Why FinOps Rewrote Its Mission and What It Signals for Technology Management

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 ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

Empowering the Human Side of the Autonomous IT Age

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 Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

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 ...