Skip to main content

Forrester: Top 10 Emerging Technologies for 2024

GenAI, TuringBots, And IoT Security Poised To Deliver Fastest ROI

According to Forrester's The Top 10 Emerging Technologies In 2024 report, generative AI (genAI) for visual content, genAI for language, TuringBots, and IoT security are the top emerging technologies that will deliver the most immediate ROI for businesses in 2024 and beyond.

With new technologies emerging seemingly every day, business and technology leaders need to time those investments based on value, risk, and potential payout timelines. Forrester organizes its top emerging technologies by benefit horizon to help with these decisions.

Emerging technologies that will offer significant benefits within the next two years

GenAI for visual content: Advanced machine learning models that generate images or video from text, audio, or video prompts, this technology will help firms generate visual content for marketing, experiences, and products.

GenAI for language: GenAI for language is already delivering value in customer support and content creation but continues to advance at a blinding pace. It is accelerating many other technologies as it goes.

TuringBots: Accelerated by advancements in genAI for language, these AI-powered software robots help developers build applications that deliver more than just code generation.

IoT security: The proliferation of devices has led to an exponential explosion in security attacks, raising the importance of security for IoT devices. Vendors are competing and colliding in a rush to offer capabilities.

Midterm emerging technologies that will deliver benefits in the next two to five years

AI agents: The role of autonomous workplace assistants or AI agents has expanded beyond the back office and employee assistance to customer-facing automation. These AI agents will grow increasingly sophisticated to better understand and respond to nuance and context.

Autonomous mobility: This technology will accelerate commercial and urban transportation ecosystem collaborations to orchestrate personalized mobility experiences for both customers and businesses.

Edge intelligence: Advanced edge intelligence capabilities such as edge machine learning are still not yet common, even though many foundational elements like Apple foundation models are becoming available.

Quantum security: This technology will overhaul security systems for on-premises and cloud compute, storage and network infrastructure, commercial off-the-shelf software, commercial software-as-a-service offerings, and in-house built software.

Emerging technologies that will take at least five more years to deliver tangible value for most firms and use cases

Extended reality (XR): Only 8% of US online adults own a virtual-reality headset, and just 16% have used an augmented-reality device or app. While XR is advancing in training and onboarding, companies are resisting investing in tools like these until they see broad adoption.

Zero Trust edge (ZTE): ZTE technology has the potential to protect remote workers, retail outlets, and branch offices with embedded local security, but only a handful of true ZTE solutions exist today, and legacy devices add additional management complexity.

"Tech leaders must be able to identify the right use cases and quantify potential benefits, costs, and risks across multiple horizons," says Brian Hopkins, Forrester VP, Eerging Tech Portfolio. "They need to spread investments out, with shorter-term technologies delivering quick returns and longer-term bets requiring more effort, more foundational investment, and the capacity to manage more risk."

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

Forrester: Top 10 Emerging Technologies for 2024

GenAI, TuringBots, And IoT Security Poised To Deliver Fastest ROI

According to Forrester's The Top 10 Emerging Technologies In 2024 report, generative AI (genAI) for visual content, genAI for language, TuringBots, and IoT security are the top emerging technologies that will deliver the most immediate ROI for businesses in 2024 and beyond.

With new technologies emerging seemingly every day, business and technology leaders need to time those investments based on value, risk, and potential payout timelines. Forrester organizes its top emerging technologies by benefit horizon to help with these decisions.

Emerging technologies that will offer significant benefits within the next two years

GenAI for visual content: Advanced machine learning models that generate images or video from text, audio, or video prompts, this technology will help firms generate visual content for marketing, experiences, and products.

GenAI for language: GenAI for language is already delivering value in customer support and content creation but continues to advance at a blinding pace. It is accelerating many other technologies as it goes.

TuringBots: Accelerated by advancements in genAI for language, these AI-powered software robots help developers build applications that deliver more than just code generation.

IoT security: The proliferation of devices has led to an exponential explosion in security attacks, raising the importance of security for IoT devices. Vendors are competing and colliding in a rush to offer capabilities.

Midterm emerging technologies that will deliver benefits in the next two to five years

AI agents: The role of autonomous workplace assistants or AI agents has expanded beyond the back office and employee assistance to customer-facing automation. These AI agents will grow increasingly sophisticated to better understand and respond to nuance and context.

Autonomous mobility: This technology will accelerate commercial and urban transportation ecosystem collaborations to orchestrate personalized mobility experiences for both customers and businesses.

Edge intelligence: Advanced edge intelligence capabilities such as edge machine learning are still not yet common, even though many foundational elements like Apple foundation models are becoming available.

Quantum security: This technology will overhaul security systems for on-premises and cloud compute, storage and network infrastructure, commercial off-the-shelf software, commercial software-as-a-service offerings, and in-house built software.

Emerging technologies that will take at least five more years to deliver tangible value for most firms and use cases

Extended reality (XR): Only 8% of US online adults own a virtual-reality headset, and just 16% have used an augmented-reality device or app. While XR is advancing in training and onboarding, companies are resisting investing in tools like these until they see broad adoption.

Zero Trust edge (ZTE): ZTE technology has the potential to protect remote workers, retail outlets, and branch offices with embedded local security, but only a handful of true ZTE solutions exist today, and legacy devices add additional management complexity.

"Tech leaders must be able to identify the right use cases and quantify potential benefits, costs, and risks across multiple horizons," says Brian Hopkins, Forrester VP, Eerging Tech Portfolio. "They need to spread investments out, with shorter-term technologies delivering quick returns and longer-term bets requiring more effort, more foundational investment, and the capacity to manage more risk."

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...