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Emerging Technology Priorities Go Beyond AI

Matt Cloke
Endava

Over the past decade, the pace of technological progress has reached unprecedented levels, where fads both quickly rise and shrink in popularity. From AI and composability to augmented reality and quantum computing, the toolkit of emerging technologies is continuing to expand, creating a complex set of opportunities and challenges for businesses to address.

In order to keep pace with competitors, avoiding new models and ideas is not an option. It's critical for organizations to determine whether an idea has transformative properties or is just a flash in the pan — a challenge tackled in Endava's new 2024 Emerging Tech Unpacked Report.


The main takeaway from the report is that, due to the ongoing uncertainty within the tech sector, most decision makers are choosing technologies that offer more noticeable, near-term benefits — such as AI, which nearly 50% of respondents ranked as a top-three initiative. However, despite the space that AI now takes up in the conversation around emerging technology, there are other areas of focus that also show ROI potential.

Additional insights from the report include:

■ Unsurprisingly, AI and generative AI were the top two priorities for organizations included in the study, with only 3% declaring AI not relevant to their business. It is understandable that companies are putting large amounts of resources into AI, particularly generative AI, as many leaders expect it to drive near-term and long-term benefits.

■ After AI, big data and predictive analytics emerged as the third and fourth-highest priorities among organizations. Over 30% of respondents have already implemented both technologies, and a further 30% are in the process of doing so.

■ Internet of things (IoT) was the fifth-highest priority for the study's participants. 40% of respondents already use IoT in some capacity, making it the most implemented technology in this year's study. Though IoT has been around for a while and is not as buzzy as other topics, organizations still see its appeal and application to their business.

■ Virtual reality is one area of technology that is still being treated with caution, as leaders struggle to see it driving business results. 53% of respondents said that the metaverse would be moderately or very relevant, yet only 17% have actually implemented a strategy. With Apple's recent high-profile launch of the Vision Pro, it remains to be seen whether the technology will ever meet the hype it received a few years ago.

All the technologies outlined in the report need quality, well-structured data to be successfully implemented. Data is crucial for training AI models, delivering accurate predictive data, facilitating IoT decision-making, and more. While organizations have different choices for what to invest in, many will start to prioritize data infrastructure and management.

With so many different options for adopting technology, organizations face a daunting landscape filled with promising opportunities and difficult challenges. As businesses navigate these complexities, they must consider how these technologies fit their company's unique circumstances and the timeline for return on investment. As the digital toolkit will undoubtedly further expand in the coming years, businesses will need foresight, adaptability and creativity to use technology to problem solve, and those that think outside of the box will be the most successful.

Matt Cloke is Chief Technology Officer at Endava

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Emerging Technology Priorities Go Beyond AI

Matt Cloke
Endava

Over the past decade, the pace of technological progress has reached unprecedented levels, where fads both quickly rise and shrink in popularity. From AI and composability to augmented reality and quantum computing, the toolkit of emerging technologies is continuing to expand, creating a complex set of opportunities and challenges for businesses to address.

In order to keep pace with competitors, avoiding new models and ideas is not an option. It's critical for organizations to determine whether an idea has transformative properties or is just a flash in the pan — a challenge tackled in Endava's new 2024 Emerging Tech Unpacked Report.


The main takeaway from the report is that, due to the ongoing uncertainty within the tech sector, most decision makers are choosing technologies that offer more noticeable, near-term benefits — such as AI, which nearly 50% of respondents ranked as a top-three initiative. However, despite the space that AI now takes up in the conversation around emerging technology, there are other areas of focus that also show ROI potential.

Additional insights from the report include:

■ Unsurprisingly, AI and generative AI were the top two priorities for organizations included in the study, with only 3% declaring AI not relevant to their business. It is understandable that companies are putting large amounts of resources into AI, particularly generative AI, as many leaders expect it to drive near-term and long-term benefits.

■ After AI, big data and predictive analytics emerged as the third and fourth-highest priorities among organizations. Over 30% of respondents have already implemented both technologies, and a further 30% are in the process of doing so.

■ Internet of things (IoT) was the fifth-highest priority for the study's participants. 40% of respondents already use IoT in some capacity, making it the most implemented technology in this year's study. Though IoT has been around for a while and is not as buzzy as other topics, organizations still see its appeal and application to their business.

■ Virtual reality is one area of technology that is still being treated with caution, as leaders struggle to see it driving business results. 53% of respondents said that the metaverse would be moderately or very relevant, yet only 17% have actually implemented a strategy. With Apple's recent high-profile launch of the Vision Pro, it remains to be seen whether the technology will ever meet the hype it received a few years ago.

All the technologies outlined in the report need quality, well-structured data to be successfully implemented. Data is crucial for training AI models, delivering accurate predictive data, facilitating IoT decision-making, and more. While organizations have different choices for what to invest in, many will start to prioritize data infrastructure and management.

With so many different options for adopting technology, organizations face a daunting landscape filled with promising opportunities and difficult challenges. As businesses navigate these complexities, they must consider how these technologies fit their company's unique circumstances and the timeline for return on investment. As the digital toolkit will undoubtedly further expand in the coming years, businesses will need foresight, adaptability and creativity to use technology to problem solve, and those that think outside of the box will be the most successful.

Matt Cloke is Chief Technology Officer at Endava

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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 ...