Generative and other types of artificial intelligence (AI) top the list of strategic technology trends that organisations need to explore in 2024, says a new report by the technology research and consulting firm Gartner Inc.
"Technology disruptions and socioeconomic uncertainties require willingness to act boldly and strategically enhance resilience over ad hoc responses," said Bart Willemsen, VP analyst at Gartner. "IT leaders are in a unique position to strategically lay down a roadmap where technology investments help their business sustain success amid these uncertainties and pressures."
IT leaders and other executives must evaluate the impacts and benefits of strategic technology trends, "but this is no small task given the increasing rate of technological innovation", said Chris Howard, distinguished VP analyst and chief of research at Gartner.
Mr Howard says deriving business value from the durable use of AI requires a disciplined approach to widespread adoption while paying attention to the risks.
"For example, generative and other types of AI offer new opportunities and drive several trends. But deriving business value from the durable use of AI requires a disciplined approach to widespread adoption along with attention to the risks."
The top strategic technology trends for 2024 are:
- Democratised generative AI: Generative AI (GenAI) is becoming democratised by the confluence of massively pretrained models, cloud computing and open source, making these models accessible to workers worldwide. By 2026, Gartner predicts that over 80% of enterprises will have used GenAI application programming interfaces and models and/or deployed GenAI-enabled apps in production environments, up from less than 5% early 2023.
- GenAI applications can make vast sources of information -- internal and external -- accessible and available to business users. This means the rapid adoption of GenAI will significantly democratise knowledge and skills.
- AI trust, risk and security management: The democratisation of access to AI has made the need for risk management even more urgent. Without guardrails, AI models can rapidly generate compounding negative effects that spin out of control, overshadowing any positive performance and societal gains that AI enables. An updated risk-management approach offers proactive data protection, AI-specific security, model monitoring (including monitoring for data drift, model drift and/or unintended outcomes) and risk controls for inputs and outputs to third-party models and applications.
- AI-augmented development: AI-augmented development is the use of AI technologies, such as GenAI and machine learning, to aid software engineers in designing, coding and testing applications. AI-assisted software engineering improves developer productivity and enables development teams to address the increasing demand for software to run the business. These AI-infused development tools allow software engineers to spend less time writing code.
- Intelligent applications: Intelligent applications include intelligence -- which Gartner defines as learned adaptation to respond appropriately and autonomously -- as a capability. This intelligence can be utilised to better augment or automate work and deliver experiences that dynamically adapt to the user.
- A clear need and demand for intelligent apps exists. Twenty-six percent of CEOs in the 2023 Gartner CEO and senior business executive survey cited the talent shortage as the most damaging risk for their organisation. Attracting and retaining talent is the top workforce priority, while AI was identified as the technology that will most significantly affect their industries over the next three years.
- Augmented-connected workforce: The augmented-connected workforce (ACWF) is a strategy for optimising the value derived from human workers. The need to accelerate and scale talent is driving the trend. The ACWF uses intelligent apps and workforce analytics to provide everyday context and guidance to support the workforce's experience, well-being and ability to develop its own skills.
- Continuous threat exposure management: Continuous threat exposure management (CTEM) is a pragmatic and systemic approach that allows organisations to evaluate the accessibility, exposure and exploitability of an enterprise's digital and physical assets continually and consistently. By 2026, Gartner predicts that organisations prioritising their security investments based on CTEM will realise a two-thirds reduction in breaches.
- Machine customers: Machine customers (also called "custobots") are nonhuman economic actors that can autonomously negotiate and purchase goods and services in exchange for payment. By 2028, 15 billion connected products will exist with the potential to behave as customers, with billions more to follow in the coming years. This growth trend will be the source of trillions of dollars in revenues by 2030 and eventually become more significant than the arrival of digital commerce.
- Sustainable technology: Sustainable technology is a framework of digital solutions used to enable environmental, social and governance (ESG) outcomes that support long-term ecological balance and human rights. The use of technologies such as AI, cryptocurrency, the Internet of Things and cloud computing is driving concern about the related energy consumption and environmental impacts. This makes it more critical to ensure that the use of IT becomes more efficient, circular and sustainable.
- Platform engineering: Platform engineering is the discipline of building and operating self-service internal development platforms. Each platform is a layer, created and maintained by a dedicated product team, designed to support the needs of its users by interfacing with tools and processes. The goal of platform engineering is to optimise productivity, the user experience and delivery of business value.
- Industry cloud platforms: By 2027, Gartner predicts more than 70% of enterprises will use industry cloud platforms (ICPs), up from less than 15% in 2023. ICPs address industry-relevant business outcomes by combining underlying software-, platform- and infrastructure-as-a-service offerings into a whole product offering with composable capabilities. These typically include industry data, a library of packaged business capabilities, composition tools and other platform innovations.
