Gartner Identifies the Top 10 Strategic Technology Trends for 2024

Gartner, Inc. today announced its list of 10 top strategic technology trends that organizations need to explore in 2024. Analysts presented their findings during Gartner IT Symposium/Xpo, which is taking place here through Thursday.

“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's sustenance of success amidst these uncertainties and pressures.”

“They 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. “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:

Democratized Generative AI

Generative AI (GenAI) is becoming democratized 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 APIs and models and/or deployed GenAI-enabled applications 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 democratize knowledge and skills in the enterprise. Large language models enable enterprises to connect their workers with knowledge in a conversational style with rich semantic understanding.

AI Trust, Risk and Security Management

The democratization of access to AI has made the need for AI Trust, Risk and Security Management (TRiSM) even more urgent and clear. 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. AI TRiSM provides tooling for ModelOps, 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.