The emerging technology you need on your radar: Gartner

What stage are the 25 most disruptive technologies at, and when will they become reality? Gartner’s annual Emerging Technology Hype Cycle highlights what’s on the cutting edge and what’s at the peak of inflated expectations.

When it comes to the technology that will emerge from research labs into our everyday lives over the next decade, there are four categories, or buckets, we should be thinking about, according to Gartner.

The first is artificial intelligence, a term that entered mainstream conversation after OpenAI’s ChatGPT launched in November 2022. Gartner advises that autonomous AI, in particular, is a key technology we should be paying attention to

“AI’s fast evolution is producing autonomous AI systems that can operate with minimal human oversight, improve themselves and become effective at decision-making in complex environments,” Gartner states.

“These advanced AI systems that can perform any task a human can perform are beginning to move slowly from science fiction to reality. These technologies include multiagent systems, large action models, machine customers, humanoid working robots, autonomous agents, and reinforcement learning.”

The three other buckets we need to be aware of contain technology related to developer productivity, total experience, and human-centric security and privacy programs.

“Even as AI continues to grab the attention, CIOs and other IT executives must also examine other emerging technologies with transformational potential for developers, security and customer and employee experience and strategise how to exploit these technologies in line with their organisations’ ability to handle unproven technologies,” says Arun Chandrasekaran, an analyst at Gartner.

The only disruptive technology that is less than two years away from reaching a plateau is GitOps, according to Gartner.

Atlassian describes GitOps as an “incredibly powerful workflow pattern for managing modern cloud infrastructure,” offering benefits like improved communication, visibility, stability, and system reliability for engineering teams.

Generative AI, or GenAI, has already hit the peak of inflated expectations, according to Gartner. It is now on the verge of entering what Gartner refers to as the “trough of disillusionment.”

“Generative AI (GenAI) is over the Peak of Inflated Expectations as business focus continues to shift from excitement around foundation models to use cases that drive ROI. This is accelerating autonomous AI. While the current generation of AI models lack agency, AI research labs are rapidly releasing agents which can dynamically interact with their environment to achieve goals, although this development will be a gradual process,” Gartner’s research states.

The 5 stages of hype that emerging technology goes through

The Hype Cycle features a timeline that has five stages. The first is an ‘Innovation Trigger.’ Awareness of emerging technologies builds up among early adopters and the general public during this period. The technology then reaches a stage called the ‘Peak of Inflated Expectations,’ where expectations of the technology is at its highest level, and then begins to decline. This is where GenAI sits now.

The ‘Trough of Disillusionment’ follows, and during this time expectations of the technology plummet. All is not lost, however, as after languishing in the trough of disillusionment, the ‘Slope of Enlightenment’ takes place, where expectations of the technology increase again. The final stage is the ‘Plateau of Productivity’ – it is here where expectations are neither inflated, nor are people disillusioned by the hype of its potential. Equilibrium is reached during the plateau, and productivity of the technology is maximised.

Technology that will reach productivity in 2 – 5 years

• Disinformation security
• AI supercomputing
• AI TRISM
• Prompt engineering
• Internal developer portals
• AI-augmented software engineering
• Web assembly
• Generative AI

Technology that will reach productivity in 5 – 10 years

• Spatial computing
• Digital twin of a customer
• Multiagent systems
• Autonomous agents
• Digital immune system
• Reinforcement learning
• Federated machine learning
• Homomorphic encryption
• Superapps
• Cloud native

Technology that will reach productivity in 10+ years

• Large action models
• Humanoid working robots
• Cybersecurity mesh architecture
• 6G
• Artificial General Intelligence (AGI)
• Machine customers

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