Gartner is presenting its yearly overview of the emerging technologies that enterprise clients should monitor in the years ahead. AI, security, energy-efficient computing, robotics, and virtual computing interactions are featured among the research company’s top 10 strategic technology trends, announced at Gartner’s annual IT Symposium/XPO in Orlando.

To begin with, Gartner anticipates a surge in “agentic AI,” which pertains to intelligent software entities that utilize AI techniques to perform tasks and accomplish objectives, as noted by Gene Alvarez, distinguished vice president analyst at Gartner.

By 2028, it is predicted that at least 15% of everyday work decisions will be autonomously made through agentic AI, rising from 0% in 2024. Agentic AI will be integrated into AI assistants and embedded in software, SaaS platforms, IoT devices, and robotics. Numerous startups are currently branding themselves as platforms for building agentic AI, and hyperscale companies are incorporating agentic AI into their AI assistants, according to Gartner.

Agentic AI holds the promise of a virtual workforce capable of relieving and enhancing human work, as Alvarez noted. The goal-oriented functionalities of this technology will result in more adaptable software systems capable of accomplishing a wide range of tasks. Agentic AI has the potential to fulfill CIOs’ ambitions of enhancing productivity throughout the organization, according to Alvarez.

“Intelligent agents in AI are set to transform decision making and enhance situational awareness in organizations by facilitating faster data analysis and predictive insights. While you rest, these advanced AI agents might assess five of your company’s systems, analyze an immense volume of data beyond human capability, and determine the best course of action,” shared Tom Coshow, senior director analyst with Gartner’s technical service providers division, in a report discussing the role of intelligent agents in AI.

According to Alvarez, AI governance platforms play a critical role in Gartner’s evolving AI trust, risk, and security management (TRiSM) framework, which allows organizations to oversee the legal, ethical, and operational efficacy of their AI systems. These platforms are designed to establish, manage, and enforce policies for responsible AI usage, clarify the functions of AI systems, and enhance transparency, thereby fostering trust and accountability.

One of the notable advantages of implementing AI governance platforms is the potential to prevent ethical incidents related to AI. Predictions from Gartner suggest that by 2028, organizations employing robust AI governance frameworks will see a 40% reduction in AI-related ethical incidents compared to their counterparts lacking such systems.

AI governance platforms advocate for responsible AI practices by enabling organizations to supervise the legal, ethical, and operational effectiveness of AI through a mix of methods and technological tools that ensure robustness, transparency, fairness, accountability, and compliance with risks, as outlined in Gartner’s reports.

Gartner has identified a significant new concern related to artificial intelligence: disinformation security. This emerging area of technology focuses on identifying reliable sources and establishing systematic methods to maintain integrity, evaluate authenticity, prevent impersonation, and monitor the spread of harmful content, as explained by Gartner.

“The widespread access and sophisticated nature of AI and machine learning tools being misused are expected to lead to an increase in disinformation incidents affecting organizations. If not addressed, such misinformation can inflict considerable and enduring harm on any business,” noted Alvarez.

According to Gartner, by the year 2028, half of all enterprises are anticipated to start utilizing products, services, or features tailored to counter disinformation security challenges, a steep rise from less than 5% currently in use.

Moreover, Gartner forecasts that advancements in quantum computing will render most conventional asymmetric cryptography insecure by 2029. This accentuates the importance of post-quantum cryptography, which offers data protection that can withstand potential decryption risks posed by quantum computing.

Asymmetric encryption is ubiquitous, found in numerous software applications, billions of devices across the globe, and the majority of online communications. According to a recent report from Gartner, there may already be “harvest-now, decrypt-later” attacks in action.

Mark Horvath, a vice president analyst at Gartner, emphasized the urgency for organizations to shift towards post-quantum cryptography (PQC) to defend against threats from both classical and quantum computers. However, he warned that this transition won’t be straightforward—it will demand significantly more effort than preparing for Y2K, and the repercussions of failing to adapt could be dire. Furthermore, many organizations have yet to create plans or allocate budgets for this essential change.

One of the significant hurdles in implementing post-quantum cryptography is the lack of straightforward replacement options. Horvath mentioned that there are no direct substitutes for existing cryptographic algorithms, necessitating extensive discovery, categorization, and reimplementation.

To tackle these challenges and facilitate the transition to new algorithms, it’s advisable to start formulating policies regarding algorithm substitutions, data retention, and the processes involved in altering or updating your current cryptographic practices. A program centered on policy development can help mitigate confusion, prevent arbitrary decisions, and enhance manageability.

“With the advancements in quantum computing over the past few years, we anticipate the phasing out of various forms of traditional cryptography that are currently prevalent,” Alvarez remarked. “Transitioning to new cryptographic methods is challenging, so organizations need ample time to prepare themselves to securely protect any sensitive or confidential information.”

Hybrid computing is highlighted in Gartner’s latest report. This type of computing is characterized as a system that integrates computing, storage, and networking mechanisms, aimed at addressing intricate computational challenges. It facilitates technologies like AI in pushing beyond existing technological boundaries.

According to Alvarez, new computing paradigms are constantly emerging, encompassing CPUs, GPUs, edge computing, application-specific integrated circuits, neuromorphic systems, and quantum technologies. He emphasized that hybrid computing is set to foster highly efficient and transformative innovation ecosystems, outperforming traditional computing environments.

Gartner also indicates that energy-efficient computing will remain a key focus. The impact of IT on sustainability is significant, and as we move into 2024, the primary concern for many IT organizations will be their carbon footprint, as stated by Alvarez.

According to Alvarez, applications that require intensive computing, including artificial intelligence training, simulations, optimization, and media rendering, are poised to be the primary contributors to the carbon footprint of organizations due to their high energy consumption.

Green computing or energy-efficient computing comprises both short-term strategies, like utilizing renewable energy sources or upgrading to more energy-efficient hardware, and long-term solutions driven by emerging technologies, according to reports from Gartner.

Current examples of green computing methods include employing application architecture, coding practices, and algorithms that minimize energy usage, investing in new, efficient hardware, and opting for sustainable energy sources. Looking ahead, Gartner notes that more sophisticated approaches, such as innovative computing platforms that are still under research, are on the horizon.

Alvarez anticipates that from the late 2020s onward, various new computing technologies—including optical, neuromorphic, and unique accelerators—will be introduced for specialized tasks like artificial intelligence and optimization, operating with considerably lower energy requirements.

Ambient invisible intelligence refers to the extensive adoption of small, affordable tags and sensors that monitor the location and condition of various objects and environments, as noted by Gartner.

By 2027, initial applications of ambient invisible intelligence are expected to target urgent issues, such as inventory management in retail and the logistics of perishable goods. This approach aims to facilitate low-cost, real-time tracking and sensing of items, ultimately enhancing visibility and operational efficiency, according to Gartner.

Spatial computing enhances the physical world through technologies like augmented and virtual reality. Over the next five to seven years, the implementation of spatial computing will significantly boost organizational effectiveness by streamlining processes and fostering better collaboration. By 2033, Gartner forecasts that the value of spatial computing will rise to $1.7 trillion, a marked increase from $110 billion in 2023.

These advanced systems can perform multiple functions, replacing specialized robots that are tailored to execute a single task. Polyfunctional robots are created to collaborate effectively with humans, allowing for rapid deployment and easier scalability. According to Gartner, by 2030, 80% of people will interact with smart robots on a daily basis, a significant increase from less than 10% today.

This innovative technology aims to enhance human cognitive functions by utilizing methods that interpret and analyze brain activity. It achieves this by employing unidirectional brain-machine interfaces or more advanced bidirectional brain-machine interfaces (BBMIs). These technologies hold significant promise in three primary domains: enhancing human skills, revolutionizing marketing strategies, and boosting overall performance. Neurological enhancements are expected to improve cognitive functions, provide brands insight into consumer thoughts and emotions, and elevate human neural capabilities to achieve better results. According to predictions by Gartner, by the year 2030, 30% of knowledge workers will be augmented by technologies like BBMIs, making them essential for staying competitive as AI continues to evolve in the workplace, a notable increase from less than 1% in 2024.

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