The most important strategic technology for 2025 and beyond is agentic AI, according to the latest forecast by tech analyst Gartner.
"Agentic AI systems autonomously plan and take actions to meet user-defined goals," said Gene Alvarez, distinguished VP analyst at Gartner, as he revealed the Top 10 Strategic Technology Trends for 2025 at Gartner IT Symposium/Xpo 2024 last week.
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Spending on AI will help drive a healthy increase in IT expenditure. Gartner said worldwide IT spending is expected to total $5.74 trillion in 2025, an increase of 9.3% from 2024.
2025 Top 10 Strategic Technology Trends - Gartner
"It is clear that no matter where we go, we cannot avoid the impact of AI," said Daryl Plummer, distinguished VP Analyst, chief of research, and Gartner Fellow.
Gartner predicts that spending on software will increase 14% to reach $1.23 trillion in 2025, up from 11.7% growth in 2024. Meanwhile, spending on IT services is expected to grow 9.4% to $1.73 trillion in 2025, up from 5.6% in 2024.
Here are Gartner's top 10 strategic technology trends for 2025, led by agentic AI:
Agentic AI - Agentic AI systems autonomously plan and take actions to meet user-defined goals. Agentic AI offers a virtual workforce that can offload and augment human work. Gartner predicts that, by 2028, at least 15% of day-to-day work decisions will be taken autonomously through agentic AI, up from 0% in 2024. The goal-driven capabilities of this technology will deliver more adaptable software systems, capable of completing a wide variety of tasks. AI Governance Platforms - AI governance platforms are a part of Gartner's evolving AI Trust, Risk and Security Management (TRiSM) framework that enables organizations to manage the legal, ethical, and operational performance of AI systems. These technology solutions can create, manage, and enforce policies for responsible AI use, explain how AI systems work, and provide transparency to build trust and accountability. Gartner predicts that by 2028, organizations that implement comprehensive AI governance platforms will experience 40% fewer AI-related ethical incidents compared to those without such systems. Disinformation Security - Disinformation security is an emerging technology category that systematically discerns trust and aims to provide methodological systems for ensuring integrity, assessing authenticity, preventing impersonation, and tracking the spread of harmful information. By 2028, Gartner predicts that 50% of enterprises will begin adopting products, services, or features designed specifically to address disinformation security use cases, up from less than 5% today.Postquantum Cryptography - Postquantum cryptography is data protection that resists quantum computing decryption risks. Analysts expect several types of conventional cryptography to end as quantum developments progress. Gartner predicts that advances in quantum computing will make most forms of asymmetric cryptography unsafe to use by 2029. The switch to postquantum cryptography methods is far from easy. Organizations must have a longer lead time to prepare robust protection of anything sensitive or confidential. Ambient Invisible Intelligence - Ambient invisible intelligence is enabled by ultra-low-cost smart tags and sensors that deliver large-scale affordable tracking and sensing. In the long term, ambient invisible intelligence will create a deeper integration of sensing and intelligence into everyday life. Through 2027, early examples of ambient invisible intelligence will focus on solving immediate problems, such as retail stock checking or perishable goods logistics, by enabling low-cost, real-time tracking and sensing of items to improve visibility and efficiency.
Energy-Efficient Computing - Compute-intensive applications, such as AI training, simulation, optimization, and media rendering, will be the biggest contributors to organizations' carbon footprint as they consume the most energy. New advances starting in the late 2020s will help to boost sustainability. Several new technologies, such as optical computing, neuromorphic computing, and novel accelerators, will emerge for special-purpose tasks such as AI and optimization. These technologies will use significantly less energy. Hybrid Computing - New computing paradigms continue to emerge, including central processing units, graphic processing units, edge computing, application-specific integrated circuits, neuromorphic computing, and classical quantum computing paradigms. Hybrid computing combines different compute, storage, and network mechanisms to solve computational problems.
Spatial Computing - Spatial computing digitally enhances the physical world with technologies, such as augmented reality and virtual reality, and is the next level of interaction between experiences. The use of spatial computing will increase organizations' effectiveness in the next five to seven years through streamlined workflows and enhanced collaboration. By 2033, Gartner predicts spending on spatial computing will grow to $1.7 trillion, up from $110 billion in 2023. Polyfunctional Robots - Polyfunctional machines can do more than one task and are replacing task-specific robots that are custom-designed to perform a single task repeatedly. The functionality of these new robots improves efficiency and provides a faster return on investment. Polyfunctional robots are designed to operate alongside humans to support quicker deployment and easier scalability. Gartner predicts that 80% of humans will engage with smart robots daily by 2030, up from less than 10% today. Neurological Enhancement - Neurological enhancement improves human cognitive abilities using technologies that read and decode brain activity. This technology reads a person's brain using unidirectional brain-machine interfaces or bidirectional brain-machine interfaces (BBMIs). By 2030, Gartner predicts that 30% of knowledge workers will be enhanced by, and dependent on, technologies such as BBMIs (both employer and self-funded) to stay relevant due to the rise of AI in the workplace. This proportion represents a big rise from less than 1% in 2024.
CIOs and IT leaders were reminded of the importance of agentic AI during Gartner's Symposium. It was suggested the CIO role must expand to include responsibilities of the chief AI officer.
In an age of artificial intelligence (AI), chief information officers (CIO) must help stakeholders turbocharge their output.
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The role of the CIO now is much more than delivering access to trustworthy, relevant, timely, and impactful information -- these are table-stakes requirements.
Recent Salesforce research, based on a survey of 150 CIOs of companies with more than 1,000 employees, also found that companies are looking for their CIOs to be AI experts.
Almost two-thirds (61%) of CIOs feel they're expected to know more about AI than they do, and their peers at other companies are their top sources of information.
CIOs are now in the business of manufacturing intelligence and autonomous work. They are responsible for creating a work environment where humans and AI agents can collaborate and co-create stakeholder value.
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Digital leaders must design, own, and deliver the roadmap to the autonomous enterprise. Maximizing enterprise performance with generative AI (gen AI) requires modernizing data foundations and measuring business outcomes.
Gartner's top strategic predictions for 2025 and beyond led with predictions focused on generative AI and agentic AI. Here are the analyst's key predictions for AI-specific future trends:
Through 2026, 20% of organizations will use AI to flatten their organizational structure, eliminating more than half of current middle management positions. Organizations that deploy AI to eliminate middle management human workers will be able to capitalize on reduced labor costs in the short-term and long-term benefits savings. By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are material to their business. AI-generated insights will have a far-reaching impact on executive decision-making and empower board members to challenge executive decisions. By 2028, 40% of large enterprises will deploy AI to manipulate and measure employee mood and behavior. AI can perform sentiment analysis on workplace interactions and communications. By 2027, 70% of new employee contracts will include licensing and fair usage clauses for AI representations of their personas. The large language models (LLMs) that emerge have no set end date, which means employees' personal data captured by enterprise LLMs will remain part of the model during employment and after. By 2027, 70% of healthcare providers will include emotional-AI-related terms and conditions in technology contracts or risk billions in financial harm. By 2028, 30% of S&P companies will use Gen AI labeling to reshape their branding and chase new revenue. CMOs view Gen AI as a tool that can help launch new products and business models. By 2028, 25% of enterprise breaches will be traced back to AI agent abuse from external sources and malicious internal actors. AI agents will significantly increase the invisible attack surface at enterprises and new security and risk solutions will be necessary. By 2028, 40% of CIOs will demand using "Guardian Agents" that are available to autonomously track, oversee, or contain the results of AI agent actions. Enterprises' interest in AI agents is growing, but as a new level of intelligence is added, new Gen AI agents are poised to expand rapidly in strategic planning for product leaders. Through 2027, Fortune 500 companies will shift $500 billion from energy operational spending to microgrids to mitigate chronic energy risks and AI demand. Microgrids are power networks that connect generation, storage, and loads in an independent energy system that can operate on its own or with the main grid to meet the energy needs of a specific area or facility.Agentic AI will be the most important strategic technology for the next few years. Welcome to the age of agentic AI, where companies that grow and thrive will focus on the most important business currencies of trust, speed, scale, and personalization, while also dealing with the balance between automation and meaningful work.