Artificial intelligence (AI) is rapidly transforming industries through generative models, predictive analytics, intelligent automation, and real-time decision-making. As machine learning (ML) algorithms, cloud infrastructure, and AI chipsets advance, 2025 promises to be a pivotal year for artificial intelligence adoption. Drawing from ABI Research insights, this blog highlights the top eight AI trends, including the rise of Agentic AI and the continued evolution of AI-powered hardware, wearables, enterprise solutions, and more.
Table of Contents
- AI-Powered Computers Will Become the Standard
- AI Smart Glasses Will Gain Momentum
- Agentic AI Will Enable Autonomous Workflows
- AI in Telecom Networks Will Take Longer to Mature
- AI-Powered Cybersecurity Will Expand
- Traditional AI Will Regain Popularity
- Cloud AI Will Drive Scalable Intelligence
- AI Server Infrastructure Will Navigate Global Pressures
1. AI-Powered Computers Will Become the Standard
AI-enabled computing devices are becoming mainstream. By 2025, nearly 60% of PCs sold will come equipped with built-in AI accelerators or on-device AI models to manage real-time data processing and automation. These artificial intelligence-powered systems enable enterprises to improve productivity by streamlining workflows, enhancing content creation, and boosting real-time responsiveness.
Neural Processing Units (NPUs) are becoming more cost-effective, making AI-enhanced PCs accessible to more businesses. Windows 12, expected by late 2025, will feature AI-native Copilot functions, while chipsets like Qualcomm’s Snapdragon X Plus will bring artificial intelligence tools to budget-friendly devices. This trend reflects growing demand for AI computing at the edge.
2. AI Smart Glasses Will Gain Momentum
AI smart glasses represent a major evolution in wearable AI. With more than 700,000 Meta Ray-Ban AI-powered glasses sold in 2024, consumer and enterprise interest in smart wearables is accelerating. These devices offer hands-free AI functionality for tasks like live translation, guided navigation, and immersive training.
Advances in computer vision and gesture recognition make AI-based Extended Reality (XR) more intuitive. Applications now span virtual product demonstrations, logistics, and industrial simulation. Tech giants including Google, Samsung, Huawei, Lenovo, and Xiaomi are expanding their AI glasses portfolios to address the increasing market demand.
3. Agentic AI Will Enable Autonomous Workflows
Agentic AI is emerging as a key artificial intelligence trend for 2025. Unlike generative AI, which focuses on producing content, Agentic AI involves autonomous AI agents that take action, make decisions, and execute structured workflows with minimal human intervention.
Powered by fine-tined Large Language Models (LLMs), Agentic AI agents can classify documents, extract and process enterprise data, and update backend systems. These agents operate on defined goals, feedback loops, and contextual understanding, enabling full task execution from start to finish.
Real-world applications of Agentic AI, as identified by Principal Analyst Reece Hayden, include:
- Telecom providers supporting broadband self-service using autonomous agents
- Banks deploying AI for complaint classification and response generation (e.g., Crédit Agricole)
- Manufacturers embedding AI into ERP systems to automate order management (e.g., Beam AI)
The business benefits of enterprise AI agents capable of in-depth reasoning are substantial: faster decisions, fewer manual errors, and scalability across departments. While full autonomy is still aspirational, ABI Research forecasts that Agentic AI will play a major role in intelligent automation strategies. Humans will remain in the loop to supervise and validate AI outputs, particularly in regulated environments.
4. AI in Telecom Networks Will Take Longer to Mature
Artificial intelligence in telecommunications holds massive potential, but full-scale deployments will remain limited in 2025. Initiatives like the AI-RAN Alliance are promoting AI for radio access network (RAN) automation, bandwidth allocation, and network optimization. Still, commercial rollout is expected closer to 2026 or beyond.
Telecom operators will continue with pilot programs for AI-based traffic management, predictive maintenance, and fraud detection. Challenges such as interoperability, cost, and regulations remain key obstacles. Companies like SoftBank and NVIDIA are leading initial trials, setting the stage for future AI-enabled telecom infrastructure.
5. AI-Powered Technologies in Cybersecurity Will Expand
As cyber threats evolve, AI-driven cybersecurity solutions are becoming critical. In 2025, enterprises will invest heavily in AI-powered threat detection, automated encryption, and anomaly detection systems. A recent CrowdStrike survey found 63% of IT teams now prefer AI-enhanced cybersecurity platforms.
Artificial intelligence models will identify suspicious behavior, manage encryption keys, and validate identities in real-time across hybrid and multi-cloud environments. These capabilities are particularly vital in healthcare, finance, and other highly regulated sectors that demand strong digital trust frameworks.
6. Traditional AI Will Regain Popularity
While generative AI dominates headlines, traditional AI techniques remain foundational. According to Amazon Web Services (AWS), nearly 85% of current enterprise AI deployments do not involve generative models, underscoring the continued relevance of classic ML algorithms.
High failure rates in Gen AI pilots (estimated between 80%-90%) are pushing companies to revisit tried-and-tested AI approaches for computer vision, forecasting, and classification. Generative models will complement rather than replace traditional AI, enhancing established systems without disrupting workflows.
7. Cloud AI Will Drive Scalable Intelligence
Cloud AI is a foundational element of AI developments in 2025, as enterprises adopt cloud-native platforms to scale intelligent workloads. ABI Research projects a 23% CAGR in the cloud AI chipset market through 2030, with revenues nearing US$119 billion.
Cloud AI enables real-time training, inference, and data processing across public, private, hybrid, and telco cloud environments. Major providers like AWS, Microsoft Azure, and Google Cloud offer scalable infrastructure to support AI workloads ranging from generative models to predictive analytics.
As Gen AI adoption rises, demand for GPU-accelerated compute and Application-Specific Integrated Circuits (ASICs) surges. Enterprises also face growing pressure to optimize infrastructure for power efficiency, latency, and cost. The shift toward edge and hybrid deployments is critical to managing this demand.
Telco cloud remains in early stages, but sovereign cloud platforms such as Telefónica’s Tech Cloud are emerging to support compliance and customization. These dynamics underscore how cloud AI is not just a technology trend—it is becoming an operational backbone for digital transformation.
8. AI Server Infrastructure Will Navigate Global Pressures
AI servers are central to supporting next-generation artificial intelligence applications. ABI Research estimates the global AI server market size will reach US$245.2 billion, reflecting 25% year-over-year growth.
Yet geopolitical risks, trade tariffs, and supply chain complexity are reshaping how AI server OEMs—such as Dell, Supermicro, HPE, and Penguin Solutions—build and distribute infrastructure. AI servers rely on specialized silicon and components sourced from globally distributed suppliers in regions like Taiwan, Malaysia, and South Korea.
Recent tariffs introduced in 2025 triggered volatility across tech markets, impacting procurement, inventory strategies, and CAPEX planning. While hyperscalers like Amazon, Google, and Microsoft are ramping AI data center investments (each committing over US$75 billion in 2025), enterprise buyers face cost pressures and delivery challenges.
OEMs are exploring mitigation strategies such as:
- Cost pass-through pricing
- Margin absorption
- Supply chain diversification and nearshoring (e.g., assembly in Mexico under USMCA exemptions)
Despite these hurdles, demand for AI compute remains inelastic, particularly for workloads involving Agentic AI and large-scale model training. ABI Research expects OEMs with agile supply chains and transparent pricing strategies to emerge stronger amid these headwinds.
More Insights Into the Future of AI
The artificial intelligence landscape in 2025 will focus on practical innovation and enterprise adoption. Key AI trends such as Agentic AI, AI-powered hardware, smart wearables, domain-specific agents, and cybersecurity platforms reflect a shift toward actionable and business-centric use cases. ABI Research will continue to provide in-depth coverage of emerging AI trends, generative and traditional models, and the evolving AI market.
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