The AI landscape has undergone significant transformation in the first half of 2025. Industry leaders released a wave of new models, model architecture enhancements surged, and organizations started seeing measurable impact of their genAI initiatives. Strategic bets on agentic systems are also beginning to reshape how AI is applied across industries.
Model Advancements: Who’s Leading the Pack?
Some of the most powerful generative AI models yet were released in early 2025. OpenAI’s GPT-4.5, Google’s Gemini 2.5 Pro, and Anthropic’s Claude 3.7 Sonnet each brought new reasoning or multimodal capabilities. Microsoft doubled down on its Copilot strategy and also released Phi-4-reasoning-plus, a smaller open-weight model that performs impressively on structured reasoning tasks. xAI’s Grok added real-time visual analysis, and DeepSeek’s R1 model made headlines for its cost-efficient training.
There were some setbacks too. Anthropic’s Claude usage declined, OpenAI rolled back a GPT-4o update due to its “sycophant-y and annoying” personality, and Meta delayed the rollout of its Llama 4 Behemoth model.
In addition, in May, Microsoft struck a deal with Anthropic to use its new Claude 4 models to power Microsoft’s AI agent features, reflecting Microsoft’s willingness to branch out from OpenAI.
Capabilities to Watch: Reasoning, Memory, and Agents
As genAI models grow more powerful, new capabilities are beginning to reshape how they’re used across industries. Four standouts from the first half of 2025 are hybrid reasoning, long-term memory, agentic AI, and deep research tools.
- Hybrid Reasoning: The first half of 2025 marked a notable shift in the competitive landscape, with reasoning models emerging as a key differentiator. OpenAI’s o1/o3 models and DeepSeek’s R1 emphasized structured, step-by-step logic. In February, hybrid reasoning — the ability to toggle between fast answers and slower, step-by-step thinking — was introduced by Anthropic and later by Google, giving users more control and enabling deeper support in complex domains.
- Long-term Memory: Long-term memory allows genAI models to retain context across sessions and deliver more personalized interactions. Between February and May, Microsoft, OpenAI, xAI, Anthropic, and Google all introduced long-term memory features, with varying levels of user control to view, modify, or disable what the model remembers.
- AI Agents: 2025 was predicted to be the year of AI agents, and it’s starting to happen. Chinese startup Butterfly Effect launched its autonomous system Manus, while OpenAI, Google, Amazon, and Microsoft all expanded their agentic offerings. These systems can use web browsers, code advanced algorithms, and carry out tasks with minimal human guidance, though their reliability still varies.
- Deep Research Agents: Google, OpenAI, Perplexity, Microsoft, AlphaSense, and others unveiled deep research capabilities, tools that generate structured, source-backed reports from a single prompt. These systems go beyond simple Q&A, breaking down complex queries into multi-step processes that retrieve and synthesize information across multiple sources, while also emphasizing transparency.
Building the Foundation: Strategic Infrastructure
Infrastructure has become a strategic battleground. In January 2025, OpenAI announced Stargate, a $500 billion U.S.-based data center project. Meta plans to spend up to $65 billion this year, and Microsoft announced $80 billion for global data centers.
Alongside the hyperscalers, a new class of providers — neoclouds — are rising fast. CoreWeave went public in March and, along with peers like Lambda Labs and Voltage Park, is reshaping the compute market with AI-optimized infrastructure.
Companies are also acquiring critical pieces of the stack. CoreWeave acquired Weights & Biases and Nvidia bought synthetic data startup Gretel. OpenAI reached an agreement to acquire coding assistant startup Windsurf and announced it would acquire IO, a startup founded by iPhone designer Jony Ive, to develop “a new family of products” designed for the age of Artificial General Intelligence. Google, meanwhile, announced plans to acquire cloud security company Wiz for $32 billion. While not a model play, the deal shows how committed major cloud providers are to securing the AI stack, especially for enterprise adoption.
Enterprise Impact: ROI, Use Cases, and Workforce Shifts
Organizations are beginning to see clear ROI from genAI, especially in areas like content creation, customer service, software development, and cybersecurity. Companies like nib Group and ResMed reported significant cost savings from genAI-powered assistants, while Walmart used LLMs to update hundreds of millions of product entries at a fraction of the time and cost.
Entry-level roles are also evolving across the economy. 86% of executives plan to replace some entry-level roles with AI, while others are creating new roles like data curators, AI ethics specialists, and algorithm trainers. New professionals must know how to interact with AI-generated outputs, verify their accuracy, and integrate them into their workflows.
What Comes Next: Risks and Forward Momentum
Despite the progress, new risks are emerging. Cyberattacks powered by generative AI tools and the spread of AI-generated misinformation are raising concerns. During just the first quarter of 2025, financial losses from deepfake-enabled fraud exceeded $200 million globally. And, contrary to expectations, hallucinations are increasing with some newer genAI models.
Still, the momentum is undeniable. The remainder of 2025 will likely bring more optimized infrastructure. Agentic AI is also poised to really take off in the second half of this year. With major players advancing their agent platforms and startups innovating rapidly, we’ll likely see broader deployment of autonomous systems. GenAI will also likely become more deeply embedded in enterprise systems.
As AI continues to redefine competitive advantages across sectors, technical sophistication will no longer be the only differentiator. How well organizations can align their people, processes, and data strategies to harness the power of AI will increasingly decide winners and losers. Success will depend on more than just deploying the latest models; it will require operational readiness, cultural adaptability, and a clear vision for where AI can drive the most value.
Read the full report for a deeper dive into the companies, capabilities, and strategic bets shaping the generative AI economy in 2025.
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