The Big Names in AI (2025): Who They Are, What They Do, Where They’re Going

Artificial Intelligence has rapidly become the defining theme of this decade — not just in technology, but across every industry and financial market.
From chipmakers powering neural networks to software giants building large language models and AI assistants, the “AI stack” now stretches across the world’s most valuable companies.

This guide gives you an overview of the biggest names in AI — what they do, how they got here, where they’re going next, and insights into how their stock has performed over the past two years.

NVIDIA (NVDA) — the compute engine of AI

What they do: NVIDIA designs the GPUs and full-stack systems (CUDA, cuDNN, networking, software) that train and run frontier models.
History in brief: Pivoted from gaming GPUs to accelerated computing in the 2010s; Data Center became the growth engine with the A100/H100 era. In 2024 NVIDIA unveiled Blackwell (B200, GB200) to power the next wave of generative and agentic AI.
Where they’re going: Scaling “AI factories,” Earth-2 digital twins, and end-to-end platforms with hyperscalers and sovereign AI partners.
Market snapshot: Price $202.49 (USD). Two-year trend: strong uptrend through 2024–25 on hyperscaler capex and model demand; periodic pullbacks on supply/valuation headlines.

Microsoft (MSFT) — the Copilot + Azure flywheel

What they do: AI across Copilot (workflows), Azure AI (model hosting), and a deep strategic relationship with OpenAI.
History in brief: Windows/Office giant that turned Azure into a hyperscale cloud; 2023–25 cemented an “AI first” product cadence across the stack.
Where they’re going: New OpenAI terms (bigger multi-year Azure commitments, loosened exclusivity), broader model choice (e.g., Mistral) to court enterprises and governments.
Market snapshot: Price $517.81 (USD). Two-year trend: steady climb as Copilot monetization and Azure AI usage scale.

Alphabet (GOOGL) — Gemini everywhere

What they do: Gemini models across Search, YouTube, Android, and Vertex AI; custom TPU silicon.
History in brief: Pioneered the “transformer”; 2024–25 consolidated under Gemini 2.0 with multimodal/tool-use capabilities for the “agentic era.”
Where they’re going: Deeper agentic features inside Google apps and enterprise ML on Vertex AI.
Market snapshot: Price $281.19 (USD). Two-year trend: re-rating as Gemini matured and Cloud turned profitable.

Amazon (AMZN) — AI as a cloud service (Bedrock + chips)

What they do: AWS Bedrock (managed access to top models), Claude via a $4B Anthropic deal, and custom Trainium/Inferentia AI chips.
History in brief: The pioneer of cloud turns AI into “a service” for builders; 2024–25: Bedrock adoption and Claude integrations.
Where they’re going: Verticalized AI services, tighter model + silicon economics inside AWS.
Market snapshot: Price $244.22 (USD). Two-year trend: strong rebound with cloud optimization cycle and GenAI workloads.

Meta (META) — open-weight LLMs at consumer scale

What they do: Social platforms (Facebook, Instagram, WhatsApp) and widely used open-weight Llama family for developers.
History in brief: Rebranded to Meta (2021), doubled down on long-horizon AI + metaverse; 2024–25: Llama 3/3.2 push and AI-driven ranking/ads efficiency.
Where they’re going: More capable open-weight models and AI agents inside consumer apps.
Market snapshot: Price $648.35 (USD). Two-year trend: major recovery from 2022 lows; volatility around capex and Reality Labs spend.

Apple (AAPL) — “Apple Intelligence,” privacy by design

What they do: Apple Intelligence weaves on-device + private cloud models into iPhone, iPad, and Mac (writing tools, image edits, a more capable Siri).
History in brief: Long AI investment under the hood (Neural Engine); 2024 public roll-out of consumer AI UX.
Where they’re going: Personal, context-aware assistants; tight device-silicon-software integration.
Market snapshot: Price $270.37 (USD). Two-year trend: range-bound in 2023, firming with Apple Intelligence adoption in 2024–25.

Tesla (TSLA) — autonomy + robots on custom AI infrastructure

What they do: End-to-end, vision-only autonomy stack (FSD v12+), Dojo training, and humanoid robot Optimus development.
History in brief: From EV disruptor to AI-first mobility company; massive training-compute ramp in 2025.
Where they’re going: Higher-scale fleet learning, software margins, and non-auto AI applications.
Market snapshot: Price $456.56 (USD). Two-year trend: volatile; sentiment tracks FSD rollout cadence and margin mix.

AMD (AMD) — alternative AI accelerators at scale

What they do: Instinct MI300/MI325 accelerators, ROCm software, EPYC CPUs — the main alternative to NVIDIA in training/inference.
History in brief: CPU/GPU turnaround under Lisa Su; AI pivot accelerated 2023–25 with MI300 family.
Where they’re going: Faster product cadence (MI325/MI350 roadmap), cloud wins, and growing software ecosystem.
Market snapshot: Price $256.12 (USD). Two-year trend: up strongly on AI accelerator traction; competitive dynamics vs. NVIDIA drive swings.

TSMC (TSM) — the foundry behind the AI boom

What they do: Manufactures the world’s most advanced chips (3nm/2nm) and advanced packaging (CoWoS) used in AI GPUs.
History in brief: Continued to expand CoWoS capacity (target: ~2x in 2025) and ramp leading nodes to meet AI demand.
Where they’re going: Packaging and node leadership (N3/N2) to support ever-larger AI systems.
Market snapshot: Price $300.43 (USD). Two-year trend: up with AI supply chain build-out; sensitive to cycle/supply headlines.

Oracle (ORCL) — OCI as an AI infrastructure dark horse

What they do: Oracle Cloud Infrastructure (OCI) + close NVIDIA partnership (DGX Cloud, Grace Blackwell, NIM microservices) powering AI training/inference and sovereign AI.
History in brief: Rapid GPU capacity build-out, distributed cloud for data residency.
Where they’re going: “AI anywhere” — public cloud, Dedicated Region, and Alloy for regulated sectors.
Market snapshot: Price $262.61 (USD). Two-year trend: re-rating as AI workloads land on OCI; still benchmarked vs. hyperscaler peers.

IBM (IBM) — enterprise AI with governance

What they do: watsonx (ai/data/governance) platform for regulated, enterprise-grade AI — open-model choice, lifecycle tooling, and controls.
History in brief: 2023 launch of watsonx; 2024–25 expanded with governance and industry use cases.
Where they’re going: Trust, risk, and compliance as differentiators; hybrid/multicloud deployments.
Market snapshot: Price $307.41 (USD). Two-year trend: steady; investor focus on software mix and AI services pull-through.

Palantir (PLTR) — applied AI for operations

What they do: AIP (Artificial Intelligence Platform) to build AI apps, actions, and agents on enterprise data, plus Foundry/Gotham.
History in brief: 2023 “AIP sprint” catalyzed commercial demand; 2025 feature cadence continues.
Where they’re going: More “agentic” workflows and packaged industry solutions.
Market snapshot: Price $200.47 (USD). Two-year trend: sharply higher amid AIP adoption; volatile around earnings cadence.

Broadcom (AVGO) — AI networking & custom silicon

What they do: High-speed networking (switch/optics) and custom silicon that underpins AI data centers.
History in brief: Beneficiary of the AI networking upgrade cycle; VMware integration adds software leverage.
Where they’re going: Ethernet-based AI fabrics and “AI factory” infrastructure.
Market snapshot: Price $369.63 (USD). Two-year trend: up with AI networking demand; digestion phases around M&A.

Also in the conversation (private companies — no share prices)

• OpenAI: Creator of ChatGPT and GPT-series models; deep ties with Microsoft Azure; 2025 partnership evolution adds massive Azure commitments and relaxes exclusivity.

• Anthropic: Claude family; strategic collaboration with AWS/Bedrock; $4B investment from Amazon completed in 2024 and deepened in 2024–25.

• Mistral AI: Open and proprietary LLMs; partnerships to distribute on Azure; UK CMA declined to probe Microsoft tie-up (competition context).

At SmartInvestorsAI.com, we explore the impact of AI on investing — providing insights that empower, not overwhelm. As always, use technology wisely, stay informed, and invest with your eyes open.

Disclaimer
This article is for informational purposes only and does not constitute financial advice. All investing involves risk, and past performance is not indicative of future results. Readers should conduct their own research and consult a qualified advisor before making investment decisions.