In 2025, AI became the defining force across technology sectors, driving new investments, reshaping business models and shifting how organisations build, deploy and scale digital systems. The impact was visible across Indian IT, global startups, Big Tech and global capability centres (GCCs), which recalibrated their plans to accelerate adoption.
Indian IT
This year marked a structural pivot for Indian IT, driven less by optimism and more by measurable AI adoption across enterprises. A joint EY-CII report showed that 47% of Indian enterprises now run multiple GenAI use-cases in production.
This surge changed the $264-billion Indian IT industry, pushing companies to update their services with more automation, cloud tools and enterprise AI.
TCS led the transition with a headline-making $6.5-billion commitment to AI-ready data centres, the first large-scale infrastructure bet by any Indian IT giant.
The IT company reached $1.5 billion in annualised revenue from AI-related services. CEO K Krithivasan told analysts at the company’s Analyst Day 2025 event that this shift from digital to AI is a “huge opportunity” and a “civilizational change” in how enterprises operate.
Infosys, Wipro and HCLTech followed suit by embedding GenAI across delivery lines, from modernisation and cybersecurity to industry-specific platforms.
Infosys secured a landmark $1.6 billion contract from the UK’s National Health Service Business Services Authority, signed in October. Another highlight was HCLTech’s partnership with OpenAI to drive enterprise AI.
Quarterly results showed that AI and cloud projects helped the big IT firms grow steadily, even though they hired fewer people and focused more on bringing in specialists with domain and AI skills.
AI Startups
According to a report by Second Talent, AI startups raised more than $89 billion this year, accounting for 34% of all venture capital, while a separate report by CB Insights shows that they are on track to secure more than half of total annual VC funding for the first time in 2025.
OpenAI announced in March that it raised $40 billion in a funding round, making it the largest private tech funding round ever. The company launched GPT 5.2 and a dedicated Sora app. Meanwhile, ChatGPT turned three in November.
Big funding rounds such as Anysphere’s $2.3 billion and Mistral’s €1.7 billion made it clear that investors now prefer companies building core infrastructure and developer tools instead of flashy AI ideas.
Anthropic added to the momentum with a massive $13 billion Series F round that valued the company at $183 billion. Databricks, the data and AI leader, closed a $4 billion Series L round. This move pushed its valuation past $134 billion.
Anthropic pushed deeper into coding-led AI with the launch of Claude Opus 4.5. Even early-stage players saw remarkable traction, with the Stockholm-based startup Lovable raising $330 million in a Series B funding round at a $6.6 billion valuation.
Big Tech
Big Tech spent this year in an all-out sprint to secure leadership in AI, announcing massive investments in both infrastructure and next-generation models.
Google expects full-year 2025 capital expenditures between $91 billion and $93 billion, Meta allocated between $64 billion and $72 billion, with plans for further increases, and Microsoft spent about $80 billion on AI cloud workloads and data centres.
Amazon led with an estimated $100 billion to $125 billion investment focused on AI capabilities and cloud infrastructure. The cloud giant announced plans to pour up to $50 billion into expanding AI and supercomputing systems for US government customers on AWS.
Meanwhile, Oracle struck one of the biggest cloud-computing deals on record, securing a $300 billion contract with OpenAI that will run for five years from 2027.
At the same time, India is witnessing a boom in data centres. Industry projections suggest the demand is real. India’s data centre demand is expected to surge from 1.3 GW in FY2025 to between 4.7 GW and 5.7 GW by FY2030, attracting a significant influx of investment from both domestic and global players.
Amazon has committed to investing over $35 billion in India by 2030, while Microsoft has pledged $17.5 billion over the next four years to expand its cloud and AI infrastructure in the country.
On the model front, Google pushed aggressively with Gemini, rolling out Gemini 2.0, 2.5 and eventually Gemini 3.0, alongside new AI-native tools such as Antigravity and deeper integration across Cloud and Workspace. The company spent the year clawing back dominance with a calmer, more mature AI strategy. This year, Nano Banana Pro was the company’s most popular image generation model.
Microsoft strengthened its lead in enterprise AI by creating a unified CoreAI engineering group and embedding AI across its cloud, developer stack and productivity platforms. The company also introduced its in-house speech model, MAI-Voice-1, and began public testing of its large language model MAI-1-preview, signalling its ambition to build specialised AI systems.
NVIDIA remained the sector’s growth engine as demand for its chips surged, boosting its valuation toward the $5-trillion mark. At the same time, AMD gained ground with new AI accelerators positioned to challenge its dominance.
GCCs
GCCs had a standout year as multinational companies increasingly turned their India hubs into centres of innovation rather than routine back-office operations. India now hosts more than 1,700 GCCs, with over 100 new centres added in the past two years, according to a Zinnov report.
The firms doubled down on engineering, AI, product development and data-led decision-making. A sharp shift towards AI was visible everywhere. According to a report by EY, about 58% of GCCs reported active investment in agentic AI, while more than 80% placed generative AI on their near-term roadmap.
Alongside IT and engineering, GCCs are now applying AI across customer service, finance, cybersecurity, operations and analytics, supported by dedicated innovation teams and internal AI centres of excellence.
Major GCC hubs include Bengaluru, Hyderabad, Pune, Chennai, Mumbai and the NCR. The industry is expected to grow to $105 billion by 2030, with nearly 2,400 centres employing more than 2.8 million people, further reinforcing India’s position as a leading destination for global enterprise operations.
Talent needs have shifted as well, with companies prioritising data science, cloud engineering, AI/ML and domain expertise over traditional back-office roles.