..... . VALI disclosures . .....: 26/02/26, IT vs AI

Monday, February 16, 2026

26/02/26, IT vs AI

The $280-billion plus Indian IT services industry is in the midst of a structural upgrade as they navigate an artificial intelligence (AI) led reset in its businesses.

From Tata Consultancy Services (TCS) committing significant capital to build AI-ready data centre infrastructure and rehauling its business, to Infosys scaling its Topaz platform and LTIMindtree (now LTM) winning multi-year AI-led transformation deals through BlueVerse, the shift is already visible. HCLTech, too, is positioning itself to capture clients' AI-driven discretionary spending.

This transition has been in the works for at least over a year for most of these Tier-1 IT majors, and this is reflected in the steadfast belief Indian investors held in the past couple of weeks, even as the US-driven AI panic led to a stock rout.

TCS declared its ambition to become the world's largest AI-led technology services company during its Analyst Day in December 2025.

The company has identified five pillars of growth that include “driving an AI-first culture, refining services, reskilling the current workforce through learning paths, developing innovative cross-industry solutions, and expanding the AI ecosystem through M&A and venturing into new businesses,” an Axis Direct note said.

To this extent, in the October-December quarter alone, TCS had announced two mid-sized Salesforce acquisitions and launched a data centre-focused joint venture. In the third quarter, TCS acquired Salesforce consulting and AI solutions firm Coastal Cloud in a $700-million all-cash deal, and ListEngage MidCo in October for $72.8 million.

TCS currently plans to invest approximately $6.5 billion into building 1 GW of data centre capacity over the next five to seven years.

As of November, TCS said it will be investing $2 billion (Rs 18,000 crores) along with global alternate asset management firm TPG to fund its AI data centre business, HyperVault. The investment will happen in tranches over the next few years.

Moneycontrol had previously reported that TCS is in talks to sign up hyperscalers, including Amazon Web Services (AWS) and artificial intelligence firm OpenAI, as anchor customers for its first data centre coming up in Navi Mumbai.

TCS' AI services now generate $1.8 billion in annualized revenue and are growing at 17.3% QoQ in constant currency. The Mumbai-headquartered IT major has worked on 5,000 AI projects to date.

“We remain steadfast in our ambition to become the world's largest AI-led technology services company, guided by a comprehensive five-pillar strategy. We are delivering accelerated value to our clients through strategic investments across the full AI stack, from infrastructure to intelligence,” TCS CEO and MD K Krithivasan said in January during the company's earnings conference.

Infosys' bestseller ‘Topaz'

“Until 2025, Infosys was experimenting with GenAI. From FY2026, the company has undertaken measures to scale GenAI both internally and with clients,” noted analysts at Kotak Institutional Equities.

Analysts expect Infosys to possibly lead in AI adoption in the medium to long term, although the company's management has yet to disclose its AI revenue, unlike TCS, Accenture, and HCLTech.

Infosys offers an AI suite of solutions and platforms, Topaz, and generative AI technologies. It brings the advantage of over 12,000 AI assets, 150-plus pretrained AI models, and 10-plus AI platforms.

Speaking to Moneycontrol on the sidelines of the World Economic Forum (WEF) last month, Infosys CEO Salil Parekh said the Bengaluru-based company is seeing opportunities from AI, even as parts of traditional work come under pressure.

“We see some places where there's compression and some places where there's growth. And we see the growth a little bit more than what we see on the compression,” he said.

Parekh highlighted that AI is creating new service demand across software development, customer service, and modernisation of legacy applications, driven by increasing adoption of AI agents and broader use of different foundation models.

The company is also developing AI orchestration layers and infusing domain and client context on top of generic foundational models and AI agents.

HCLTech bets on ‘advanced AI'

HCLTech reported $146 million in advanced AI revenue for the December quarter of FY26 (Q3FY26).

The advanced AI business grew nearly 20 percent sequentially, even as overall company revenue rose 4.2 percent quarter-on-quarter in constant currency terms; making AI-led revenue opportunities critical for the overall growth.

HCLTech defines advanced AI revenue as work done across physical AI, robotics, agentic AI, data centres, and intellectual property, and excludes AI that is merely embedded within existing services or data and analytics engagements.

HCLTech offers the AI Force platform and the AI Foundry. AI Foundry is an enterprise-scale Data and AI managed services solution helping organisations to modernize data, simplify insights ,and scale AI responsibly. It bridges the gap between experimentation and production, with 50% faster time to production and 45% lower platform management costs.

CEO and MD C Vijayakumar expects discretionary spending will now come from emerging technologies and newer pockets, primarily driven by AI.

“I believe there is little value in waiting for either historical or anticipated discretionary spending to resume. Instead, the focus should be on opportunity, identifying proactively where the spending is occurring and targeting those opportunities,” he said during the company's earnings conference.

Wipro sees clients reshape priorities

Wipro executive chairman Rishad Premji recently weighed in on AI, saying Indian IT services companies are moving fast enough on AI and are not behind the curve.

Speaking at WEF, Premji said the complexity of the AI journey is in fact creating a broader opportunity for services firms to guide and execute adoption.

“And so that creates huge opportunities actually for services companies, all the way from helping a customer in terms of advising them on their journey of AI, helping them actually curate data, helping them leverage the curated data to fine-tune the models, helping identify the use cases,” he said.

Wipro too has been leveraging the platforms that it has built for use cases, to fine-tune AI models, to build out the agentic AI, to manage the use cases, to orchestrate it and to deliver it continuously, Premji said.

Wipro Chief Executive Officer Srinivas Pallia said AI has now become board level mandate led by CEO's, who see it as the lever to “unlock productivity” and create lasting competitive advantage.

Speaking at the company's earnings conference, Pallia noted that organisations are “reshaping priorities as AI influences how they plan, invest, and operate.”

Tech Mahindra's LLM push

Tech Mahindra has been the only Indian IT company to build its own large language model (LLM). It is currently a part of the IndiaAI Mission, developing an education-sector-focused sovereign LLM built on 8-billion parameters.

Prior to this, the Pune-headquartered IT firm was working on Project Indus to build its own 1-billion-parameter LLM when it decided to shift gears to participate in the IndiaAI Mission and repurpose the models.

Tech Mahindra CEO and MD Mohit Joshi emphasised AI being a key growth pillar for its strategy during its Q3 earnings conference, as customers are increasingly moving from pilots to scaled deployments – also ensuring quality and durability of revenue.

“We are seeing AI increasingly embedded across large enterprise engagements, driving business experience, process and operations transformation, IT build and change, as well as IT operations,” he said during an earnings call in January.

Joshi believes AI is bringing the IT services industry “back in the limelight” as clients have evolved to understand the need for data readiness and clean data for AI use cases.

“You need to make sure that your apps are simplified and modernised. Only then can you get AI and start that virtuous cycle. This means that a lot of the work that the industry is very good at, which is building out modern data stacks, simplifying applications, will come back in the limelight,” Joshi told Moneycontrol on the sidelines of the WEF Davos in January

Report by Debangana Gosh for Network18

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Trade Cycles

The four important features of Trade Cycle are (i) Recovery, (ii) Boom, (iii) Recession, and (iv) Depression!

The trades cycle or business cycle are cyclical fluctuations of an economy. A full trade cycle has got four phases: (i) Recovery, (ii) Boom, (iii) Recession, and (iv) depression. The upward phase of a trade cycle or prosperity is divided into two stages—recovery and boom, and the downward phase of a trade cycle is also divided into two stages—recession and depression.

Phases of Trade Cycle:

The phases of trade cycle are explained with a diagram:

(1) Recovery:

In the early period of recovery, entrepreneurs increase the level of investment which in turn increases employment and income. Employment increases purchasing power and this leads to an increase in demand for consumer goods.

As a result, demand for goods will press upon their supply and it shall, thereby, lead to a rise in prices. The demand for consumer’s goods shall encourage the demand for producer’s goods.

The rise in prices shall depend upon the gestation period of investment. The longer the period of investment, the higher shall be the price rise. The rise of prices shall bring about a change in the distribution of income. Rent, wages, interest do not rise in the same proportion as prices.

Consequently, the margin of profit improves. The wholesale prices rise more than retail prices. The prices of raw materials rise more than the prices of semi-finished goods and the prices of semi-finished goods use more than the prices of finished goods.

(2) Boom:

The rate of investment increases still further. Owing to the spread of a wave of optimism in business, the level of production increases and the boom gathers momentum. More investment is possible only through credit creation. During a period of boom, the economy surpasses the level of full employment and enters a stage of over full employment.

(3) Recession:

The orders for raw materials are reduced on the onset of a recession. The rate of investment in producers’ goods industries and housing construction declines. Liquidity preference rises in society and owing to a contraction of money supply, the prices falls. A wave of pessimism spreads in business and those markets which were sometime before sellers markets become buyer’s markets now.

(4) Depression:

The main feature of a depression is a general fall in economic activity. Production, employment and income decline. The prices fall and the main factor responsible for it is, a fall in the purchasing power.

The distribution of national income changes. As the costs are rigid in nature, the margin of profit declines. Machines are not used to their full capacity in factories, because effective demand is much less. The prices of finished goods fall less than the prices of raw materials.

✳Reality Tips to Traders

1)Trading in the stock market is a marathon. 2)Protecting your capital is key. (Learn to protect first) 3)Making 0 on the day is better than losing 50k 4)Losses happen; they are part of this business. 5)It’s not you vs. the market. It’s you VS you. 6)You are your biggest enemy; learn to be mentally disciplined. 7)Don’t follow the majority; follow the correct path. 8)Traders without a stop loss end up not being traders for long. 9)There is always another trade. 10)The big money is made waiting for the right set-ups. 11)Waiting for the right trade is the most powerful strategy. 12)It is better to cut a loss than to wait to be proven right. 13)Position sizing can make or break you. 14)Worry about the downside before you even think about the upside. 15)Don’t listen to headlines

..BANKING TERMINOLOGY

There are various types of Banks: PSU Banks, Private Banks, Co-operative/Regional Banks, Small Finance Banks and Foreign Banks. When you deposit money in a bank, let's say the bank gives you an interest rate of 4%. But when the bank lends out this money, they lend it out at say, 12%. The difference of 8% in the above scenario is effectively the profit of the bank! The loans that do not pay interest for 90 days are known as Non-performing Assets. Banks have to provide for such bad loans. Structure of a Bank Asset for a Bank: The asset portion of a bank's capital includes cash, government securities, and interest-earning loans (e.g., mortgages, letters of credit, and inter-bank loans). Liabilities for a Bank: The bank's main liabilities are its capital (including cash reserves and, often, subordinated debt) and deposits. The latter may be from domestic or foreign sources (corporations and firms, private individuals, other banks, and even governments). Banks are required to maintain Liquidity with the Reserve Bank of India: SLR (Statutory Liquidity Ratio): It is the money a bank needs to preserve in the form of cash, gold or government Bonds before providing credit customers. This limitation is added by RBI on banks to make funds available to customers on-demand at your earliest convenience. Banks are required to maintain SLR at 18%. CRR (Cash Reserve Ratio): Banks are required to hold a certain proportion of their deposits in the form of cash. Banks don’t hold these as cash with themselves, but deposit such amounts with RBI / currency chests. CRR rate is at 4.5% currently. Repo Rate: The rate at which the RBI lends short-term money to the banks. The RBI through its Monetary Policy committee changes the repo rate to balance growth and Inflation. Reverse Repo rate: The rate at which banks park their short-term excess liquidity with the RBI. Now let us understand various terminologies for Banks Net Interest Income (NII): This is the spread the bank makes on its lending. It is calculated as Interest Income – Interest Expended Net Interest Margin (NIM): This is the spread the bank makes on its lending. It is the earning which is left after deducting the cost paid to depositors from its yields on Loans. This is denoted in % terms. The formula is Yield on Loans – Cost of funds Capital Adequacy Ratio (CAR): The capital adequacy ratio (CAR) is a measure of a bank's available capital expressed as a percentage of a bank's risk-weighted credit exposures. Essentially, it is the Capital that is available to lend. Tier I Capital – In simple words this capital is freely available with the bank to lend out. Tier II Capital- This is the capital tied up somewhere and is less freely available to lend. In case of an adverse event, the bank can use this capital to lend. Under Basel III norms, a bank’s tier 1+tier 2 capital must be a minimum of 8% of its risk-weighted holdings. The minimum capital adequacy ratio, also including the capital conservation buffer, is 10.5%. Current Account Saving Account (CASA)- There is no interest paid on the Current Account and a small interest rate is paid on a savings account. The combination of both is called CASA which shows the liabilities of the bank on which it pays relatively less interest. Deposits: Bank deposits are a savings product that customers can use to hold an amount of money at a bank for a specified length of time. In return, the financial institution will pay the customer the relevant amount of interest, based on how much they choose to deposit and for how long. Now let us come to NPA. Gross NPA (GNPA): It is the total loans on which no payment has been paid for 90 days or more. GNPA % is usually shown in each Bank’s quarterly results. The percentage is basically the GNPA amount as a % of the total advances. Slippages: Slippages denote the fresh amount of loans that have turned bad in a year. The slippage ratio of a bank is calculated as Fresh accretion of NPAs during the year /Total standard assets at the beginning of the year multiplied by 100. Provisioning Coverage Ratio (PCR): This is the ratio of provisioning to GNPA and indicates the extent of funds a bank has kept aside to cover loan losses. For Instance, a company has GNPAs of Rs 100 and they have set aside 50 Rs, then the PCR is 50%. Net NPA (NNPA): The total figure left after deducting provisions made for bad loans from GNPA. (GNPA – Provisions+upgrades/writeoffs = NNPA) Special Mention Account (SMA) SMA-0 is a category in which stress with respect to the principal and interest has remained overdue for a period of 0 to 30 days. SMA-1 is a category in which stress with respect to the principal and interest has remained overdue for a period of 30-60 days. SMA-2 is a category in which stress with respect to the principal and interest has remained overdue for a period of 60-90 days

..... . VALI disclosures . .....

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Monday, February 16, 2026

26/02/26, IT vs AI

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16/02/26, AI is thinking, writing and calculating faster and cheaper than ever. With white-collar jobs at risk, are Science, Commerce or Humanities still safe bets?

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