Nearly Half of Indian IT-Sector M&A Deals in Past Two Fiscal Years Linked to AI Capabilities, Crisil Says

Artificial intelligence has become one of the most important drivers of mergers and acquisitions across India's technology-services industry, with nearly half of the deals undertaken by leading IT companies over the past two financial years linked to AI and related capabilities, according to Crisil Ratings.

The shift represents a significant change in acquisition strategy. Indian IT companies historically used acquisitions to expand geographically or acquire capabilities in cloud computing, automation and analytics. AI has now emerged as a primary strategic trigger as clients demand faster deployment, specialised engineering talent and measurable productivity improvements. (ETCIO.com)

Crisil assessed around 90 M&A transactions across the sector. Over the latest two fiscal years, acquisition targets have increasingly brought capabilities spanning artificial intelligence, data engineering, digital engineering, engineering research and development and enterprise platforms. (ETHRWorld.com)

The trend suggests that Indian IT companies increasingly view acquisitions as the fastest way to close capability gaps that might otherwise require years of internal hiring and development.

AI Moves From Experimentation to Acquisition Strategy

Artificial intelligence initially entered corporate technology budgets largely through pilots.

Companies tested:

generative AI assistants,

coding tools,

chatbots,

and automation applications.

That stage is rapidly evolving.

Enterprise customers now increasingly expect IT vendors to deploy AI inside production systems and demonstrate tangible business outcomes.

Crisil says this transition has moved AI from experimental technology toward a boardroom priority, encouraging IT companies to use inorganic investment to accelerate capability creation. (ETCIO.com)

Nearly Half of Recent Deals Carry AI Angle

The scale of the shift is significant.

Among the transactions assessed by Crisil, nearly half of M&A activity across the past two fiscals was linked to obtaining AI or related advanced-technology capabilities.

That does not mean every target was a pure artificial-intelligence company.

Many acquisitions provide complementary capabilities such as:

data engineering,

cloud platforms,

engineering R&D,

digital engineering,

and industry-specific technology.

These capabilities increasingly form the infrastructure required to deliver enterprise AI projects.

Earlier Acquisitions Focused More on Digital Transformation

Between fiscals 2019 and 2024, Indian IT-sector acquisitions were more commonly aimed at strengthening conventional digital capabilities or expanding geographic reach.

Cloud computing, process automation and analytics were important acquisition themes during that period. (ETCIO.com)

The transition toward AI illustrates how quickly the competitive priorities of the IT-services industry have changed.

Cloud capability remains essential.

But clients increasingly expect cloud infrastructure to support AI applications rather than simply conventional digital transformation.

Acquisitions Can Reduce Capability-Building Time

Developing a specialist AI practice internally can take years.

Companies need to recruit:

AI engineers,

data scientists,

domain experts,

and product specialists.

They also need intellectual property, reference customers and proven delivery experience.

Buying an established company can provide many of these capabilities immediately.

Crisil Director Aditya Jhaver said acquisitions can shorten capability development from years to months as enterprise AI adoption accelerates. (ETCIO.com)

Talent Is One of the Most Valuable Acquisition Assets

Many technology acquisitions are effectively talent acquisitions.

Highly experienced AI engineers remain scarce.

Specialist firms may already employ teams capable of building:

machine-learning platforms,

agentic AI systems,

and enterprise automation.

Large IT companies can acquire those teams in one transaction instead of competing for individual employees.

Proprietary Platforms Add Strategic Value

Indian IT services companies have traditionally generated most revenue from human expertise and project execution.

AI creates an opportunity to add more intellectual property.

Acquisition targets may possess:

software platforms,

industry-specific AI tools,

automation frameworks,

or reusable engineering assets.

These can help IT companies move beyond purely labour-based delivery.

Enterprise Customers Want Faster AI Deployment

Clients are increasingly unwilling to spend years developing experimental AI systems.

They want projects that can enter production quickly.

IT vendors therefore need pre-built technology, experienced teams and proven architectures.

Acquisitions can make those capabilities available immediately.

That can become a competitive advantage when bidding for large transformation contracts.

More Than 70% of Recent Targets Were Overseas

The acquisition strategy has also become heavily international.

Crisil said more than 70% of targets acquired during the past two fiscals were based in the United States and Europe. (ETCIO.com)

Indian IT companies are targeting these markets partly because they contain deep pools of specialised AI talent and established enterprise customers.

US and Europe Offer Specialist Talent Pools

North America and Europe contain large concentrations of:

AI startups,

cloud architects,

engineering firms,

and industry-specific technology companies.

Acquiring these businesses can simultaneously provide Indian IT firms with technology capability and access to customers.

That combination can be difficult to replicate through organic hiring alone.

Local Presence Also Helps Win Enterprise Contracts

Large global clients often value vendors with strong local teams.

An acquisition in the US or Europe can provide:

sales relationships,

consulting talent,

and delivery capabilities.

This strengthens an Indian IT company's ability to compete for higher-value projects requiring close collaboration with client leadership.

Coforge’s Encora Deal Highlights Scale of AI M&A

One of the largest transactions identified by Crisil is Coforge's $2.35 billion acquisition of Encora.

The deal significantly expands Coforge's engineering and digital capabilities and illustrates how mid-sized Indian IT firms are increasingly prepared to use major acquisitions to accelerate growth. (ETCIO.com)

The transaction is particularly important because it demonstrates that AI-led consolidation is not restricted to India's largest IT companies.

TCS Acquires Coastal Cloud

Crisil also highlighted Tata Consultancy Services' approximately $700 million acquisition of Coastal Cloud.

The transaction strengthens TCS's enterprise transformation capabilities and provides additional specialist expertise.

For a company with TCS's enormous existing workforce, acquisitions are less about adding headcount at scale and more about adding specific high-value capabilities.

Infosys Buys Optimum Healthcare IT

Infosys' approximately $465 million acquisition of Optimum Healthcare IT was another transaction highlighted by Crisil. (ETHRWorld.com)

Healthcare is particularly attractive for AI-led transformation because the industry generates enormous amounts of data while operating through complex workflows.

Specialised technology capability can therefore help Infosys deepen its position in an industry where domain expertise matters alongside technical skills.

Wipro Acquires Harman DTS

Wipro's approximately $375 million acquisition of Harman Digital Transformation Solutions was also among the transactions cited.

The acquisition strengthens engineering and digital capabilities that can increasingly be connected with AI-led services. (ETCIO.com)

The wider pattern shows Indian IT companies assembling combinations of AI, engineering and domain knowledge rather than pursuing AI models alone.

India’s Largest IT Companies Are Increasing Acquisition Spending

M&A activity has accelerated more broadly.

India's top 10 IT-services companies spent nearly $4.5 billion on acquisitions during the first half of calendar 2026, reflecting the industry's push toward AI, cybersecurity and specialised technology capabilities. (Moneycontrol)

This level of spending indicates that acquisitions have become a major component of competitive strategy rather than occasional portfolio moves.

AI Is Changing the Traditional IT Services Model

India's IT-services industry historically scaled by hiring large numbers of software engineers.

Revenue often increased alongside headcount.

Artificial intelligence challenges that relationship.

AI tools can automate portions of:

coding,

testing,

customer support,

and documentation.

Clients increasingly expect technology vendors to deliver more output without proportionately increasing staffing.

Clients Are Demanding More Productivity for Less

The pressure is already visible in commercial contracts.

Indian IT companies are increasingly shifting from traditional headcount-based pricing toward models linked to business outcomes and productivity as clients demand more output from AI-enabled delivery. (Reuters)

That creates urgency.

Companies that cannot demonstrate meaningful AI capability may struggle to defend pricing.

Outcome-Based Contracts Could Expand

Traditional outsourcing often charges according to:

employees,

hours,

or project milestones.

AI can make these models less attractive to customers because automation reduces the amount of labour required.

Outcome-based pricing instead ties revenue to measurable results.

Examples might include:

faster processing,

lower operating costs,

or improved customer conversion.

This changes the risk profile for IT vendors.

AI Could Compress Labour-Based Revenue

If a project previously required 1,000 employees and AI allows the same work to be completed with 700, a traditional per-person billing model would generate lower revenue.

IT companies therefore need new ways to monetise productivity.

These could include:

platform fees,

AI usage,

intellectual property,

and outcome-based pricing.

Acquisitions can accelerate the transition toward these models.

Mid-Sized IT Companies May Gain Ground

AI is also changing competitive dynamics within the industry.

Smaller and mid-sized firms can sometimes adopt new technologies faster because they have fewer legacy processes.

Recent industry data has shown companies such as Persistent Systems and Coforge growing faster than several larger IT-service companies as customers increasingly value specialised capability and execution speed. (Reuters)

This puts additional pressure on established leaders to acquire specialist businesses.

Acquisitions Can Protect Market Relevance

For the largest IT companies, AI-related M&A is partly defensive.

They already possess scale.

What they need is relevance in newly emerging areas.

A specialist acquisition can provide a capability that allows an incumbent to remain competitive when customer priorities change.

Without such investments, scale can become less valuable.

AI Talent Retention Will Determine Deal Success

Buying a technology company does not automatically transfer all its value permanently.

A large portion of that value can reside in employees.

If key engineers leave after the acquisition, the buyer may lose much of the capability it intended to acquire.

Crisil identified talent retention as one of the critical factors that will determine whether recent AI-related deals create lasting value. (ETHRWorld.com)

Integration Is Another Major Risk

Large companies and startups often have very different cultures.

A specialist AI company may operate with:

rapid experimentation,

small teams,

and decentralised decision-making.

A global IT-services company may rely on more structured processes.

Poor integration can reduce innovation or encourage key employees to leave.

Successful acquisitions therefore require a balance between organisational integration and operational independence.

Cross-Selling Will Be Crucial

One of the strongest economic arguments for these acquisitions is cross-selling.

A small AI company may have strong technology but a limited sales network.

An Indian IT major may have hundreds of global enterprise customers.

Combining the two allows the acquired capability to reach a much larger market.

That potential is one of the central reasons specialist acquisitions can create more value under a larger owner.

Customer Relationships Add Immediate Revenue Opportunity

Some target companies already serve major global corporations.

Acquiring them can therefore provide both technology and customer relationships.

Those relationships may open access to additional projects beyond the original services of the acquired business.

This is especially valuable in industries where trust and domain knowledge are important.

Balance Sheets Have Remained Strong So Far

Despite the rise in acquisition spending, Crisil said the transactions assessed have not materially weakened the balance sheets of the acquiring companies.

Most have been funded through:

internal accruals,

cash reserves,

or share swaps,

with limited reliance on debt. (ETCIO.com)

That is significant because aggressive M&A can create financial risk when companies borrow heavily.

Indian IT Companies Enter AI Race With Large Cash Reserves

The industry's historically strong cash generation gives Indian IT firms an important advantage.

Many established companies have relatively conservative balance sheets.

This gives them capacity to acquire technology without taking on excessive leverage.

It also allows management to respond quickly when attractive targets become available.

Deal Discipline Remains Important

Crisil cautioned that strong credit profiles will depend on companies maintaining discipline.

Acquisitions need to remain reasonable relative to the acquirer's financial capacity.

Large transactions can create problems when buyers overpay or assume unrealistic synergy expectations.

The current wave therefore needs to produce measurable commercial results.

AI Valuations Can Create Overpayment Risk

AI businesses can command high valuation multiples because of strong investor demand.

This increases acquisition risk.

A buyer may pay a substantial premium for capabilities that become widely available within a few years.

Technology cycles are moving unusually quickly.

What appears differentiated today may become commoditised tomorrow.

Open-Source AI Can Reduce Scarcity

Open-source models are improving rapidly.

That means some AI capabilities may become cheaper to access without acquisitions.

Companies therefore need to distinguish between genuinely scarce assets and technology that can be replicated relatively easily.

The most valuable targets may be those combining AI with:

proprietary data,

domain expertise,

and customer relationships.

Domain Knowledge Is Becoming More Important

Generic AI capability alone may not create durable competitive advantage.

Enterprises need technology adapted to specific industries.

A bank needs different AI systems from a manufacturer.

Healthcare organisations have different requirements from retailers.

That makes industry expertise increasingly valuable.

Engineering R&D Becomes Important Acquisition Theme

Crisil identified engineering research and development as another key capability being acquired alongside AI. (ETHRWorld.com)

This reflects the growing convergence between software and physical industries.

Automobiles, factories and industrial equipment increasingly incorporate:

software,

sensors,

and AI.

IT companies want exposure to these engineering-heavy transformation projects.

Automotive AI Could Create Major Opportunity

Vehicles increasingly depend on software.

AI is entering:

driver assistance,

manufacturing,

and predictive maintenance.

Indian IT companies with engineering expertise can support global automakers through this transition.

Acquisitions can provide specialised capabilities faster than building them internally.

Healthcare AI Requires Domain Expertise

Healthcare organisations want AI for applications including:

clinical documentation,

data analysis,

and administrative automation.

But medical systems operate under strict regulation and complex workflows.

Companies with existing healthcare experience therefore have an advantage.

This helps explain the strategic value of industry-specific technology acquisitions.

Financial Services Remain Major AI Market

Banks are another large opportunity.

They are deploying AI across:

fraud detection,

risk management,

and customer operations.

Indian IT companies already have extensive banking relationships.

Adding specialised AI capabilities allows them to sell more advanced services into existing accounts.

AI Could Raise Revenue Per Employee

The long-term opportunity for IT services is not simply cost reduction.

AI can allow companies to generate more revenue without increasing headcount proportionately.

That could raise:

revenue per employee,

and operating productivity.

If companies can capture part of the economic value generated by automation, margins could eventually improve.

But Client Pricing Pressure Could Offset Productivity Gains

The challenge is that customers also understand AI's productivity potential.

Clients may demand lower prices because they know projects require fewer labour hours.

The financial outcome therefore depends on how productivity gains are shared.

Companies with differentiated intellectual property may retain more of the benefit.

Commodity service providers may pass most of it to customers.

Acquisitions Could Help Defend Margins

Owning proprietary technology can reduce dependence on pure labour arbitrage.

A company that provides a unique AI platform can charge for the value created rather than simply the number of employees involved.

This is one reason M&A increasingly targets product and platform capabilities.

India’s IT Workforce Will Also Change

AI-led transformation has significant implications for employment.

Entry-level coding and testing roles are among the areas most exposed to automation.

At the same time, demand is rising for skills including:

AI engineering,

data architecture,

cloud systems,

and cybersecurity.

The workforce mix is therefore changing rather than simply shrinking.

Training Alone May Not Be Fast Enough

Large IT companies are investing heavily in reskilling existing employees.

But internal training cannot always provide deep specialist expertise quickly.

Acquisitions can fill gaps while broader workforce transformation continues.

This creates a two-track strategy: build capabilities internally and buy critical expertise externally.

AI M&A Could Continue

The structural drivers behind the current acquisition wave remain in place.

Enterprise AI adoption is still expanding.

Technology cycles remain fast.

Specialist talent remains scarce.

Indian IT firms continue to hold strong balance sheets.

These conditions suggest AI-related acquisitions could remain an important strategic tool.

Future Deals May Become More Selective

However, acquisition activity may become more disciplined as valuations rise and investors scrutinise returns.

Companies will need clearer evidence that a target can deliver:

customers,

or proprietary technology.

Buying a company simply because it carries an AI label is unlikely to create sustainable value.

Monetisation Is the Ultimate Test

Crisil said the long-term impact of the transactions will depend on integration, cross-selling, talent retention and timely monetisation of acquired AI capabilities. (ETCIO.com)

This is the most important point.

Acquiring technology is relatively easy for companies with large cash balances.

Turning that technology into profitable revenue is much harder.

Investors Will Watch Acquisition Returns

Public-market investors will increasingly evaluate whether M&A improves:

organic growth,

and return on capital.

A successful acquisition should eventually produce financial performance that exceeds the cost of purchasing the business.

If not, acquisitions can dilute shareholder value even when they strengthen headline technology capabilities.

AI Is Becoming Capital-Allocation Question for IT Boards

The acquisition trend demonstrates that AI has moved beyond the technology department.

Boards now need to decide how much capital should be allocated toward:

acquisitions,

partnerships,

and internal R&D.

Those choices will help determine competitive positioning over the next decade.

Conclusion

Nearly half of the M&A transactions undertaken by leading Indian IT companies over the past two financial years have been linked to artificial intelligence and allied capabilities, according to Crisil Ratings.

The shift marks a significant change from the 2019-2024 period, when acquisitions were more commonly focused on conventional digital transformation, cloud computing, process automation, analytics or geographic expansion. (ETCIO.com)

AI has now become a strategic acquisition trigger.

More than 70% of recent targets were based in the United States and Europe, where Indian IT companies are seeking specialist talent, proprietary platforms, domain expertise and established enterprise customers. Major transactions highlighted by Crisil include Coforge's $2.35 billion Encora acquisition, TCS's $700 million Coastal Cloud deal, Infosys's $465 million Optimum Healthcare IT purchase and Wipro's $375 million Harman DTS acquisition. (ETHRWorld.com)

The financial risk has so far remained manageable because most transactions have been financed through cash, internal accruals or share swaps rather than substantial new debt.

The more difficult test now begins.

Indian IT companies must retain acquired talent, integrate specialised businesses and convert new AI capabilities into revenue and profitability.

AI is already changing how IT services are priced, delivered and staffed. Companies that acquire the right capabilities could shorten their transformation by years.

Those that overpay or fail to integrate targets effectively may discover that in one of technology's fastest-moving cycles, yesterday's expensive strategic advantage can become tomorrow's commodity.