By Prakash Pasupathy 

Not long ago, ChatGPT burst onto the scene and shifted our perception of AI from futuristic buzzword to mainstream necessity. Soon after, a host of new large language models—culminating in DeepSeek—began tackling tasks once reserved for armies of human programmers and analysts. For the software services industry, this surge of AI innovation has been a wake-up call: Those who cling to staff-heavy, legacy contracts risk being outmanoeuvred by leaner competitors—or even their own clients deploying self-service AI platforms. 

Real-Time Disruption: When Traditional Models Hit a Wall

Layoffs & Restructuring

In March 2024, Accenture announced it would move 3,000 roles to AI-focused consulting and automation projects. With client budgets shifting toward agile AI solutions, even this global powerhouse had to evolve or risk losing ground. This reallocation highlights the growing demand for faster outcomes with fewer resources, making traditional, human-intensive services far less appealing in a world where efficient AI workflows reign.

Shift in Client Spend

By July 2024, Wipro lost an USD 80M BFSI deal when the client transitioned to an in-house automation approach. As user-friendly AI platforms proliferate, organizations can often do more with fewer external vendors. This signals a swift departure from large, multi-year staff augmentation deals toward nimble, automation-first engagements that deliver immediate business impact.

Big Tech’s Grand AI Entrance: Friend or Foe?

AWS, Microsoft, and Google

AWS’s Bedrock, Microsoft’s Copilot, and Google’s Duet AI each promise to streamline AI adoption—potentially reducing hours that traditional vendors once billed. Yet these platforms also create opportunities for providers adept at integrating AI into complex, multi-cloud ecosystems. Firms that can orchestrate these solutions effectively will differentiate themselves from competitors still pushing outdated, labour-intensive models.

SaaS Providers Go Vertical

Salesforce’s AgentForce and Adobe’s Firefly embed AI directly into their core offerings, automating everything from customer service to creative workflows. While this bundling can shrink the scope of custom projects, it still leaves room for service providers who excel at large-scale deployment, governance, and optimization—especially in regulated industries.

Deals Won vs. Deals Lost: The High-Stakes AI Game

Deals Won with AI

LTIMindtree secured a USD 200M contract in late 2024 by showcasing advanced AI skills, while Infosys landed a major healthcare project integrating RPA with generative AI to streamline billing and data compliance. These wins confirm that clients are willing to pay a premium for genuine AI capabilities backed by deep domain expertise.

Deals Lost to Self-Service

Meanwhile, global healthcare and manufacturing clients are increasingly choosing internal AI solutions over third-party outsourcing, thereby slashing project scopes or cancelling them outright. Without specialized domain knowledge, regulatory insight, or robust solution architecture, many service providers risk being supplanted by cloud-native tools that can be deployed with minimal external help.

Surviving and Thriving: The New Business Models

1. Co-Innovation & IP Sharing

Build AI products in tandem with clients, jointly owning the intellectual property. This not only deepens relationships but also diversifies revenue through licensing arrangements within the same vertical.

2. AI Governance & Security

With the EU AI Act and other regulations on the horizon, ensuring compliance and data privacy is paramount. Specialized advisory services can differentiate you from commodity vendors and establish you as a trusted regulatory and risk-management partner.

3. Outcome-Based Contracts

Tie fees to tangible results like cost savings or revenue growth. As clients demand verifiable ROI, linking payments to business outcomes aligns your incentives—and fosters lasting partnerships.

4. Vertical AI Accelerators

Offer pre-built AI modules for BFSI, healthcare, retail, or manufacturing to deliver immediate value. Rapid deployment and measurable wins can demonstrate your competence far more convincingly than multi-year implementations.

What IT Services Companies Must Do Now

1. Reskill & Upskill

Master leading AI frameworks such as Azure OpenAI, Google Vertex AI, and AWS Bedrock—not just to deploy off-the-shelf solutions, but to create specialized add-ons that address unique business pain points.

2. Become a Strategic Advisor

Commodity coding is being automated away. Clients increasingly look for high-level consultants to identify and implement AI-driven opportunities that deliver concrete, lasting impact.

3. Build Partnerships

Collaborate with cloud providers, SaaS vendors, and emerging AI startups. Acting as the “connective tissue” for disparate systems will elevate you from a mere contractor to an indispensable business partner.

4. Stay Nimble

AI evolves at breakneck speed. Embrace continuous learning, pilot novel commercial models, and remain ready to pivot as new technologies emerge.

Looking Ahead: Embrace AI or Risk Irrelevance

Generative AI and AI in general isn’t just another technology wave—it’s a paradigm shift in how software and services are delivered. While it can diminish some revenue streams by automating manual processes, it also unleashes unprecedented opportunities for innovation, licensing, and high-value consulting engagements. Firms that proactively adopt AI-led strategies—rather than staunchly defend traditional models—can unlock new growth trajectories and fortify themselves for an AI-driven future.

The author is a Product & AI Executive.

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