The AI revolution in IT services: Why mid-size companies are set to disrupt the industry

In the rapidly evolving landscape of IT services, a fascinating pattern is emerging: mid-sized companies are positioning themselves to lead the AI transformation race, potentially outmaneuvering their larger competitors. This insight comes from Sidu Ponnappa, former CIO of Gojek and current CEO of RealFast, who brings a unique perspective on how AI and LLMs are reshaping the IT services industry from the ground up.

The David and Goliath Scenario

While industry giants like Accenture are pouring billions into AI initiatives—with Accenture alone having committed $3 billion and already spent $2.1 billion—their focus remains primarily on building AI talent pools and service capabilities. This creates an unexpected opening for mid-sized companies to take the lead in actual technological transformation.

Why? The answer lies in what Harvard professor Clayton Christensen famously called the "innovator's dilemma". Large incumbent firms are caught in a bind: they have substantial existing revenue streams based on traditional delivery models, often with multi-year contracts. This creates a powerful disincentive to disrupt their own business models, even in the face of transformative technology.

The compound effect of AI in IT services

The transformation potential of AI in IT services isn't just about replacing human tasks—it's about fundamentally reimagining how services are delivered. Even modest improvements of 10-20% in individual tasks can create dramatic improvements in overall delivery speed when applied across entire workflows.

Consider this scenario: A team completes their work and sends it to a centralized security team for review. Traditionally, this could mean days of waiting as the security team serves multiple projects. When AI accelerates each step in the process, these wait times shrink dramatically, creating a compounding effect that can improve overall delivery velocity several times over.

The evolution of business models

The IT services industry has traditionally operated under three main business models:
1. Time & Materials (T&M): Clients pay for the time spent on their projects
2. Fixed Price: Vendors commit to delivering a specific scope for a set price
3. Outcome-based: Vendors are paid based on achieved results (rare due to complexity)

AI is set to disrupt this traditional framework. The T&M model, in particular, may become obsolete as AI dramatically accelerates delivery times. When a prototype can be turned around in hours rather than weeks, the fundamental basis for billing by time becomes questionable.

Why mid-size companies have the advantage

Mid-sized IT service companies are uniquely positioned to lead this transformation for several reasons:

1. Agility: They can more quickly adapt their entire organization to new delivery models
2. Risk Tolerance: They're more willing to experiment with new approaches to win business from larger competitors
3. Less Legacy Burden: They have fewer long-term contracts and established processes to protect

The right way to implement AI in IT services

For companies looking to implement AI effectively, here are the key considerations:
Target the Right Processes

Look for workflows that are:
- Cash-intensive
- Heavily dependent on human resources
- Primarily text-based
- Have clear metrics for success

Focus on Internal First

While customer-facing AI applications are tempting, they carry significant risks. Internal applications, where outputs can be reviewed by employees before reaching customers, offer a safer starting point for transformation.

Prioritize Impact

Focus on areas where productivity improvements directly translate to revenue or margin improvements. This creates a clear business case for transformation and helps secure buy-in from stakeholders.

The state of AI implementation

It's important to note that we're still in the early stages of this transformation. The current state of AI frameworks and tools is comparable to web development in the late 1990s—powerful but not yet fully mature. Full commoditization of AI services is likely 2-5 years away, making this the perfect time for forward-thinking companies to build their capabilities.

Looking ahead

The IT services industry is standing at the cusp of its own industrial revolution. For the first time, we have automation technology capable of reasoning and making decisions that previously required human intelligence. This isn't just about doing the same things faster—it's about fundamentally transforming how IT services are conceived, delivered, and measured.

For mid-sized IT service companies, this represents a once-in-a-generation opportunity to leapfrog larger competitors. However, success will require careful planning and execution. Companies need to be particularly cautious about building large teams based on traditional unit economics, as these fundamentals are likely to shift dramatically as AI capabilities mature.

The bottom line

The coming years will likely see a significant reshaping of the IT services landscape. While large companies will eventually adapt, mid-sized companies that move quickly and intelligently to embrace AI transformation have a unique opportunity to capture market share and establish themselves as leaders in the new AI-first era of IT services.

For anyone in the IT services industry, the message is clear: the time to start planning for AI transformation is now. The winners in this new landscape will be those who can successfully navigate the transition from traditional service delivery to AI-augmented delivery while managing the risks and challenges along the way.