Over the last few quarters, one theme has become increasingly clear in conversations with CIOs, CTOs, and business leaders across industries: 

AI is not just transforming delivery—it is reshaping delivery economics. 

From financial services to logistics, telecom to enterprise platforms—AI is accelerating how technology is built, deployed, and operated. 

This raises an important question: 

Are our commercial models evolving at the same pace as our delivery models?

A Subtle but Powerful Shift in Value Creation 

AI is changing where effort sits—and where value is created. 

  • Development cycles are compressing 
  • Automation is expanding across workflows 
  • Intelligent systems are augmenting decision-making 

This doesn’t reduce the role of IT services—it fundamentally redefines it. 

From: 

  • Effort and activity 

To:

  • Outcomes, speed, and business impact 

For CFOs and business leaders, this creates an opportunity to realign how value is measured—and how it is priced. 

The Market is Already Moving 

We are seeing clear signals of this shift: 

  • A majority of enterprises now have AI embedded in at least one business function 
  • Enterprise AI investments continue to grow at a double-digit pace year-on-year 
  • Productivity gains from AI are beginning to influence how large IT programs are structured and evaluated 

At the same time, there is an increasing focus on ROI transparency, cost optimization, and value realization. 

This combination is what’s driving the need to rethink commercial models. 

Evolving Commercial Models: Expansion, Not Replacement 

It’s important to be clear: 

Traditional models like time-and-materials (T&M) and fixed price continue to play an important role, especially where: 

  • Scope is evolving 
  • Complexity is high 
  • Flexibility is required 

However, AI introduces new dimensions that require us to expand beyond a single-model mindset. 

What We See Emerging 

1. Outcome-Linked Components  A portion of engagements tied to measurable outcomes: 

  • Efficiency gains 
  • Cycle time reduction 
  • Automation impact 

2. Hybrid Commercial Structures  Combining: 

  • Predictable base (effort-aligned) 
  • Variable layers (value or usage-linked) 

3. Consumption-Aware Models  With AI-driven delivery, the following become relevant components of cost and pricing: 

  • Compute usage 
  • Platform consumption 
  • Model execution 

4. Shared Value & Risk Models  A more collaborative approach where: 

  • Value creation is aligned 
  • Risk is distributed appropriately 
  • Incentives are structured for long-term outcomes 

The objective is not disruption—it is alignment between effort, value, and outcomes. 

The New Layer: Governance in an AI-Driven World 

AI introduces a dimension that traditional contracts did not fully account for: 

Systems that can influence or execute decisions 

This requires commercial frameworks to evolve beyond scope and pricing, to include: 

  • Clear accountability structures 
  • Auditability and traceability 
  • Data ownership and usage clarity 
  • Explainability expectations 

Across industries, this is becoming central to building trust in AI-led delivery. 

Balancing Innovation with Cost Predictability 

One of the most consistent themes in CFO conversations is: 

How do we maintain cost predictability in an AI-driven environment? 

It’s a valid concern. 

AI introduces: 

  • Variable consumption patterns 
  • Scaling costs based on usage 
  • New cost categories (models, compute, orchestration) 

A Practical Approach 

  • Establish baseline cost structures for stability 
  • Introduce controlled variable components 
  • Build transparent measurement and reporting 
  • Enable periodic recalibration 

Predictability is no longer about fixed structures—it is about visibility, control, and adaptability. 

 A More Collaborative CFO–CXO Conversation 

This shift creates an opportunity to rethink how we engage—not just commercially, but strategically. 

Moving from: 

  • Cost negotiation 

To: 

  • Value alignment 

Key questions we should be asking together: 

  • What outcomes truly matter? 
  • How should value be measured? 
  • Where should flexibility be built in? 
  • How do we ensure governance without slowing innovation? 

Our Perspective at Saksoft 

At Saksoft, we see this as an opportunity to reimagine commercial models alongside delivery transformation. 

We work with enterprises across industries to: 

Design Balanced Commercial Structures 

  • Aligning predictability with flexibility 
  • Linking pricing to value realization 

Enable AI-Led Delivery Models 

  • Integrating AI into engineering and operations 
  • Supporting evolving, adaptive delivery frameworks 

Embed Governance, Quality, and Trust 

  • Ensuring traceability and compliance 
  • Aligning with enterprise risk and control expectations 

The focus is simple:  Create commercial models that scale with AI—while staying grounded in business outcomes. 

Final Thought 

AI is not just a technological evolution.  It is redefining how value is created, delivered, and measured. 

That shift demands a corresponding evolution in commercial models. 

For CFOs, CIOs, and business leaders, the question is no longer whether to adopt AI,  but whether commercial structures are aligned to fully realize its value. 

Because the organizations that succeed will not just adopt AI faster.  They will align value, cost, and outcomes more intelligently.