Embedding AI Across the Value Chain for Smarter Operations, Leaner Delivery
By Rohit Kumar, SVP and Chief Operating Officer, Cognizant
Outliving the hype, the trillion-dollar potential of artificial intelligence (AI) is playing out for real as businesses transform across industries. From basic workflow automation to AI agents handling complex tasks with minimal human interference, AI is elevating everything from workflow scheduling and demand forecasting to vehicle routing, quality control and marketing.
With analytical AI and generative AI adoption gaining ground in multiple organisational functions – IT, sales & marketing, software engineering, service operations, knowledge work, among others, their powerful impact is becoming visible across the entire value chain. Several studies corroborate this uptake. For instance, over 75% of organisations in a McKinsey study confirmed using AI in at least one function.
Experts believe the phase of pilots and prep work will soon transition to an era of confident AI adoption. Possibly encouraged by early returns, organisations are showing greater urgency than ever to embed AI into operations. Faced with rising client expectations and the complexity of multi-tower, multi-geography delivery models, they seek smarter, more adaptive operations – the kind AI promises.
Moreover, the technology is advancing rapidly, prompting organisations to accelerate investments or risk missing out. Cognizant’s global research estimated that in 2024 alone, large organisations spent an average of $47.5 million on generative AI. The need for speed is also real – about 70% of leaders were worried that they were not moving quickly enough.
Widespread AI adoption is on the cards, but…
Clearly, AI is no longer a future aspiration—it’s a present-day imperative. However, organisations often struggle to extract full value from their AI investments. One of the stumbling blocks to widespread generative AI adoption is the disconnect between strong leadership commitment and insufficient operational readiness.
Another area of concern is the gap between business enthusiasm and consumer perception around AI. Nearly three-quarters of the executives surveyed believe it is crucial for a successful business. On the other hand, in a different survey of US-based consumers, not even a third felt they could trust generative AI.
Unlocking AI’s transformative potential with the right building blocks
While many organisations are seeing early gains from generative AI investments, the top performers will be those that build AI deep into the operational fabric, according to a PwC survey. What gives them this distinct edge is their strategy of building. This offers a way forward for organisations looking to draw more value from AI.
The typical inhibitors must be overcome by establishing the foundational elements for AI readiness. This calls for a structured approach: modernising data infrastructure, overhauling legacy systems, and investing in AI talent.
Importantly, this investment must be done strategically. The availability and cost of talent can prove to be another major inhibitor – Industry experts have already warned us of a worldwide human talent shortage exceeding 85 million by 2030. This highlights the need to prioritise how we bring existing workforces to become AI-ready through upskilling and enablement.
The human dimension is equally critical and needs nurturing
Legal experts focusing on client needs rather than hefty paperwork, teachers gaining more time to reimagine course material, doctors spending more time with patients than on administrative work — this is the promise of AI to free up human resources to high-value work.
However, on the flipside, humans may get too engrossed in validating and monitoring AI and not utilise the freed-up time effectively. Exceptional human skills may be lost as a result. Over-reliance on AI without human intuitiveness may adversely impact the quality of outputs and outcomes and even taint brand reputation.
It is, therefore, important for businesses to take a balanced approach to using AI for efficient workflows. At the same time, they must nurture critical human skillsets by focusing on developing and retaining their expertise through continuous learning opportunities and hands-on tasks.
The path ahead
Successful AI adoption hinges on effective change management and fostering a culture that embraces experimentation and problem-solving, especially in the face of ambiguity. The key to this is an organisational mindset that values both human and AI contributions, where innovation is encouraged and failure is seen as a stepping stone to course-correction.
Given the importance of building trust in AI, organisations must consciously cultivate an AI-friendly culture grounded in responsible AI principles. Additionally, the policy makers across the globe have to continuously evaluate the current education system to develop skills of the future beyond the traditional 3 R’s in order to future proof the future generations.
As organisations move towards smarter operations and leaner delivery, it isn’t just about deploying AI —they must also ensure AI is embedded thoughtfully, sustainably, and inclusively across the value chain.